chapter 3 gis database 3.1 introduction

The Study on Integrated Water Management in the Republic of Bulgaria

Final Report - Main ReportChapter 3

JICA CTI Engineering International Co., Ltd. 3-1

CHAPTER 3 GIS DATABASE

3.1 Introduction

The project objective, concerning GIS as stated in the Inception and Interim Report, is the development of GIS Database (GIS-DB) for storing all basic data and information needed for the river basin management. The GIS database and the integrated basin analysis model are effective tools for the development and update of the river basin management plan.

The main purpose of GIS-DB for MoEW is to create an effective geo-spatial database, using contemporary GIS principles and technologies, based on international and national standards and legislation.

The GIS-DB is designed to provide MoEW and related organizations with accurate and up-to-date geographic information, related to the river basin management.

The development of the GIS-DB is based on the existing technical infrastructure (software, hardware) of MoEW and related institutions, but it introduce and implement additional software products, technologies and procedures for use of geographical data.

The general functions for the use of the GIS-DB for MoEW are:

• Collection and integration of digital and non-digital data from variety of sources and formats to a standardized and structured model;

• Storing of geographic information and other related non-spatial information on a geodatabase level;

• Actualization of the geographic and other related non-spatial information;

• Performing of analysis and modeling of the geographic information;

• Facilitating the exchange of geographic information between the different informational databases within MoEW system;

• Exchange of geographic information with external systems (other ministries, governmental institutions, European commission).

Final Report - Main Report Chapter 3

The Study on Integrated Water Managementin the Republic of Bulgaria

3-2 JICA CTI Engineering International Co., Ltd.

The organizational structure of the GIS-DB will be in MoEW (Water Directorate), ExEA and four RBDs.

The informational scope of GIS-DB includes three main parts (see Figure 3.1.1):

• Core Portion of GIS-DB – basic data, including fundamental data common to all basin directorates;

• WFD Portion of GIS-DB – specialized data, required by the Water Framework Directive;

• Local Portion of GIS-DB – specialized data, used by River Basin Directorates and MoEW, following the Water Act regulations.

This figure illustrates the main parts of the GIS Data Model.

The Core Portion includes all fundamental data, which covers the whole territory of Bulgaria. It provides the “common picture” and up-to-date map of country, including over 40 layers of information.

Local Portion of the Data Model provides information, which is generated and used by the River Basin Directorates. The Local Portion of the Data Model is build and maintained “on the top” of the Core Portion.

WFD portion of the Data Model provides information for the reporting requirements to EU. This data is generated from Core Portion and Local Portion, following the WFD data requirements.

All these three parts form an Integrated GIS Data Model for MoEW and RBDs.




3.2 Main Principles and Stages of GIS Data Modeling and Development

3.2.1 Main Stages in GIS Data Model Development

All GIS systems are built using formal models that describe how things are located in space. A geographic data model defines the vocabulary for describing and reasoning about the things that are located on the earth.

Data modeling is simply building a structure for data, including tables, relationships, specifications, metadata, identification, feature definition, topology rules, etc. The essential tasks in these activities include:

• Gathering of information and requirements analysis for:

• Maps and visualization products required;

• Analysis and decision support products required.

• Design and development:

• Conceptual design: identify data, metadata, specifications, relationships, etc;

• Physical data model: identify GDB feature datasets, classes, relationships, domains, subtypes, geometric networks, linear referencing systems, topology rules, etc.

Through the project the stage of assessment and requirements analysis included two main tasks:

• Collection of spatial data from MoEW, RBDs, ExEA, NIMH, NSI, MAF and many other governmental institutions;

• Collection data resources regarding WFD regulations, Water Act regulation and other Bulgarian, European and International regulations and standard.

Based on the collected data and resources and after evaluation and validation of the data we started the design and development of the GIS Data Model.

The design stage including conceptual modeling of the data often require document, describing what will be in the data base, how data will be organized, etc. Developed during the project are conceptual and detail technical documents for all three main parts of the data model.

After the design of the conceptual data model we started the development of the physical data model. An ongoing procedure of these activities was constant collection and validation of spatial and non-spatial data to be loaded in the final GIS database.

The figure below gives an overview of the Data development activities and other activities during the project.




GIS-DB Development Activities in the study

The Design for Technology or Guideline for future Integrated Information System (IIS) of MoEW and related institutions was produced in the form of Terms of Reference for IIS.

The training was organized in training courses on the main parts of the data model.

3.2.2 Main Elements of the GeoDataBase

The ESRI GeoDataBase format that is used for the physical development and implementation of the GIS Data Model. The geodatabase supports a variety of modeling, management, and analysis functions. One of its key benefits is that its implementation of tables, feature classes, feature dataset, and rules allows you model reality more closely than was possible with other data models. The geodatabase data model can minimize the differences between logical and physical models of reality by incorporating more intuitive data objects. The GeoDataBase provides many advantages such as:

• Centralized spatial and attribute storage;

• Easy to use standard behavior rules including domains, subtypes, topology and networks;

• Multiple customization options;

• Easy to import, export and share schema with or without data.

GeoDataBase contains various types of objects:

• Tables - store non-spatial objects like monitoring data for hydrometric stations;

• Feature classes are collections of lines, points or polygons. Specialized feature classes are used to store annotation, dimension and route features;

• Feature datasets are container for feature classes that share a common spatial reference. They are required for geometric networks and topologies;

• Relationship classes manage thematic relationships between tables, feature classes, or a combination of the two. They enforce referential integrity between the origin and destination classes;




• Geometric networks are specialized topological relationships between line and point feature classes that are used to perform analysis on directed flow network systems;

• Raster datasets are gridded data derived from a variety of sources (IMG, PG, etc.);

• Raster catalogs are tables that reference a collection of raster image files;

• Survey datasets store survey information and can group survey data into Project’s, for direct use or improvement of existing feature geometry;

• Toolboxes contain geoprocessing tools used in the geoprocessing framework;

• Behavior rules may be created to define legal attribute values, thematic relationships between classes, topological relationships between features, and connection between network features;

• Linear referencing system – one-dimensional linear system (rivers) for input and recording of data.

All data types and the main advantages of the GeoDataBase provide state of the art capabilities for MoEW GIS data model.




3.3 Structure of GIS Data Model

As described in the introduction the GIS data model is compiled from three main parts: Core Portion, WFD Portion and Local Portion.

All parts of the data model are in a common coordinate reference system - WGS 84, UTM Zone 35N.

The Core Portion of the data model should be stored and maintained on a central level and distributed to all users (RBD’s) on a regular basis.

The WFD Portion should be produced from the Core Portion on a regular basis as defined in the WFD requirements.

The Local Portion should be developed and maintained on the top of the Core Portion of the Data Model.

Figure 3.3.1 shows the general structure of the data model:

3.3.1 Detail Structure of Core Portion

The Core Portion of the Data Model is build following the main GIS principles for completeness, consistency and accuracy. The Core Portion uses and steps on many national and international standards and regulations in order to produce a standardized data model for the countrywide use.

Main parts of the Core portion are organized on a thematic principle and are as follows:

(1) Thematic Group “Administrative”

This thematic group of data includes information on the administrative – territorial division of the territory of Bulgaria. The data have been structured pursuant to the Administrative – Territorial Structure of the Republic of Bulgaria Act. This Act arranges the development of administrative – territorial and territorial units in the Republic of Bulgaria and the conducting of administrative – territorial changes. Pursuant to the Act administrative – territorial units are regions and municipalities, compound administrative – territorial units in the municipalities are city/town halls and districts, аnd territorial units are populated places and settlement formations. The populated places are towns and villages.




The basic layers relationships include:

"Sub-division of municipality (Zemlishte)" is the aggregate of land properties, belonging to a certain populated place (settlement). The Zemlishtes’ borders shall be identified and defined in an order, stated in an act.

The municipality territory includes the territory of populated places, included in it. The boundary is formed by the zemlishtes’, belonging to the municipality.

Region borders’ amendments could be conducted only along the borders of existing municipalities. The amendment shall be approved by a Decree of the President of the Republic of Bulgaria on a proposal of the Council of Ministers.

Based on existing regulation and collected data we have identified the following layers of information:

• A_BgBorder_Line - this layer represents information on the border of Republic of Bulgaria, like linear feature class.

• A_BgBorder_Poly - this layer represents information on the border of Republic of Bulgaria, like polygon feature class.

• A_BgRegion - this layer represents information on the Planning Regions in the Republic of Bulgaria, like polygon feature class.

• A_BgDistrict - This layer represents information on the Regions in the Republic of Bulgaria, like polygon feature class.

• A_BgMun - This layer represents information on the municipalities in the Republic of Bulgaria, like polygon feature class.

• A_BgZem - This layer represents information on the Sub-divisions of municipalities in the Republic of Bulgaria, like polygon feature class.

• A_BgSettle_Poly - This layer represents information on the populated places in the Republic of Bulgaria, like polygon feature class.

• A_BgPlace_Point - This layer represents information on the populated places in the Republic of Bulgaria, like point feature class.

• Census_2001-2005 - These Attribute Tables represent information on the population in the Republic of Bulgaria, like Attribute Tables.

(2) Thematic Group “Hydrography”

This thematic group includes information on the Basin Directorates’ borders, Water Catchments, River Network, Channels, etc.


The Layer with Basin Directorate borders’ has been developed, using the water catchments’ borders on the grounds of Article 152 of the Water Act. The Basin Directorates’ borders coincide with the state border of the Republic of Bulgaria.




The Layer of River Basins includes the main rivers’ river basins. The river basins coincide with the Basin Directorates’ borders and the state border, with the exception of parts of the border between Danube Basin Directorate and Black Sea Basin Directorate.

The Layer with Water Catchments includes the water catchments of 550 rivers in Bulgaria. The water catchments fall within the water catchment basins’ borders, the Basin Directorates’ borders and the state border. The water catchments have been organized on the basis of two rivers’ inflow or a river and a lake inflow, with the addition of “own” water catchments of significant reservoirs, as defined in Annex 1 of the Water Act.

The Layer with Rivers includes all the rivers in Bulgaria in a scale 1:100 000. Rivers have been structured from the inflow of two rivers or the inflow of a river and a lake (from junction to junction). The rivers fall into the water catchments’ borders, the river basins’ borders, the Basin Directorates’ borders (with the exception of parts of the border between Danube Basin Directorate and Black Sea Basin Directorate) and the state border.

The Layer with Lakes includes all the lakes in Bulgaria in a scale 1:100 000. The Layer with Lakes falls within the water catchments’ borders, the river basins’ borders, the Basin Directorates’ borders and the state border of the Republic of Bulgaria.

The Layer with Channels includes all the channels in Bulgaria in a scale 1:100 000. The Layer with Channels falls within the state border of the Republic of Bulgaria.

The Layer with Linear Referencing System includes a linear system of all the main rivers. The Layer with Linear Referencing System falls within the river basins’ limits, the Basin Directorates’ limits and the state border of the Republic of Bulgaria.

The Layer with Danube River includes the Danube River delineation. The Republic of Bulgaria state border passes along the river midstream and has been defined by the Chief Directorate “Border Police”.

The Layer with Islands includes all islands, which fall into Danube River (Bulgarian and Romanian). The Layer with Islands falls within the Danube River delineation.

This thematic group includes the following layers:

• H_RBD: This layer represents information on the Basin Directorates’ borders in the Republic of Bulgaria, like polygon feature class.

• H_RivBasin: This layer represents information on the river basins’ borders for the I rank rivers in the Republic of Bulgaria, like polygon feature class.

• H_Catchment: This layer represents the Water catchments in the Republic of Bulgaria, like polygon feature class.

• H_River: This layer represents information on rivers in the Republic of Bulgaria, like linear feature class.

• H_Lake: This layer represents information on lakes and reservoirs in the Republic of Bulgaria, like polygon feature class.

• H_Channel: This layer represents information on the Channels in the Republic of Bulgaria, like linear feature class.




• H_River_LRS: This layer represents information on the Rivers in the Republic of Bulgaria (first, second and third rank rivers), as well as linear referencing system.

• H_Danube: This layer represents information on the Danube River in the Republic of Bulgaria, like Polygon Feature Class.

• H_Island: This layer represents information on the Danube River islands, like Polygon Feature Class.

(3) Thematic Group “Transportation”

This thematic group of data consists of information on the road and railroad network at the territory of Bulgaria.


The Layer with Roads is linked to the point layer of settlements (the points of settlements are “attached” to the road lines). The layer of road network is represented via a geometric network, which allows navigation and optimal routes’ determination.

The Layer with Roads and the Layer with Rail Roads fall into the Republic of Bulgaria state border.


• T_BgRoad: This layer represents information on the Road network in the Republic of Bulgaria, like geometric network.

• T_BgRailRoad: This layer represents information on the Rail Road network in the Republic of Bulgaria, like linear feature class.

(4) Thematic Group “Other Data-Reference”

This thematic Group of Data contains additional information on elevations, horizontals, earth cover, soils, geology, etc. for the whole country territory.


• O_BgElevPoint: This layer represents information on elevation points in the Republic of Bulgaria territory, like point feature class.

• O_BgContour: This layer represents information on horizontals in the Republic of Bulgaria territory, like linear feature class.

• O_BgCorine: This layer represents information on land cover in the Republic of Bulgaria territory, like polygon feature class.

• O_BgErosion: This layer represents information on accessibility of soils to erosion at the territory of Republic of Bulgaria, like polygon feature class.

• O_BgSoil: This layer represents information on soils at the territory of Republic of Bulgaria, like polygon feature class.

• O_BgGeology: This layer represents information on the Geology at the territory of Republic of Bulgaria, like polygon feature class.




• O_HydroGeology: This layer represents information on the hydroGeology at the territory of Republic of Bulgaria, like polygon feature class

• O_ProtectedArea: This layer represents information on the Protected Areas at the territory of Republic of Bulgaria, like polygon feature class.

• O_Natura2000_pSCI: This layer represents information on the Special Areas of Conservation borders, pursuant to the EC Habitats Directive, defined in NATURA 2000 Project, like polygon feature class.

• O_Natura2000_SPA: This layer represents information on the Special Areas of Conservation borders, pursuant to the EC Birds Directive, defined in NATURA 2000 Project, like polygon feature class.

• O_Mine: This layer represents information on Mineral Resources deposits at the territory of Republic of Bulgaria, like polygon feature class.

(5) Thematic Group “Rasters and Image Base”

This Thematic gtroup of data contains information for Digital Elevation Model, satellite images, scanned and georeferenced topographic maps for the territory of Republic of Bulgaria.

This thematic group includes five raster catalogs:

• Raster catalog “Satellite”: In this Raster Catalog information is preserved on two satelite images of the Republic of Bulgaria territory. The satellite images have been represented as ortho rectification Landsat ETM (Enhanced Thematic Mapper) in 34 and 35 zones.

• Raster catalog “Elevation”: In this Raster Catalog information is preserved on two Raster Layers: Digital elevation model (DEM) and Hillshade. The DEM is with pixel size 50x50 meters. Hillshade is obtained by DEM via a special algorithm for Multi-Dimensional Oblique Weighting, and the result obtained is a more realistic Hillshade.

• Raster catalog “HydroRasters”: In this Raster Catalog information is preserved on two Raster Layers: Flow Direction and FlowAccumulation, for the Republic of Bulgaria territory. These two layers’ destination is their use in generating of water catchments for a random location of the terrain or for outlining the direction of outflow of a random point at the terrain.

• Raster catalog “TopoMap_100000”: In this Raster Catalog information is preserved on 67 raster images of scannered and georeferenced topographic maps in a scale 1:100 000 for the Republic of Bulgaria territory.

• Raster catalog “TopoMap_25000”: In this Raster Catalog information shall be preserved on raster images of scannered and georeferated topographic maps in a scale 1:25 000 for the Republic of Bulgaria territory. As these maps are present at the Basin Directorates, they could be added in addition to the Geo Data Base.




(6) Thematic Group “Monitoring”

The Monitoring data is stored in the Time Series. The Time Series data model includes data from National monitoring. The GIS information from the stations is connected to the monitoring information from the time series for analysis purposes. Additionally an automatic import procedure is developed in order to fill in all monitoring data from different institutions, different formats and structures into a common database. The import procedure comes with tutorial and step-by step wizard.


• Climatic_Stn: This layer represents information for the climatic stations from NIMH for the territory of Bulgaria, as point feature class.

• GW_Quality: This layer represents information for the GW Quality stations from ExEA for the territory of Bulgaria, as point feature class.

• GW_Springs: This layer represents information for springs from NIMH for the territory of Bulgaria, as point feature class.

• GW_Wells: This layer represents information for wells from NIMH for the territory of Bulgaria, as point feature class.

• Hydrometric_Stn: This layer represents information for hydrometric stations from NIMH for the territory of Bulgaria, as point feature class.

• Precipitation_Stn: This layer represents information for precipitation stations from NIMH for the territory of Bulgaria, as point feature class.

• SW_Quality: This layer represents information for SW Quality stations from ExEA for the territory of Bulgaria, as point feature class.

• Synoptic_Stn: This layer represents information for the synoptic stations for the territory of Bulgaria, as point feature class.

• DHI_IDManager: This table contains information for the automatic DHI ID, which is maintained by the Time Series database.

• DHI_Sensor: This table contains information for links between the GIS objects (monitoring stations) and the table data (monitoring measurement values).

• DHI_TimeSeries: This table contains the information for the Time Series, for each monitoring station.

• DHI_TSGroups: This table contains information for the Time Series groups of monitoring data.

• DHI_TSValues: This table contains information for the Time Series Values and stores the actual measurements.




(7) Part “Analytical Layers”

This Thematic Group of Data contains additional information on Layers, which are used for analysis and modelling in the study. This Group of data shall not be considered as a part of the Core Portion of the data model. As data have been collected and structured for the whole country, they were included as an information of reference in the model supplied.

This thematic group includes three Raster Catalogs:

• Raster catalog “Precipitation”: In this Raster Catalog information is preserved on the precipitation average monthly values in 12 raster layers (one layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000).

• Raster catalog “PET”: In this Raster Catalog information is preserved on the average monthly values of the potential evapotranspiration in 12 raster layers (a layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000).

• Raster catalog “Temperature”. In this Raster Catalog information is preserved on the average monthly values of temperature in 12 raster layers (a layer for each month) and an average annual value in 1 raster layer for a 50 years’ period (1950-2000).

(8) Part “Supplementary Layers”

In the Core Portion of the data model there are also some “Supplementary” data, which includes information from neighboring countries and data for Irrigation systems in Bulgaria. This data is defined as “supplementary” because is collected from different sources and although checked and verified cannot follow the same data quality standards as Core Portion. For example the data for neighboring countries is collected in scale 1:1 000 000 from free sources and can be used for visualization purposes only; the data for Irrigation is collected from different sources – topographic maps in 1:100 000, 1:25 000, different sketches and drawings, site visits and local experts knowledge – although up-to-date and correct this data cannot follow the standards used for other data in Core Portion.




(9) Thematic Group “Neighbour_Countries”

This Thematic group includes data for neighboring to Bulgaria countries. This data can be use for map preparation and general overview of the region.


• N_EU_Borders: This layer represents information for the boundaries of neighboring to Bulgaria countries, as polygon feature class.

• N_EU_Districts: This layer represents information for the districts of neighboring to Bulgaria countries, as polygon feature class.

• N_EU_Settle_Points: This layer represents information for the settlements of neighboring to Bulgaria countries, as point feature class.

• N_EU_Urban_Areas: This layer represents information for the urban areas of neighboring to Bulgaria countries, as polygon feature class.

• N_EU_Catchments: This layer represents information for some catchments of neighboring to Bulgaria countries, as polygon feature class.

• N_EU_WaterObjects: This layer represents information for the water objects of neighboring to Bulgaria countries, as polygon feature class.

• N_EU_Road: This layer represents information for the roads of neighboring to Bulgaria countries, as line feature class.

• N_EU_RailRoad: This layer represents information for the railroads of neighboring to Bulgaria countries, as line feature class.

(10) Thematic Group “Irrigation Systems”

This thematic group of information includes data for Irrigation Systems. This data is extracted from topographic maps from scale 1:25 000, sketches and drawings from Irrigation Systems Company, etc. Additional validation is made based on rivers, settlements and lakes from the Core Portion.


• I_ChannelPipe: This layer represents information for the channels and pipes, used for irrigation purposes, as linear feature class.

• I_CompensatingBasin: This layer represents information for the compensating basins, as point feature class.

• I_Dam: This layer represents information for the Dam, used for irrigation purposes, as polygon feature class.

• I_WaterIntake: This layer represents information for Water Intake, used for irrigation purposes, as point feature class.

• I_PumpStation: This layer represents information for Pump Stations, used for irrigation purposes, as point feature class.




• I_IrrigationSystem: This layer represents information for the Irrigation fields and Irrigations systems, as polygon feature class.

• I_Dikes: This layer represents information for Dikes, as line feature class.

3.3.2 Detail Structure of WFD Portion

This part of the Data Model includes information, necessary for reporting and using of the Water Framework Directive. The information has been developed on the basis of Guidebook No 9: “Implementing the Geographical Information System Elements (GIS) of the Water Framework Directive”. The information in WFD is prepared to the extend of currently available and defined digital data.

This part of the data model includes the following layers:

• Compauth: The Layer full name is Competent authority. This Layer represents information on the competent authorities’ borders, like polygon feature class.

• Cwbody: The Layer full name is Coastal Waters. This Layer represents information on Coastal Water Bodies, like polygon feature class.

• Ecoreg: The Layer full name is Eco region. This Layer represents information on EcoRegions, like polygon feature class.

• Gwbody: The Layer full name is Ground Water Body. This Layer represents information on Ground Water Bodies, like polygon feature class.

• GWStn: The Layer full name is Ground Water Monitoring Station. This Layer represents information on Ground Water Monitoring Stations, like point feature class.

• Lwseg: The Layer full name is Lake Water Segment. This Layer represents information on the Lake Segments, like polygon feature class.

• Lwbody: The Layer full name is Lake Water Body. This Layer represents information on Lake Water Bodies, like polygon feature class.

• Protarea: The Layer full name is Protected Areas. This information represents information on Protected Areas, like polygon feature class.

• RBD: The Layer full name is River Basin District. This Layer represents information on Basin Directorates’ borders, like polygon feature class.

• Rivbasin: The Layer full name is River Basin. This Layer represents information on the River basins, like polygon feature class.

• RivSubBasin: The Layer full name is River Sub Basin. This Layer represents information on the River Sub-basins, like polygon feature class.

• Rwseg: The Layer full name is River Water Segment. This Layer representes information on River segments, like linear feature class.

• Rwbody: The Layer full name is River Water Body. Тhis Layer represents information on River Water Bodies, like linear feature class.

• SWstn: The Layer full name is Surface Monitoring Station. This Layer represents information on Surface Monitoring Stations, like point feature class.




• Twbody: The Layer full name is Transitional Water Body. This Layer represents information on „Transitional Water Bodies”, like polygon feature class.

• Fweccls: This Table describes the status of „Fresh” Waterbodies.

• GWStatus: This Table describes the Ground Waterbodies’ status.

• Pchemcls: This Attribute Table describes the Water bodies’ PhysicoChemical Classification status.

• Saleccls: This Attribute Table describes the „Saline” Waterbodies’ status/ Saline Ecological Classification.

• Swstatus: This Attribute Table describes the SurfaceWaterbodies’ status.

3.3.3 Detail Structure of Local Portion

Local portion of data model includes the following groups of information:

• “Cadastre” group of data;

• “Permissions” group of data;

• “Monitoring” group of data;

• “Other” data.

These groups are organized following the organizational structure of the River Basin Directorates and includes to corresponding GIS information in each department.

(1) “Cadastre” Group of Data

This thematic group of data, including information on the Sanitary Protected Areas, as defined in Regulation No 3 from 16.10.2000 of the Water Act.

The „Cadastre“ group of data is developed for the needs of „Water and Water Economy Cadastre“ Department. The information within the Department is developed and used in a Coordinate system 1970. The data in this group shall be structured in separate Groups of data (Feature Datasets) by zones. The information from this department shall be recorded in the Central Group of data in a coordinate system WGS84, UTM Projection Zone 35N for use from other departments.

“Cadastre” group of data includes the following thematic layers with spatial information and additional attribute tables.

• SPA (Sanitary Protected Areas): This Layer represents information on the Sanitary Protected Areas, within the Basin Directorate territory, like polygon feature class.

• PA_Bath: This Layer represents information on Protected Areas for Bathing, within the Basin Directorate, like polygon feature class.

• PA_Fish: This Layer represents information on Protected Areas for Fish breeding.

• MapSeries_25000: Map series of scanned and georeferenced topographic maps.




(2) “Permissions” Group of Data

Main types of permission – water intake, water use and discharge, structure GIS data with location of permissions – the basic types of Layers. Each type of permission has corresponding purposes. For example gravel excavations or sand pits are located in layer SW_Use, Permission purpose type: gravel excavations.

“Permissions” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers:

• SPA (Sanitary Protected Areas): This Layer represents information on the Sanitary Protected Areas, within the Basin Directorate territory, like polygon feature class.

• PA_Bath: This Layer represents information on Protected Areas for Bathing, within the Basin Directorate, like polygon feature class.

• PA_Fish: This Layer represents information on Protected Areas for Fish breeding.

• MapSeries_25000: Map series of scanned and georeferenced topographic maps.

(3) “Permissions” Group of Data

Main types of permission – water intake, water use and discharge, structure GIS data with location of permissions – the basic types of Layers. Each type of permission has corresponding purposes. For example gravel excavations or sand pits are located in layer SW_Use, Permission purpose type: gravel excavations.

“Permissions” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers:

• P_SW_Intake: This Layer represents information on the location of water intake – surface water, falling within the Basin Directorate territory, like point feature class.

• P_GW_Intake: This Layer represents information on the location of water intake – surface water, falling within the Basin Directorate territory, like point feature class.

• P_MW_Intake: This Layer represents information on the location of mineral water places, falling within the Basin Directorate territory, like a point feature class.

• P_SW_Use: This Layer represents information on the location of places for water use – surface water, falling within the Basin Directorate territory, like point feature class.

• P_GW_Use: This Layer represents information on the location of places for groundwater use, falling within the Basin Directorate territory, like a point feature class.




• P_Discharge: This Layer represents information on the location of places for discharge (domestic and industrial water), falling within the Basin Directorate territory, like point feature class.

• F_HydroFacility_Line: This Layer represents information on hydraulic facilities, falling within the Basin Directorate territory, like a linear feature class. This Layer shall be used for linking HPP and water intake for a HPP, as well as for other objectives (WWTP - discharge of a WWTP).

• F_HydroFacility_Point: This Layer represents information on the location of linear infrastructure systems and facilities, crossing water bodies – aqueducts, bridges, portable networks and lines. This layer is represented as point feature class.

• F_DischargeFacility_Point: This Layer represents information for the Discharge Facility Point, as point feature class. This layer is to be connected to discharge point thought F_HydroFacility_Line.

• F_HPS: This Layer represents information on the location of HPP, falling within the Basin Directorate territory, like point feature class. HPP have been spatially represented with the location of HPP site. Information on the water intake for a HPP shall be available in Water intake Surface Water Layer, with an objective for water use - HPP. The relation between the HPP site and the HPP water intake shall be effected via a „straight” line from F_HydroFacility_Line Layer.

• F_WWTP: This Layer represents information on the location of the Waste Water Treatment Plants, as point feature class.

(4) “Monitoring” Group of Data

The “Monitoring” group of data includes the following thematic layers with spatial information and additional attribute tables. A list of layers:

• Data from permissions with location of structures by basic types of permissions;

• Own monitoring Tabular data.

In addition data are used from:

• Monitoring stations from “Core Portion” of data model;

• Tabular data in a time series’ format.

The monitoring data at Basin Directorates shall include two basic groups of information: data from the National Network for Monitoring of Water and data from own and control monitoring, related to the procedures of issuing of permissions.

The data from the National Network for Monitoring of Water is structured in the „Core portion“ of the data model. The structure is in Time Series, allowing an analysis of statistical rows. The monitoring data are still under processing and they shall be input into the developed structure of data.

The own monitoring data, affected on the Basin Directorate territory, shall be attached to the GIS objects form the „Permissions“ Group of data. The place of performing the own




monitoring shall coincide with the location of the permission in GIS, and the relation between the Protocols for measurements and the object in GIS shall be realized along with the number of permission and the serial number of point (оbject) from the respective permission.

(5) Group of Data “Other”

The thematic group of data „Other“ include other data, which shall be used at the Basin Directorates, but which is not directly related to cadastre, monitoring and permissions. Тhese data shall be obtained from sources outside the Basin Directorates or they shall be developed according to the needs of certain departments/experts within the Basin Directorates. Тhis group of data should be expanded and supplemented.

The group of data “Other” includes the following thematic layers with spatial information and additional attribute tables. A list of layers:

• O_Waste_Landfills: This Layer represents information on waste landfills in the Basin Directorate territory, as point feature class.

• О_Lagoon_Sites: This Layer represents information on earth lagoons in the Basin Directorate territory.

• O_Uranium_Mines: This Layer represents information on Uranium extraction mines in the Basin Directorate territory, as polygon feature class.

• O_Industry: This Layer represents information on industries (without permissions) in the Basin Directorate territory, as point feature class.

• O_Tailing_Ponds: This Layer represents information on the tailing ponds in the Basin Directorate territory, as polygon feature class.

• O_Pestiscide_Storages: This Layer represents information on the pesticides’ storages in the Basin Directorate territory, as point feature class.

• O_CrossSection: This Layer represents information on river cross-sections, falling within the Basin Directorate borders, as point feature class.




3.4 GIS Activities

Apart from the GIS Data Model development other main GIS activities during the project were as follows:

• Establishment of GIS workgroup;

• Development of Terms of Reference for Integrated Information System for MoEW and related institutions (supplied as separated Annex);

• Training of counterparts.

3.4.1 GIS Workgroup Activities

The GIS Workgroup was established with the main purpose for discussion, review and acceptance of the common structure of the GIS Data Model, including all main parts.

There were five official meetings of the GIS workgroup and one additional interim meeting.

The GIS Workgroup includes participants from MoEW, all River Basin Directorates, ExEA and JICA Study Team members.

Main topics, which were discussed, were as follows:

• Review of the collected data from all RBDs: data condition and structure;

• Review and discussion on Core Portion of data model – review of documentation and geodatabase;

• Review and discussion on WFD Portion of data model – review of documentation and geodatabase structure;

• Review and discussion on Local Portion of data model – review.

Detail documentation for each main part of the data model was delivered to the Workgroup participants. All participants provided feedback with comments and recommendations for improvement of the data model. Based on the feedbacks the structure of all part of the data model was modified and finalized.

Each meeting of the Workgroup and all activities and decisions were documented with official meeting protocols signed by all participants.




3.4.2 GIS Training

The GIS training includes trainings of all members of GIS Workgroup. For EABD and WABD there was training on their premises, which included additional GIS personal from different departments. Main topics of the trainings were:

• Introduction of main building blocks of GeoDataBase;

• Review and use of Core Portion of the Data Model;

• Review and use of the WFD Portion of the Data Model;

• Review and use of the Local Portion of the Data Model.

Each training was conducted based on a preliminary developed and approved program and with list of participants.




3.5 Conclusions, Recommendations and Results

In the first phase of the project was conducted extensive evaluation of the current status of MoEW and RBD’s in regards to GIS.

The main conclusions of the analysis of GIS in MoEW system, as stated in the Interim Report are as follows:

• A major problem specified explicitly by all four RBDs is the condition of GIS data, especially for layers standardization, work methodology standardization, boundary area issues and other. There is no consistent data format and data model for four basin directorates and MoEW;

• There is a variety of different digital data, collected from different organizations, in different time periods, different coordinate systems and scale. The data is structured, maintained and use in different ways within the directorates and MoEW. This cause significant problems inside the basin directorates departments, between the basin directorates and between basin directorates and MoEW (especially for reporting activities to EC);

• The condition of GIS data in all four RBDs includes (based on the collected and verified data):

• Topological errors (by WFD topological rules and other standards);

• Referential errors (compared to 25 000, 100 000 topographic maps, satellite images and additional map sources for reference – hydrological maps and atlases of Bulgaria);

• File naming issues (layers, attributes) – use of different naming conventions in different RBDs;

• Metadata issues – lack or no update and maintenance of metadata information;

• Digital formats – use of different formats for data storage (GeoDatabase, shape files, MS Excel, MapInfo Tab, MS Access, ZEM, text files).

• Lack of GIS working group or GIS coordination unit in MoEW, which should produce main guidelines and coordinate activities between RBDs;

• A minimum GIS hardware and software is installed in the RBDs allowing initial input of basic GIS data and fulfillment of most urgent GIS tasks;

• To the present day sector experts as additional tasks apart from their main obligations undertook the GIS activities in the RBDs. Generally there is constant lack of IT and GIS expert;

• In all RBDs the GIS experts feel the need for specialized GIS training;

• Lack of clear GIS DB specifications;

• Lack of clear metadata specifications.




The priority matters identified in the Interim report for improving GIS status are:

• Increase the Number of GIS staff and additional training for existing staff;

• Establishment of GIS Database Specification and Explicit metadata;

• Developing of spatial data from accurate and reliable sources with will allow correct modeling and analysis activities;

• GIS maintenance and guideline.

Through the second phase of the project, the GIS activities were concentrated on:

• Ongoing development of data for Core Portion, WFD Portion and Local Portion, based on accurate and reliable sources;

• Ongoing development and support for the development of water quality and water quantity models;

• Finalization of clear GIS Database specifications for Core Portion with complete digital data;

• Finalization of clear GIS Database specifications for WFD Portion and input all available and defined data in the project time frame;

• Finalization of clear GIS Database specification for Local Portion and input most of the available data for WABD, EABD and pilot areas in BSBD and DBD;

• Development of extensive documentation for each part of the data model;

• Establishment and collaboration of GIS Workgroup for development of data model and related GIS issues;

• GIS Training of counterparts.

The main results of the GIS activities from the study can be summarized as follows:

• Development of standardized data model for the needs of MoEW and RBDs, which includes Core Data Model, WFD Data Model and Local Data Model;

• Technical GIS training of MoEW, ExEA and RBDs personal;

• Establishment and collaboration of activities of the GIS technical workgroup;

• Development of TOR for future information systems of MoEW and RBDs.

The main recommendations for future work activities in regards to GIS are as follows:

• MoEW should continuously maintain and expand the Core Portion of the Data Model. This could be achieved with the specialists of Water Directorate, specialists of ExEA or to be outsourced to external company. Considering the available resource may be most appropriate solution is to outsource the maintenance of Core Portion to external organization, which will be responsible to update on a regular basis;

• RBDs should continuously maintain and further develop and populate the Local Portion of the Data Model;




• RBDs should further populate the WFD portion of the data model based on the WFD time frame requirements;

• MoEW should continue the meetings of the GIS workgroup on a regular basis in order to discuss the data maintenance; further data model development and all other GIS related issues (training, software, hardware, work procedures);

• MoEW should use and implement the proposed TOR for Integrated Information System.




CHAPTER 3

3.1

Main Report

Chapter 3

Figures




Figure 3.1.1 General Structure of the Data Model




3.2

3.3

Figure 3.3.1 General Structure of the GIS Data Model.




CHAPTER 4 INTEGRATED RIVER BASIN ANALYSIS MODEL

4.1 Modeling Concept

4.1.1 General

Figure 4.1.1 shows the data treated in the study. There are several kinds of data to be handled as follows.

• Level 1: Core Data • Level 2: Waterbodies Data • Level 3: Monitoring Data • Level 4: Basic Analysis Data • Level 5: Spatial Distribution Analysis Data • Level 6: Water Management Plan Data

The model developed in the study will be mainly used to produce the Level 5 and Level 6 data using the other level data. In other words, the model can be utilized for the following purposes.

• Assessment for existing condition • Observed point data to spatially distributed presentation with some

assumptions • Planning such as long term strategy for water management, program measures

• Checking effectiveness of some of program measures • Reference for permission based on long term strategy for water

management

The model developed in the study is not suitable for the following purposes due to insufficient data and information so far.

• Operational decision such as daily reservoir operation and flood warning • It requires additional data, information and model development with

additional modules and so on (or different types of model might be required).

There are general notes regarding a model as follows.

• Model is not perfect. It is simplified representation of actual world. However, it can help thinking of what happens and what will happen.

• If a model is used for decision support, it is not necessary for the model to be perfect. However, it should be transparent in its assumption and methodology. Conesus on the model is important.

The present study proposes the model that will be directly handled by Basin Directorates and will support their river basin management activity. Transparency of the model with clear explanation on assumptions for the model will be important for this purpose.




4.1.2 Two Different Types of Model

(1) Simple Model and MIKE11 Model

In the present study, two different types of model are proposed. One is “Simple Model”, which is based on basically simple mass balance and can be working in general software such as MS-Excel. Another one is “MIKE11 Model” which is well known but requires specific software for implementing the simulation. Characteristics of the two models are summarized as below (see also Figure 4.1.2).

• Simple Model • No specific modeling software • Spread sheet calculation only • Point representation at key points for management • Time scale: Monthly or Average in whole year and/or summer time • Reference for permission • Scenario setting for improvement plan

• MIKE11 Model • Specific software (MIKE11& MIKE BASIN) • Physical process-based model • Spatio-temporal representation along river network • Time scale: Daily • Detailed simulation for confirming effects of improvement plan

As for MIKE11 model, the following modules are introduced in the present study.

• Rainfall-Runoff Module (MIKE11-RR) • Conversion of Precipitation to Runoff in Catchment • NAM model has been selected.

• Hydro Dynamic Module (MIKE11-HD) • Conversion of Inflow (Runoff in Catchment) to Flow Condition along

River

• Water Quality Module (MIKE11-AD & Eco-Lab) • Conversion of Flow Condition and pollution load in River to Water

Quality Condition along River

It is noted that MIKE11 can run the above components simultaneously.

MIKE11 model is selected because of its integrated treatment on water quantity and quality. HEC model, which is public domain software and thus could be one of alternatives, does not have water quality module in the current version. The Pollution Load Calculator as a part of MIKE11 model in the present study, which is an extension of ArcGIS, can be also integrated in order to prepare some of input files on pollution load for MIKE11 model simulation in a transparent way on GIS platform. Furthermore, MIKE11 model was introduced in the previous JICA Study on the Maritsa River Basin. The concept and parameter setting developed in the previous JICA Study will be referred in




the present study so that the model in the present study will be efficiently developed in a limited timeframe.

(2) Structure of Modeling Environment

Figure 4.1.3 shows the proposed structure of modelling environment. The GIS-DB is a base of the modelling environment.

MIKE11 model development and simulation are implemented within MIKE ZERO platform, which is provided by DHI as a native platform for MIKE11 model. For development of a model, some layers in the GIS-DB such as river network and catchment can be imported to MIKE ZERO platform.

MIKE11 model requires a lot of time series data for input, although format of input file is special format for MIKE11 model. For smooth implementation of the simulation using the GIS-DB, MIKE BASIN Temporal Analyst and Pollution Load Calculator, which are extensions of ArcGIS, as well as Excel sheet, are utilized for preparing input files for MIKE11 simulation. Conversion of .xls file, .txt file and/or Geodatabase (.mdb) to .dfs0 (MIKE11 time series format) will be easily implemented by using the Temporal Analyst.

MIKE View on MIKE ZERO platform can be used for visualization of the simulation result of MIKE11 model. However, output files can also be imported to ArcGIS using MIKE BASIN Temporal Analyst, and then result presentation and analysis would be conducted in GIS environment. For example, linear reference system in ArcGIS may be utilized for the analysis and presentation on the result of the simulation in GIS environment.

As for Simple model, input data for the model are extracted from the GIS-DB. Some model parameters such as runoff volume are set using the result of MIKE11 model. Simple model is rather independent from GIS software so that user can use it without any knowledge of specific GIS software.

4.1.3 Modeling Cycle

There are three stages for the modeling, which consists of modeling cycle, as follows.

• Model development stage • Model usage stage • Model revision and refinement stage

The present study covers model development stage and a part of model usage stage. It is expected that Basin Directorate will continue model usage after the study. Model revision and refinement is proposed to be conducted after sufficient data and information will be accumulated in future. The best timing for model revision and refinement seems to be just before the river basin management plan will be revised.




Model Development

Model Revision & RefinementBy conducting re-calibration

Coverage by the Study

Model Usage

Accumulated (Good) monitoring data, permission data and so on

At least Every 6 years (proposal)

Model Development

Model Revision & RefinementBy conducting re-calibration

Coverage by the Study

Model Usage

Accumulated (Good) monitoring data, permission data and so on

At least Every 6 years (proposal)

Modeling Cycle

The following table summarizes the activities which the present study has conducted in the model development and usage stages and which the Study expects for RBDs to conduct in model revision and refinement stage after the study.

Activities in Each Modeling Stage

Stage MIKE11 Model Simple Model

Model development stage

-Calibration of parameters for rainfall-runoff module for MIKE11 model (2001 – 2005: 5 years) -Setting river-network for hydro dynamic module for MIKE11 model -Calibration of parameters for water quality module for MIKE11 model (2004: a representative year)

-Preparation of Excel sheets (incl. Macros) as templates

Model usage stage -To run the developed model by changing water use, pollution load based on scenarios

-Checking of water balance for different water use conditions -Examination on effect of pollution load reduction on water quality

Model revision and refinement stage

(After the study)

-Re-calibration of model parameters using accumulated data and information.

-Re-calibration of model parameters using accumulated data and information.

4.1.4 Target Users

Target users for Simple model and MIKE11 model are proposed as shown in the following table. There will be two kinds of users. One is the user who will run the model for different scenarios only. Another is the user who will maintain the model. Model run for MIKE11 model and model maintenance for both models require detailed knowledge on the model. It is thus recommended that Basin Directorate keep a few responsible persons for model maintenance, who will conduct model maintenance and model run for MIKE11 model, and model maintenance for Simple model.




Target Users

Responsible person for model maintenance in RBD

with discussion among Planning & Monitoring &

Permission Dept.



Permission Dept.

Model Maintenance



Permission Dept.

Planning & Monitoring & Permission Dept.Model Run

MIKE 11 ModelSimple ModelUser



Permission Dept.



Permission Dept.

Model Maintenance



Permission Dept.

Planning & Monitoring & Permission Dept.

Simple ModelUser MIKE 11 Model

Model Run

4.1.5 Modeling Layer

Modeling layer has been prepared as one of supporting layers beside core data model and WFD layer discussed in GIS-DB as shown in the following figure and Table. The modeling layer will be utilized for:

• Reference for preparing WFD layer, and • Base for preparing basin management plan.

Each object in the modeling layer has its ID for modeling purpose. To avoid confusion with WFD code for water bodies, it is totally different from the WFD code.

Core Data Model

WFD Layer

Modeling Layer

Core Data Model

WFD Layer

Modeling Layer

Modeling Layer

Prepared Modeling Layer Layer Explanation

Catchment Base unit for modeling, same as Core data, but has unique ID for modeling

NAM Catchment Base unit for Rainfall-Runoff modeling, which is prepared by aggregation of Catchment

MainRiverSegment Selected river segment corresponding to Catchment One Catchment has one MainRiverSegment basically.

SignificantLake Selected reservoir and lake for modeling purpose Significant reservoirs specified by Water Act and lakes whose surface area is more than 5km2 are selected.




4.2 Modeling Activities during the Study

Outline of modeling activities during the study is shown below.

Data Collection

Model Concept

Model Development for Water Quantity

Model Usage

Inception Report(June 2006)

Technical Seminar

(Jun 2007)

Interim Report(Jan 2007)

Draft Final Report(Jan 2008)

Technical Meeting

(Oct 2006)Training for Water Quantity Modeling

(Jun - Jul 2007)

Training for Water Quality Modeling

(Nov 2007)

Model Development for Water Quality

Phase I Phase II

Preliminary Analysis

Data Collection

Model Concept

Model Development for Water Quantity

Model Usage

Inception Report(June 2006)

Technical Seminar

(Jun 2007)

Interim Report(Jan 2007)

Draft Final Report(Jan 2008)

Technical Meeting

(Oct 2006)Training for Water Quantity Modeling

(Jun - Jul 2007)

Training for Water Quality Modeling

(Nov 2007)

Model Development for Water Quality

Phase I Phase II

Preliminary Analysis

In Phase I of the study, data collection and preliminary analysis on the data were done. Based on the preliminary analysis, modeling concept was developed and presented at technical meeting on October 2006.

After the seminar, selection of MIKE11 river network and setting of NAM catchment for each river basin was conducted. Firstly, the Study Team proposed the initial idea. The initial idea was modified by the discussion with C/P in EABD and WABD. Some rivers are added and some are excluded. Finally, the draft version of MIKE11 river network and NAM catchment was agreed between C/P in EABD, WABD and the Study Team.

In Phase II of the Study, data collection was continued because of delay of data collection in Phase I. Actual model development was also conducted. The developed model was used for scenario simulations for formulation of river basin management plan (draft).

Technical seminar was held on June 2007 to present progress of model development. Consequently, training for water quantity model, which is total 6 days with once a week, was conducted in June to July 2007. Training for water quality model, which is total 3 days with once a week, was also conducted in November 2007. There were totally about 10 participants from EABD and WABD but also MoEW, ExEA, DRBD and BSBD for trainings for both water quantity and quality modeling.




4.3 MIKE11 Model for Water Quantity

4.3.1 Outline of Model

MIKE11 model for water quantity consists of MIKE11-RR (Rainfall-Runoff module) and MIKE11-HD (Hydrodynamic module).

Several different rainfall-runoff models are prepared for MIKE11-RR. Among those, NAM model is selected in the present study. In the present study, snow routine for MIKE11-RR is considered, because snow-melting process in mountain region is one of key hydrological processes.

MIKE11-HD module is to simulate river flow process. One-dimensional version of governing equations for momentum transfer and continuity of fluid flow is basic equations for MIKE11-HD. In the present study, dynamic wave model is selected for solver option.

The outline of the model set-up is shown in the following table. Figures 4.3.1 – 4.3.5 show MIKE11 river network and rainfall-runoff (NAM) catchment for each river basin.

Outline of MIKE11 River Network and Rainfall-Runoff (NAM) Catchment

River Basin Total Modeling

Catchment Area (km2)

Number of Rainfall-Runoff

(NAM) Catchment

Total Length of Modeling River Network (km)

Number of Branch

Struma 8667.18 25 343.14 6 Mesta & Dospat

3397.71 14 141.80 3

Arda & Biala 5811.84 12 332.10 5 Tundzha 7890.93 20 409.46 5 Maritsa 21272.27 34 954.98 20

4.3.2 Input Data for Water Quantity Model

The following data were collected for modeling in the present study.

• Meteo-Hydrological Data • Precipitation • Potential evapo-transpiration (PET) • Air Temperature • Water quantity at key HMSs

• Water Transfer, Abstraction, Discharge Data

• Reservoir operation (for significant reservoir) • Water abstraction

• Irrigation water use • Domestic & Industrial water use

• Water discharge (waste water)

• River Condition Data • Cross-section data




4.3.3 Calibration

The rainfall-runoff (NAM) model has many model parameters to be calibrated. In the present study, the model parameters were calibrated using the water quantity during 2001-2005. During this period, there were both extremely dry and wet years. The calibration was conducted to reproduce reasonable hydrograph with such wide range of precipitation conditions. Therefore, it is expected that the calibrated model parameters can be valid against relatively wide range of precipitation condition.

When the calibration was conducted, it was set for duration of simulation to be from the beginning of August 2000 to the end of 2005 so as to avoid including significant influence of initial condition for the model parameters on the simulated results. Duration from the beginning of August 2000 to the end of 2000 was regarded as initial running period, which should not be used for further analysis.

The model parameters were basically calibrated against estimated quasi-natural runoff from the watershed that was determined by calibrated points and/or rainfall-runoff catchment. The quasi-natural runoff was estimated by using observed flow and estimated transferred water, abstracted water and discharged water within the watershed.

It should be noted that the effect of regime change by local reservoirs was not taken into account for estimating quasi-natural runoff in the present study, because of lack of the information.

The data used for the estimation of quasi-natural flow were sometimes monthly data. The monthly data were converted to daily data, assuming same fluctuation pattern as the reference daily data with keeping mass balance for monthly basis. The reference daily data were selected from the observed data, which were recorded at the HMS nearby same river.

During the calibration, the following priority was considered.

• 1st Priority: Total mass balance during 2001-2005 • 2nd Priority: Overall fitness during 2001- 2005 • 3rd Priority: Low flow condition

Water balance for quasi-natural condition by calibrated NAM model is shown in Table 4.3.1. It can be seen that runoff rate (RO/P) ranges 20 to 45%. The storage shown in the table is mainly because of large time scale of retention in lower ground water storage.

Hydrodynamic simulation, in which water transfer, abstraction and discharge are taken into account, was tested using the calibrated parameters for Rainfall-runoff (NAM) model. Figures 4.3.6 – 4.3.10 show comparison between observed (disturbed flow) and simulated hydrograph at a representative HMS for each river basin. It can be seen that the simulated results agree fairly with the observed ones.

4.3.4 Presentation and Analysis of Simulated Results

As an output of the study, an environment that users in river basin directorates can easily see and analyze the results of MIKE11 have been prepared. Simulated results by




MIKE11 water quantity model have been linked to ArcGIS platform using Temporal Analyst for ArcGIS. Figure 4.3.11 shows an example of presentation of results of MIKE11 model using Temporal Analyst. Many kinds of statistical analysis such as calculation of average, maximum and minimum value for the output of MIKE11 can be conducted and those results can be presented in ArcGIS platform.

The simulated results by MIKE11 water quantity model are utilized further for MIKE11 water quality analysis directly. Furthermore, the outputs of Rainfall-runoff model are utilized for Simple Model for water quantity.

4.4 MIKE11 Model for Water Quality

4.4.1 Introduction

A MIKE 11 Water Quality Model (MIKE 11 EcoLab) is set up for all the water bodies described by the MIKE 11HD Hydraulic Model for water quantity. The selected water quality module focuses on degradation of organic matter, transformation of N-components and the consequences for the oxygen concentrations. The selected model includes in addition phosphorus compounds.

The BOD, oxygen and N-transformation processes are outlined in Figure 4.4.1. The model includes both the transformation processes for the substances flowing in to the rivers as well as processes as photosynthesis and respiration of plants animals and sediment.

The Phosphorus Model used describes absorption-desorption sorption processes expanded with relevant processes related to plant, animal and sediment.

The WQ-module describes the following concentration (State Variables):

• BOD (Biological Oxygen Demand) • Diluted Oxygen (DO) • Total Ammonium (NH4-N) • Nitrate (NO3-N) • Phosphate (PO4-P) • Phosphor bound to particulate material (Particulate –P) • Temperature

4.4.2 Input Data for Water Quality Model

Data concerning the pollution load to the rivers in EABD and WABD has been collected with focus on quantification of the following groups of sources:

• Agricultural sources • From domestic live stock • From use of fertiliser

• Urban point sources • Out flow from WWTP (may include industrial wastewater) • Sewered but not treated sewage (may include industrial wastewater)




• Urban non-point sources

• Sewered small settlements • Non severed settlements and individual houses/farms

• Industries, point sources: • Direct discharge (including big animal breeding farms)

4.4.3 Calibration of Water Quality Models

The pollution load has been relative roughly quantified and there exist significant uncertainties on domestic, industrial, as well as agricultural load. Therefore the pollution is to be regarded as estimations of the levels. The year 2004 has been chosen as the hydraulic basis for the calibration. These in spite that the pollution loads to a higher extent represent the level in the period 2005-2007. The year 2004 has been selected as hydraulic basis, because this year has been characterized closed to an average year between those for which hydrological data was available. All together this mean that it can’t be expected to achieve very precise simulation of the monitored concentration and especially not the suddenly peaks and variation through the year. For these reason it has during the calibration process been aimed to achieve a representation of the measured level not only in 2004 but also that measured other resent years.

Examples of the calibration result for the variables BOD, Oxygen (DO), Ammonium (NH4-N) and Phosphate-P (PO4-P) at a representative station in each river basin are shown in Figures 4.4.2 – 4.4.6.

Generally the simulated concentration levels correspond to the measured ones except the most upstream reach of some rivers although some of the dynamic variation is not described too well. To achieve an improved simulation of the dynamic in the river system requires at least better estimations of the variation in pollution load. No such data have been available.

The results of the simulation for several different scenarios are shown in Chapter 6.




4.5 Simple Model

4.5.1 Water Quantity

(1) Basic Ideas of Model

The Simple model for water quantity is basically based on monthly mass balance calculation. The calculation is implemented on spread sheet such as Ms-Excel.

Unit of analysis in space for the simple model for water quantity is a catchment. The simple model analyzes water movement and balance among the catchments. To develop the simple model for water quantity, connectivity of the catchments is examined and an additional attribute for modelling catchment layer is recorded using GIS environment. The additional attribute for the catchment connectivity allows analyzing easily affected catchments by a source catchment.

“Matrix for contribution” can also be prepared based on the additional attribute table. Using this matrix, one can easily calculate the total accumulated value at an observation point from all of upstream catchments. In the present study, the matrix of contribution for each river basin has been prepared and stored in the Excel sheet as a part of the Simple Model.

In a catchment, the following sources are estimated.

• Catchment Area • Run-off from Catchment • Abstraction from Catchment • Discharge from Catchment • Transfer from Catchment

For example, the simple model of water quantity utilizes the results of calibrated rainfall-runoff (NAM) model. To estimate quasi-natural runoff from each catchment, the following is assumed.

• Runoff from each catchment inside a rainfall-runoff (NAM) catchment is proportional to: (Cacthment Area) x (Precipitation – Evapo-transpiration)

The other sources such as abstraction, discharge and transfer from a catchment are estimated by using same methodology for MIKE11 water quantity model.

When the sources from catchments are given, accumulated values without influence of significant reservoir such as quasi-natural flow and total abstracted water at an observation point are calculated using the matrix of contribution.

Influence of operation of significant reservoir is taken into account by introducing “matrix for reservoir influence”. At the catchments, which are affected by specific reservoir, modified water quantity by the operation of the reservoir is substituted by quasi-natural water quantity to get disturbed water quantity. All of the calculation is implemented in Excel sheet with Macros, which have been prepared in the present study.




(2) Versions of Simple Model for Water Quantity

The simple model for water quantity has the following four versions.

Versions for Simple Model for Water Quantity

Version Purpose

SimpleModel_ver_Existing -To estimate existing condition -Developed in the study (No need to change until RR model will be revised.)

SimpleModel_ver_Potential

-To estimate probable water quantity for quasi-natural and potential flows -Developed in the study (No need to change until RR model will be revised.)

SimpleModel_ver_Permit -To examine the effect of permitted water amount -Local + Existing water abstraction by Significant Reservoir -Local + Permitted water abstraction for Significant Reservoir

SimpleModel_ver_Demand -To estimate water demand with several scenarios

An example of the presentation of simple model_ver_Existing is shown in Figure 4.5.1. The user can specify any observation points to see the time series of water balance.

The results of ver_Exitsing and ver_Potential are basis for the draft basin management plan prepared by the present study. On the other hand, Basin Directorate itself has prepared Simple Model_ver_Permit and ver_Demand rather for Decision Support Tools for proper water management. Main features for each version are as follows:

• Ver_Permit • Entering permission data for hydropower, irrigation, drinking water

supply and industrial water supply.

• Selection of reference points for management

• Summary table for annual average and average during summer time (Jul. to Sep.) for year 2001 -2005 for each catchment/segment and reference point

• Longitudinal plot of the summarized results along main channel

• Time series plot for each reference point and/or catchment/segment

• Globally and locally changeable coefficient for permitted water amount

• Preparation of an input file related to local water abstraction for each NAM catchment for MIKE11 water quantity model

• Ver_Demand • Entering parameters for estimation of water demand for irrigation,

drinking water supply and industrial water supply

• Selection of reference points for management




• Summary table for annual average and average during summer time (Jul. to Sep.) for each catchment/segment and reference point

• Longitudinal plot of the summarized results along main channel

• Time series plot for each reference point and/or catchment/segment

• Preparation of an input file related to local water abstraction for each NAM catchment for MIKE11 water quantity model

4.5.2 Water Quality

In order to facilitate the formulation of water quality management plan and for future use for water quality management, simple model for water quality was developed in the Study.

(1) Basic Concept of the Simple Model for Water Quality (WQL Simple Model)

• The WQL Simple Model will simulate the effect of reducing pollution loads to the river water quality in terms of BOD5.

• The simulation will be done at key calculation points along the rivers.

• The calculation will be done by MS-Excel.

• The model can be utilized for quick review of the conditions of BOD loads in the river basins comparing the future required BOD loads to attain good status of water (such as Class II with BOD5 3.0 mg/l).

(2) Procedure of Developing the WQL Simple Model

Figure 4.5.2 shows the procedure for developing the WQL Simple Model.

• First to check the general co-relation between the present accumulated catchment BOD loads from the upstream of the calculation points and the river BOD loads at the calculation points. If there is junction of tributary, the calculation points are set at the upstream side of the main stream. If there is no tributary, the calculation point is just on the main stream at that point. Figure 4.5.3 shows the calculation points for EABD and WABD with NAM catchments. There is clear co-relation between the accumulated catchment BOD loads and the river BOD loads as shown in the “Main Report 6.2 Water Quality Management Plan”.

• The existing sewer networks in EABD and WABD have significant loss of pollutants such as at least 50% loss for the Maritsa and Tundzha River Basin, 40% in the Arda River Basin, and 60% in the Struma and Mesta River Basin. The current loss percentage to the domestic BOD load and industrial BOD load discharged into the sewerage system is applied for calculating their inflow BOD loads to the river. This assumption is more or less acceptable because the domestic loads without sewerage system are calculated with smaller unit loads (15 g/day/PE) compared to the generated unit load of 60 g/day/PE, and it may reach to the river through ditch or gulley.

• Ratios between the inflows BOD loads and river BOD loads are calculated at every calculation point.




• Under the assumed condition of reducing the loss from the sewer networks up to 10% in the long time future, inflow BOD loads based on the Near Future BOD load including under constructed WWTPs or committed for constructing WWTPs in EABD and WABD are calculated. Corresponding to this, River BOD load and the BOD concentration in the near future condition with loss of sewerage with 10% are calculated.

• In order to attain the good status of water, which is better than Class II with BOD5 of 3.0 mg/l, required inflow BOD load and corresponding accumulated catchment BOD load is calculated.

• Setting the pollution reduction plan such as construction of WWTPs in the future, future accumulated catchment BOD load is calculated, and compared with the required accumulated catchment BOD load.

(3) Results of the Calculation

Based on the procedure described above, the following figures show the results of the calculations by the WQL Simple Model.

Figure Contents

Figure 4.5.4 Present Accumulated Catchment BOD Loads and River BOD Loads in EABD

Figure 4.5.5 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High Priority Towns for WWTPs

Figure 4.5.6 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High and Medium Priority Towns for WWTPs

Figure 4.5.7 Present Accumulated Catchment BOD Loads and River BOD Loads in WABD

Figure 4.5.8 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High Priority Towns for WWTPs

Figure 4.5.9 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High and Medium Priority Towns for WWTPs

Effects of reduction of BOD loads in EABD by the high priority towns for WWTPs as well as the high and medium priority towns for WWTPs are rather good along the Maritsa and Tundzha Main Rivers in general. However, for the upstream to mid-stream part of the Tundzha River, reduction rate is slightly lower than the downstream. This reaches of the Tundzha River might have more influence from the medium and smaller settlements. Therefore, in the future, it will be necessary for reduction of pollution loads in this part from medium to smaller settlements as well.

Overall effects for reducing BOD Loads by the high priority towns for WWTPs as well as the high and medium priority towns for the Struma and Mesta Rivers are generally good. However, for the Struma River, reduction rate of the pollution loads is insufficient especially from upstream to mid-stream part. Therefore in the future, it may be necessary to treat medium and smaller settlements in the upstream to the mid-stream parts as well.




CHAPTER 4

4.1

Main Report

Chapter 4

Tables

4.2




Table 4.2.1 Water Balance for Quasi-Natural Condition during 2001-2005 by Calibrated NAM Model

Source: JICA Study Team

Struma Mesta Dospat Arda Biala Tundzha Maritsa

Catchment Area (km2) 8541 2785 613 5213 599 7891 21272

Average Elevation (m) 919 1225 1330 639 418 386 569

Precipitation (P) (mm/y) 761 844 875 902 833 710 723

PET (mm/y) 629 577 552 671 717 689 669

ET (mm/y) 483 442 490 511 567 513 488

Total Runoff (RO) (mm/y) 231 349 321 371 232 158 173

Lower Base Flow (LBF) 28 56 81 14 12 27 41

OverlandFlow (OF) (mm/y) 25 26 30 165 99 26 31

Storage (ST) (mm/y) 48 53 64 20 35 39 62

ET/P (%) 63.5 52.4 56.0 56.7 68.1 72.3 67.5

RO/P (%) 30.4 41.4 36.7 41.1 27.9 22.3 23.9

LBF/P (%) 3.7 6.6 9.3 1.6 1.4 3.8 5.7

OF/P (%) 3.3 3.1 3.4 18.3 11.9 3.7 4.3

ST/P (%) 6.3 6.3 7.3 2.2 4.2 5.5 8.6

ET/PET (%) 76.8 76.6 88.8 76.2 79.1 74.5 72.9

Total Runoff (m3/s) 62.6 30.8 6.2 61.3 4.4 39.5 116.7

Specific Total Runoff (l/s/km2) 7.325 11.067 10.179 11.764 7.357 5.010 5.486

Remarks

1) Catchmentarea is only formodelled areain Bulgarianteritory.2) Twocatchments aredisturbedcondtion.3) Precipitationis modifiedconsideringelevation in themodel.

1) Catchmentarea is only formodelled area.2) Precipitationis modifiedconsideringelevation in themodel.









CHAPTER 4

4.1

Main Report

Chapter 4

Figures




Figure 4.1.1 Work Contents and Data in the Study


Figure 4.1.2 Relationship between Simple Model and MIKE11 Model

Rainfall Runoff Simulation(MIKE11-RR）

Runoffq(m3/s/km2)

Month

Input

Precipitation

Outflow from Dam

Input

Pollution Load from Industry

Input

Pollution Load from Livestock farm

Irrigation Area

Irrigation AreaIntake

Input

Input

Pollution Load from Town

Input

Sophisticated Model ( MIKE11)

- Simulation of longitudinal variation of discharge, -water level and water quality along rivers- Continuous simulation for time series

Discharge Q(m3/s)

1 2 11 12Month

BOD, COD etc.(mg/l)

1 2 11 12Month

Output

Simple Model

- Simulation at key stations only- Simulation for monthly averaged values

OutputMonthly. Ave. (m3/s)

1 2 11 12Month

Monthly. Ave. BOD, COD etc.(mg/l)

1 2 11 12Month

Rainfall Runoff Simulation(MIKE11-RR）

Runoffq(m3/s/km2)

Month

Runoffq(m3/s/km2)

Month

Input

Precipitation

Outflow from Dam

Input

Pollution Load from Industry

Input

Pollution Load from Livestock farm

Irrigation Area

Irrigation AreaIntake

Input

Input

Pollution Load from Town

Input



Discharge Q(m3/s)

1 2 11 12Month

BOD, COD etc.(mg/l)

1 2 11 12Month

Output



Discharge Q(m3/s)

1 2 11 12Month

BOD, COD etc.(mg/l)

1 2 11 12Month

OutputDischarge Q(m3/s)

1 2 11 12Month

BOD, COD etc.(mg/l)

1 2 11 12Month

BOD, COD etc.(mg/l)

1 2 11 12Month

Output

Simple Model



1 2 11 12Month


1 2 11 12Month

Simple Model



1 2 11 12Month

Monthly. Ave. (m3/s)

1 2 11 12Month


1 2 11 12Month


1 2 11 12Month

Level 1Core Data 1. Topography, Geology, River & River Basin Boundary, Hydro-geology,

2. Administration Boundary/Towns/Villages, Population, Landuse, Economy, and3. Natural and Social Environment including Protected Areas

Level 3 Monitoring Data

1. Meteorology (Temperature, Relative Humidity and Precipitation)2. Hydrology (Surface Water Level and Discharge)3. Surface Water Quality and Hydro-biology4. Groundwater (Level and Quality)5. Water Abstraction and Control (Intake and Reservoir) including Permission6. Pollution Source and Wastewater Discharge (Quantity and Quality) including Permission

Level 4Basic Analysis Data

at Points

1. Time Series Data at Points: Meteo-hydrology, Surface Water Quantity and Quality, Groundwater Quantity and Quality, Intake Water Volume, and Reservoir Operation.2. Annual Condition at Points Hydro-biology Wastewater Discharge and Pollution Load

1. Surface Water Quantity Management and Improvement Plan2. Surface Water Quality Management and Improvement Plan3. Groundwater Quantity and Quality Management and Improvement Plan4. Monitoring Plan for Surface Water, Groundwater, Water Use and Wastewater Discharge

Level 5Spatial Distribution

Analysis Data

1. Water Balance Distribution by Sub-Basin and in the River Networks2. Pollution Load Distribution by Sub-Basin3. Water Quality Distribution in the River Networks4. Hydro-biological Index Distribution in the River Networks5. Groundwater Quantity and Quality Distribution by Sub-Basin6. Distribution of Risk (Surface Water and Groundwater)

Level 6Water Management

Plan Data

Wat

er Q

uant

ity a

nd Q

ualit

y M

odel

(Sim

ple

Mod

el a

nd M

IKE1

1 M

odel

)

Level 2Water Bodies Data

1. Surface Water Bodies2. Groundwater Bodies




MIKE11(MIKE Zero platform)

Simple Model (Spread sheet)

GIS-DB

MIKE BASINTemporal Analyst &

Pollution load calculator(ArcGIS extension:

part of MIKE11 GIS after ver2007)

- Extract base layer- Connection to DB

- Preparation of input file for simulation

Connection of output file to GIS environment

Extract from DB

FinalAssembling

Parameters(Quasi-Natural Run-off etc.)

Ms-Excel

MIKE11 & MIKE BASIN

- Water Body- Natural & Socio-economical information- Monitoring Data for Water Quantity and Quality - Permission Data- Operation record for reservoir and irrigation

Boundary Condition MIKE11

(MIKE Zero platform)

Simple Model (Spread sheet)

GIS-DB

MIKE BASINTemporal Analyst &

Pollution load calculator(ArcGIS extension:

part of MIKE11 GIS after ver2007)

- Extract base layer- Connection to DB

- Preparation of input file for simulation

Connection of output file to GIS environment

Extract from DB

FinalAssembling

Parameters(Quasi-Natural Run-off etc.)

Ms-Excel

MIKE11 & MIKE BASIN

- Water Body- Natural & Socio-economical information- Monitoring Data for Water Quantity and Quality - Permission Data- Operation record for reservoir and irrigation

Boundary Condition


Figure 4.1.3 Structure of Modeling Environment

4.2

4.3

ST_ARK

ST_BRA

ST_DRA

ST_DZH1

ST_DZH2

ST_ELE

ST_GRA

ST_KON

ST_M1

ST_M10

ST_M2

ST_M3

ST_M4

ST_M5

ST_M6

ST_M7

ST_M8

ST_M9

ST_PIR

ST_RIL

ST_SAN

ST_SOV

ST_STR1

ST_STR2

ST_TRE

RiverNetWorkMIKE11MainRiverSegment

SignificantLakeCatchment

NAM Catchment


Figure 4.3.1 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Struma River Basin




DO_M1

DO_M2ME_GLA

ME_IST1

ME_IST2

ME_KAN

ME_M1

ME_M2

ME_M3

ME_M4

ME_M5

ME_M6

ME_NEV

ME_ZLA



NAM Catchment


Figure 4.3.2 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Mesta and Dospat River Basins

AR_CHE

AR_KRU1

AR_KRU2

AR_M1

AR_M2

AR_M4

AR_M5AR_VAR1

AR_VAR2

BI_M

AR_M3

AR_M0



NAM Catchment


Figure 4.3.3 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Arda and Biala River Basins




TU_ARA

TU_ASE1

TU_BEL

TU_KAL

TU_M1

TU_M2

TU_M3TU_M4TU_M6TU_M7

TU_M9

TU_MOC1

TU_MOC2

TU_POP1

TU_ASE2

TU_M8

TU_POP2

TU_M5

TU_SIN



NAM Catchment


Figure 4.3.4 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Tundzha River Basin

MA_BLA

MA_CPI1

MA_CPI2 MA_CPL1

MA_CPL2MA_HAR1MA_HAR2

MA_LUD1

MA_LUD2

MA_M1

MA_M2

MA_M3

MA_M4MA_M5

MA_M6

MA_M7

MA_PYA1

MA_PYA2

MA_RBA

MA_RDO

MA_ROV

MA_SAZ1

MA_SAZ2

MA_STA1

MA_STA2

MA_STR1

MA_STR2

MA_TOP1

MA_TOP2

MA_TOP3

MA_TOP4

MA_VAC1

MA_VAC2

MA_YUG



NAM Catchment


Figure 4.3.5 MIKE11 River Network and Rainfall-Runoff (NAM) Catchment in the Maritsa River Basin




51880Discharge, ST_M 0.000-12713.450 4

2000 2001 2002 2003 2004 2005

Time

0

100

200

300

400

500

600

Wat

er Q

uant

ity (m

3/s)


Figure 4.3.6 Comparison between Observed and Simulated Hydrograph (The Struma River: HMS51880)

61550Discharge, AR_KRU 21091.111328125

2000 2001 2002 2003 2004 2005

Time

0

50

100

150

200

250

300

Wat

er Q

uant

ity (m

3/s)


Figure 4.3.7 Comparison between Observed and Simulated Hydrograph (The Mesta River: HMS52850)




61550Discharge, AR_KRU 21091.111328125

2000 2001 2002 2003 2004 2005

Time

0

50

100

150

200

250

300

Wat

er Q

uant

ity (m

3/s)


Figure 4.3.8 Comparison between Observed and Simulated Hydrograph (The Arda River: HMS61550)

74850Discharge, TU_M 53379.5703125

2000 2001 2002 2003 2004 2005

Time

0

50

100

150

Wat

er Q

uant

ity (m

3/s)


Figure 4.3.9 Comparison between Observed and Simulated Hydrograph (The Tundzha River: HMS74850)




73750Discharge, MA_M 50444.6015625

2000 2001 2002 2003 2004 2005

Time

0

200

400

600

800

1000

1200

Wat

er Q

uant

ity (m

3/s)


Figure 4.3.10 Comparison between Observed and Simulated Hydrograph (The Maritsa River: HMS73750)


Figure 4.3.11 Example of Presentation of Results of MIKE11 Model Using Temporal Analyst




4.4

Figure 4.4.1 Basic processes with respect to BOD, N-component and oxygen (DO) included in the MIKE 11 WQ Model used under this study

Respirationnitrification

BODOrg. Matter

BODdegradation

Photosynthesis

Pollution sourcesBOD NH4 ( NO3)

Reaeration

(NO3)

(N2)

-DO

-DO

+DO

Sunlight

Sediment respiration

-DOnitrification

+DO

-DO

RespirationnitrificationRespirationnitrification

BODOrg. Matter

BODdegradation

PhotosynthesisPhotosynthesis

Pollution sourcesBOD N ( NO3)

Reaeration

(NO3)

(N2)

-DO

-DO

+DO

Sunlight

Sediment respiration

-DOnitrification

+DO

-DO

NH4




Figure 4.4.2 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) Concentration at Station 464, Struma River

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

ST_M

840

6.41

BO

D

Exte

rnal

TS

146

4_BO

D

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

7.0

8.0

9.0

10.0

11.0

12.0

13[m

.0g/l]

Tim

e S

erie

s C

once

ntra

tion

Con

cent

ratio

nS

T_M

840

6.41

DIS

SO

LVED

OX

YG

EN

Exte

rnal

TS

146

4_D

O

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

ST_M

840

6.41

AM

MO

NIA

Exte

rnal

TS

146

4_NH

4

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

ST_

M 8

406.

41 O

RTH

OPH

OS

PHA

TE

Exte

rnal

TS

146

4_PO

4

Figu

re 4

.4.2

Sim

ulat

ed a

nd M

onito

red

BO

D, O

xyge

n (D

O) ,

Am

mon

ia (N

H4-

N) ,

Pho

spha

te (P

O4-

P) C

once

ntra

tion

at

Stat

ion

464,

The

Str

uma

Riv

er

BO

D

Oxy

gen

(DO

)

Am

mon

ia (N

H4-

N)

Phos

phat

e (P

O4-

P)




Figu

re 4

.4.3

Sim

ulat

ed a

nd M

onito

red

BO

D, O

xyge

n (D

O) ,

Am

mon

ia (N

H4-

N) ,

Pho

spha

te (P

O4-

P) C

once

ntra

tion

at

Stat

ion

432

Figure 4.4.3 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 432, Mesta River

, The

Mes

ta R

iver

BO

D

Oxy

gen

(DO

)

Am

mon

ia (N

H4-

N)

Phos

phat

e (P

O4-

P)

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

2.0

4.0

6.0

8.0

10.0

120.

14.0[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

ME_

M 2

1250

.00

BOD

Exte

rnal

TS

143

2_BO

D

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

][m

g/l

Tim

e S

erie

s C

once

ntra

tion

Con

cent

ratio

nM

E_M

212

50.0

0 D

ISS

OLV

ED O

XY

GEN

Exte

rnal

TS

143

2_D

O

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

ME_

M 2

1250

.00

AM

MO

NIA

Exte

rnal

TS

143

2_NH

4

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

ME_

M 2

1250

.00

OR

THO

PHO

SPH

ATE

Exte

rnal

TS

143

2_PO

4




Figu

re 4

.4.4

Sim

ulat

ed a

nd M

onito

red

BO

D, O

xyge

n (D

O) ,

Am

mon

ia (N

H4-

N) ,

Pho

spha

te (P

O4-

P) C

once

ntra

tion

at

Stat

ion

412

Figure 4.4.4 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 412, Arda River

, The

Ard

a R

iver

BO

D

Oxy

gen

(DO

)

Am

mon

ia (N

H4-

N)

Phos

phat

e (P

O4-

P)

1-7-

2000

17-1

-200

15-

8-20

0121

-2-2

002

9-9-

2002

28-3

-200

314

-10-

2003

1-5-

2004

17-1

1-20

045-

6-20

05

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

14.0

15.0

16.0

17.0

18.0

[MG

/L]

Tim

e Se

ries

TOTA

L BO

DTO

TAL

BOD

AR_

M 1

3198

.56

Exte

rnal

TS

141

2_BO

D

1-7-

2000

17-1

-200

15-

8-20

0121

-2-2

002

9-9-

2002

28-3

-200

314

-10-

2003

1-5-

2004

17-1

1-20

045-

6-20

05

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

AR

_M 1

3198

.56

DIS

SO

LVED

OX

YG

EN

Exte

rnal

TS

141

2_D

O

1-7-

2000

17-1

-200

15-

8-20

0121

-2-2

002

9-9-

2002

28-3

-200

314

-10-

2003

1-5-

2004

17-1

1-20

045-

6-20

05

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

AR_

M 1

3198

.56

AM

MO

NIA

Exte

rnal

TS

141

2_N

H4

1-7-

2000

17-1

-200

15-

8-20

0121

-2-2

002

9-9-

2002

28-3

-200

314

-10-

2003

1-5-

2004

17-1

1-20

045-

6-20

05

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

AR

_M 1

3198

.56

OR

THO

PHO

SPH

ATE

Exte

rnal

TS

141

2_PO

4




Figure 4.4.5 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 309, Tundzha River

Figu

re 4

.4.5

Sim

ulat

ed a

nd M

onito

red

BO

D, O

xyge

n (D

O) ,

Am

mon

ia (N

H4-

N) ,

Pho

spha

te (P

O4-

P) C

once

ntra

tion

at

Stat

ion

309 ,

The

Tun

dzha

Riv

er

BO

D

Oxy

gen

(DO

)

Am

mon

ia (N

H4-

N)

Phos

phat

e (P

O4-

P)

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

13.0

14.0

15.0

16.0

17.0

18.0

[MG

/L]

Tim

e Se

ries

TOTA

L BO

DTO

TAL

BOD

TU_M

310

04.3

4

Exte

rnal

TS

130

9_BO

D

7-3-

2003

15-6

-200

323

-9-2

003

1-1-

2004

10-4

-200

419

-7-2

004

27-1

0-20

044-

2-20

0515

-5-2

005

23-8

-200

5

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12.0

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

TU_M

310

04.3

4 D

ISS

OLV

ED O

XY

GEN

Exte

rnal

TS

130

9_D

O

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

[mg/

l]Ti

me

Serie

s C

once

ntra

tion

Conc

entra

tion

TU_M

310

04.3

4 A

MM

ONI

A

Exte

rnal

TS

130

9_NH

4

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

50.

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

TU_M

310

04.3

4 O

RTH

OPH

OSP

HATE

Exte

rnal

TS

130

9_PO

4




Figure 4.4.6 Simulated and Monitored BOD, Oxygen (DO) , Ammonia (NH4-N) , Phosphate (PO4-P) Concentration at Station 387, Maritsa River

Figu

re 4

.4.6

Sim

ulat

ed a

nd M

onito

red

BO

D, O

xyge

n (D

O) ,

Am

mon

ia (N

H4-

N) ,

Pho

spha

te (P

O4-

P) C

once

ntra

tion

at

Stat

ion

387,

The

Mar

itsa

Riv

er

BO

D

Oxy

gen

(DO

)

Am

mon

ia (N

H4-

N)

Phos

phat

e (P

O4-

P)

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

180g/

l]

.[mTi

me

Serie

s C

once

ntra

tion

Conc

entra

tion

MA

_M 3

640.

44 B

OD

Exte

rnal

TS

138

7_BO

D

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

4.0

5.0

6.0

7.0

8.0

9.0

10.0

11.0

12[m

.0g/l]

Tim

e S

erie

s C

once

ntra

tion

Con

cent

ratio

nM

A_M

364

0.44

DIS

SO

LVED

OX

YG

EN

Exte

rnal

TS

138

7_D

O

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nCo

ncen

tratio

nM

A_M

364

0.44

AM

MO

NIA

Exte

rnal

TS

138

7_NH

4

2-3-

2000

18-9

-200

06-

4-20

0123

-10-

2001

11-5

-200

227

-11-

2002

15-6

-200

31-

1-20

0419

-7-2

004

4-2-

2005

23-8

-200

50.

0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

[mg/

l]T

ime

Ser

ies

Con

cent

ratio

nC

once

ntra

tion

MA

_M 4

9472

.20

OR

THO

PHO

SPH

ATE

Exte

rnal

TS

138

5_PO

4




4.5


Point1: Re ointfP2: Segment

No. ofRefPoint

(for 1)

CatchmentJICA_ID(For 2)

2 ST4 538

Re-plot TimeSeries

0.00

50.00

100.00

150.00

200.00

250.00

Jan

2001

Apr

200

1

Jul 2

001

Oct

200

1

Jan

2002

Apr

200

2

Jul 2

002

Oct

200

2

Jan

2003

Apr

200

3

Jul 2

003

Oct

200

3

Jan

2004

Apr

200

4

Jul 2

004

Oct

200

4

Jan

2005

Apr

200

5

Jul 2

005

Oct

200

5

Time

Dis

char

ge (m

3/s)

Quasi-Natural FlowPotential Flow with Significant ReservoirTotal Abstracted WaterDisturbed Flow

Figure 4.5.1 Example of Presentation of Simple Model_ver_Existing

Average in 2001-2005

0.00

20.00

40.00

60.00

80.00

100.00

120.00

Jan

Feb Mar AprMay Ju

n Jul

Aug Sep OctNov Dec

Time

Dis

char

ge (m

3/s)

Quasi-Natural Flow Potential Flow

Total Abstracted Water Disturbed Flow

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Jan

2001

Apr

2001

Jul 2

001

Oct

2001

Jan

2002

Apr

2002

Jul 2

002

Oct

2002

Jan

2003

Apr

2003

Jul 2

003

Oct

2003

Jan

2004

Apr

2004

Jul 2

004

Oct

2004

Jan

2005

Apr

2005

Jul 2

005

Oct

2005

Time

Dis

char

ge (m

3/s)

Total Abstracted Water Abstracted Water for IRR Abstracted Water for DWS Abstracted Water for IWS

Average in 2001-2005

0.000.501.001.502.002.503.003.504.004.505.00

Jan

Feb Mar AprMay Ju

n Jul

Aug Sep OctNov Dec

Time

Dis

char

ge (m

3/s)

Total Abstracted Water Abstracted Water for IRR

Abstracted Water for DWS Abstracted Water for IWS



1. Present Catchment BOD Load by NAM Catchment 1) Domestic load and industrial load

discharged into sewerage system 2) Livestock load 3) Industrial load directly discharged

into rivers and water bodies

4. Present River BOD Load at the Calculation Points

2. Present Accumulated Catchment BOD Load and Inflow BOD Load Upstream from the Calculation

3. Present BOD5 Concentration and Discharge in the River BOD5 of normal maximum values Average discharge quantity in the river during summer season

8. Required Accumulated Catchment BOD Loads BOD5 in the river to be better than Class II (3.0 mg/l). Required river BOD Load with BOD5 of 3.0 mg/l. Required accumulated catchment BOD load with 10 % loss from sewer networks.

NAM Catchment 2

NAM Catchment 1 Discharge : Q BOD concentration: C

River

Calculation point

Accumulated Catchment BOD Load

Inflow BOD Load

River BOD Load

5. Co-relation of the Present Accumulated Catchment and Inflow BOD Loads and River BOD Load 1) General co-relation from upstream to downstream for accumulated catchment BOD load and river BOD load. 2) Ratios at each calculation point between inflow BOD load including current pollutant loss from sewer networks to the river BOD load.

6. Near Future Catchment BOD Load and Inflow BOD Load with 10 % Loss from Sewer Networks

7. Near Future River BOD Load and BOD Concentration with 10% Loss from Sewer Networks

Figure 4.5.2 Procedure of Developing the Simple Model for Water Quality





Figu

re 4

.5.3

Cal

cula

tion

Poin

ts fo

r E

AB

D a

nd W

AB

D w

ith N

AM

Cat

chm

ents

Figure 4.5.3 Calculation Points for EABD and WABD with NAM Catchments




Figure 4.5.4 Present Accumulated Catchment BOD Loads and River BOD Loads in EABD

Figu

re. 4

.5.4

Pre

sent

Acc

umul

ated

Cat

chm

ent B

OD

Loa

ds a

nd R

iver

BO

D L

oads

in E

AB

D




Figure 4.5.5 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High Priority Towns for WWTPs

Figu

re. 4

.5.5

Req

uire

d A

ccum

ulat

ed C

atch

men

t BO

D L

oads

and

Riv

er B

OD

Loa

ds in

E

AB

D w

ith H

igh

Prio

rity

Tow

ns fo

r WW

TPs




Figure 4.5.6 Required Accumulated Catchment BOD Loads and River BOD Loads in EABD with High and Medium Priority Towns for WWTPs

Fig.

4.5

.6 R

equi

red

Acc

umul

ated

Cat

chm

ent B

OD

Loa

ds a

nd R

iver

BO

D L

oads

in

EA

BD

with

Hig

h an

d M

ediu

m P

rior

ity T

owns

for W

WT

Ps




Figure 4.5.7 Present Accumulated Catchment BOD Loads and River BOD Loads in WABD

Fig.

4.5

.7 P

rese

nt A

ccum

ulat

ed C

atch

men

t BO

D L

oads

and

Riv

er B

OD

Loa

ds in

WA

BD




Figure 4.5.8 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High Priority Towns for WWTPs

Fig.

4.5

.8 R

equi

red

Acc

umul

ated

Cat

chm

ent B

OD

Loa

ds a

nd R

iver

BO

D L

oads

in W

AB

D

with

Hig

h Pr

iori

ty T

owns

for W

WT

Ps




Figure 4.5.9 Required Accumulated Catchment BOD Loads and River BOD Loads in WABD with High and Medium Priority Towns for WWTPs

Fig.

4.5

.9 R

equi

red

Acc

umul

ated

Cat

chm

ent B

OD

Loa

ds a

nd R

iver

BO

D L

oads

in

WA

BD

with

Hig

h an

d M

ediu

m P

rior

ity T

owns

for W

WT

Ps




CHAPTER 5 SOCIO-ECONOMIC FRAMEWORK

5.1 Population

Population in Bulgaria is on the decrease from the year 1985 as a peak. Nevertheless the population in Bulgaria shows a falling trend as a whole, that in some municipalities are increased during past several years as the Capital City, Sofia. Generally speaking, decrease of population is caused by hemorrhage of labor force of young generation as 20s or 30s of ages. But, on the other hand, increase in population in some cities and/or municipalities means to show a trend of concentration of the population in urban areas.

The population of the largest municipality of Plovdiv in the East Aegean River Basin has increased from 340,122 in 2001 to 341,873 in 2005 even showing some fluctuation depending on the year. And, the population itself of the Municipality of Blagoevgrad in the West Aegean River Basin is less than that in 2001, but it has slightly increased from 77,346 in 2003 to 77,462 in 2005.

Based on the above trend, the population of both the Municipalities of Plovdiv and Blagoevgrad may be increased to the year 2015, and that of the other municipalities in the West and the East Aegean River Basins may remain on the same level as it is. As shown in Figure 5.1.1, in the Plovdiv, 3 cases are assumed as (1) the most optimistic case of population increase with 0.23% to the year 2015 based on the same trend of past 3 years, (2) medium case with 0.18% based on 50% of past 3 years increase, and (3) the most pessimistic case with 0.12% based on 25% of past 3 years increase.

On the other hand, the municipality of Blagoevgrad is the largest municipality in the West Aegean River Basin, but a scale of the municipality is far small comparing with Plovdiv. Therefore, increasing rate of the population is also small. Accordingly, 3 cases are assumed as (1) the most optimistic case of population increase with 0.05% to the year 2015, (2) medium case with 0.03%, and (3) the most pessimistic case with 0.01%. Figure 5.1.2 shows a summary of population projection to the year of 2015.

5.2 Economic Growth

The clearest factor to express the economic growth is GDP. The following table shows a summary of GDP trend during past several years.

Trend of GDP and Per Capita Production for the Past Several Years

(At current price) Description 2001 2002 2003 2004 Annual Average

Increasing Rate GDP (million Levs) GDP per Capita (Levs/capita)

29,709 3,754

32,335 4,109

34,547 4,416

38,275 4,919

8.82% 9.44%

Source: NSI.

GDP has increased by 8.8% annually in average, and GDP per Capita has also increased by 9.4% annually in average, so these trend seems to be quite firm. However, in case taking price increase into account, the situation cannot be taken lightly.




The following table shows a summary of GDP revised by the Consumer Price Index (CPI).

GDP and Per Capita Production Revised by CPI

GDP Annual increasing rate 8.84% 6.84% 10.79%CPI 3.81% 5.64% 3.98%Actual annual increasing rate 5.02% 1.20% 6.82%

GDP/capitaAnnual increasing rate 9.46% 7.47% 11.39%CPI 3.81% 5.64% 3.98%Actual annual increasing rate 5.64% 1.83% 7.41%

4.35%

4.96%

8.82%4.48%

9.44%4.48%

2004

AnnualAverage

IncreasingRate

Description 2002 2003

Both the actual GDP and the actual GDP Per Capita have been fluctuated around middle to upper end of 4%. Accordingly, it may be appropriate that GDP will be increased around 5% for the future too.

5.3 Transition of Industrial Structure and Tasks of Agricultural Sector

Industrial structure for the past several years can be expressed by the share rate of production (gross value added) (see Table 5.3.1). Production of the agricultural sector (Agriculture/ Hunting/Forestry) has around remained on the same level until 2004, but has fallen in 2005 in the share rate to GDP. On the other hand, that in the manufacturing sector has increased constantly in production. The sector of Electricity/Gas/Water Supply has fallen in production in 2005, but the production has increased steadily even increasing rate is no so much great. The production of the sectors of (1) Trade/Repair of Motor Vehicles/ Personal-Household Goods, (2) Hotels/Restaurants, (3) Transport/Storage/Communi- cations, (4) Financial Intermediation, (5) Real Estate/Renting, (6) Public Administration/ Compulsory Social Security, (7) Education, (8) Health/Social Work is also increased steadily during past several years. Table 5.3.2 shows a summary of share rates of production by economic activities to GDP.

Generally speaking, Bulgaria is a national commitment of agriculture. However, according to the above, the share rate of agricultural production to GDP is less than 10%, and it has been fallen annually. In the year 2005, it has fallen to less than 8%. It may be that to ensure the agricultural production is the most urgent task for the nation. For realizing it, development of incentives of farmers may be the most important factor. For this purpose, as well as governmental policy for increasing the agricultural production, to stabilize and accessibility of farmers to agricultural market is required to ensure.

5.4 Irrigation

According to the Agricultural Statistics, a share rate of irrigated agricultural area to total arable area is only 4% as of 2005.

And, in so called potential irrigable areas (potential irrigation areas) where have formerly been laid down irrigation facilities as canals, the share rate of actual irrigated areas are, nevertheless discrepancies exist depending upon districts, and/or differs by year, less than 10% in overall average in the whole nation.




Share rates of actual irrigated area to the total potential area in each irrigation branch are ranging from 1.29% to 19.22%, and 7.43% in overall average (see Table 5.4.1).

Each irrigation branch consists of several irrigation systems. According to this detail of irrigation systems, the share rate of the West Aegean River Basin is only 4.76% and that of the East Aegean river Basin is 7.17% in average.

Data indicated in Table 5.4.1 comes only from Irrigation Systems PLC. Actually, there exist some the other irrigation water supply companies as Hydro Melioration-Sevlievo PLC, Zeminvest PLC as quasi-largest companies as well as small-scale irrigation water supply companies located over the nation reached from 50 to 60 firms. The Irrigation Systems PLC supplies the said 2 quasi-largest companies cover only 2% of supplied water volume, and remaining 98% of irrigation water. Supplied water volume by the smallest companies is not clear, but anyway, it may say that the data above indicates overall status of actual irrigated areas of the nation.

Through the Study, it has been made clear that the reason of low actuality ratings to the potential area caused by mal-function of irrigation facilities because of its deterioration and of lack of suitable operation and maintenance. As discussed in previous sub-clause, to develop the agricultural productivity is the urgent task in the nation. However, there will be a lot of matters to be solved as financing matters, farming skills of farmers and accessibility to the market, so that to prompt realization of improvement of the agricultural production will face to a lot of difficulties.

Based on the Study, it is assumed that the irrigation areas will be expanded by 20% of the potential area in each river basin in average and this rate may be ceiling rate of irrigation improvement until the target year 2015.

5.5 Living Standard and Water Consumption

Average income level per household in Bulgaria, the level in 2001 has fallen from that in 2000, but after that the income level has been increased by 7.66% annually, and it seems that the income per household has constantly been increased, as shown in Chapter 2.3.

Among them, the income level can be illustrated as shown in Figure 5.5.1. In a simple average, the income level has been increased by 7.66% as discussed above. But the increasing rate has been decreased year by year, so that it may not be optimistic. And, during the same period, the CPI has fluctuated on the rate of 2.91% in average, so that the actual increase of income is on a level of 4%. Therefore, the increase of income is not so much.

On the other hand, according to the table “Average Annual Expenditure per Household and per Capita” in Chapter 2.3, share rate of foods to the total expenditure has improved from 42% in 2000 to 36% in 2005 that almost the same level of developed countries as summarized in the following table. But, it is rather questionable.

Share Rate of Foods to the Total Expenditure in Bulgaria

2000 2001 2002 2003 2004 200542.09% 42.72% 40.30% 38.14% 36.98% 35.97%Engel Coefficient




According to a result of “Water Utility Survey” made by JICA Study Team in 2006, the share rate of expenditure for foods to the total expenditure is more than 50% in both the Basins as shown in the following table, and it implies that the living of people may be in needy circumstances.

Share Rate of Expenditure for Foods to the Total Expenditure in Bulgaria (Lev/HH per month)

Source: A result of "Water Utility Survey" made by JICA Study Team, 2006.3.36%

17.56

17.47

283.60

271.22

52.75%

47.87%

12.74%

10.53%

Both theBasins

East AegeanRiver Basin

520.14

Income/HHin OverallAverage

River Basin

West AegeanRiver Basin

493.33

592.48

TotalFuel

31.82%274.39

62.36

62.83

62.7728.73%

12.07%

54.98%141.73

3.56%

Expenditure

493.3338.73%

592.48

Food andDrinks Water Others

2.88%

100.00%520.14

100.00%

100.00%

17.07

165.52

229.45

Provided that the share rate of expenditure for water of 3.36% is in average based on answers for expenditure by items, and this may be expressed for expenditure for public water supply, and it may not expressed the expenditure for water in total. Almost of people purchase a bottled mineral water. Actual expenditure for water in total is, as shown in the table entitled as “Expenditure for Water in Grand Total” in Chapter2.12, at 27.32 Lev/HH per month in weighted average in both the Basins, and its share rate to the total has reached to 5.25%.

Currently, consumed water volume has remained in low level as 92 ldc as of 2005 as shown in the following table. This is based on water charge collection record in water supply side, and so, it is the consumed water volume depending upon current public water supply systems. Namely, this consumed water volume may be the same amount of supplied water volume.

Changes of Consumed Water Volume by Public Water Supply Systems for the Past Several Years

(ldc)

Source: Environmental Statistics, 2005, NSI.

95 90 95 94 92Paid WaterVolume 99

2001 2002 2003 2004 20052000

Actual price of mineral water is 371 Lev/m3 as shown in the following table, so that the price 371 times of unit charge of water supplied by public water supply systems. Therefore, in case that the supplied water volume is enough for living, they must not purchase such expensive bottled mineral water.




Price of Bottled Mineral Water

Per Bottle Per Litre

Unit Price of Bottled MineralWater

Equal:(Lev/m3)

386

368

371

Source: Water Utility Survey made by JICA Study Team, 2006.

Both the Basin 0.56 0.37

West AegeanRiver Basin 0.55 0.37

West AegeanRiver Basin 0.58 0.39

River Basin(Lev/ 1.5ℓ bottle) (Lev/ℓ )

On the other hand, according to the other result of the said “Water Utility Survey”, the actual consumed water volume is 156 ldc (under the condition of 3.37 persons/HH in family scale for converting the consumed water volume per household per month) as shown in the following table. In other words, different water volume between 92 ldc and 156 ldc is to be covered by purchasing the said expensive bottled mineral water and/or some other source with heavy burden.

Actual Water Consumption

Source: A result of "Water Utility Survey" made by JICA Study Team, 2006.

156

Water Consumption(m3/HH per month)River Basin

Remarks:Conversion

into ldc(Average)Average

148

158

Both theBasins 18.43 13.02 15.73

East AegeanRiver Basin 18.77 13.25 16.01

West AegeanRiver Basin 17.55 12.45 15.00

Summer Winter

One of wastewater treatment plants under construction is designed under the condition of 180 ldc of discharge volume. If the discharge volume is assumed at 90% of consumed water volume, the consumed water volume is to be at 200 ldc. Taking into account of this as well as increase of consumed water volume for the future according to the current trend of water consumption as discussed above, it is assumed that envisaged consumed water volume will be increased by 220 ldc as of the target year 2015.




CHAPTER 5

5.1

Main Report

Chapter 5

Tables

5.2

5.3




Table 5.3.1 Fluctuation of Share Rate of Production by Economic Activities to GDP in the Past Several Years

4

(million Lev)

Agriculture/Hunting/Forestry 3,520 3,445 3,485 3,576 3,327Fishing 13 14 14 14 1Mining/Quarrying 403 412 440 530 566Manufacturing 4,606 4,966 5,516 5,989 6,750Electricity/Gos/Water Supply 1,591 1,634 1,652 1,722 1,626Construction 1,203 1,276 1,364 1,668 2,026

Hotels/Restaurants 535 563 625 713 8993,386 3,950 4,166 4,570 4,952

Financial Intermediation 831 986 1,147 1,382 1,682Real Estate/Renting 4,391 4,751 4,844 5,189 5,568

Education 1,073 1,127 1,194 1,336 1,404Health/Social Work 661 858 960 998 1,031

Total 26,356 28,526 30,227 33,169 36,023Adjustment 3,354 3,809 4,319 5,106 5,925FISIM* -539 -596 -753 -1,043 -1,360Import Duties 195 188 231 292 372Net Taxes on Products 1,057 1,143 1,434 1,938 2,115VAT 2,641 3,073 3,407 3,918 4,798GDP at Market Prices 29,709 32,335 34,547 38,275 41,948(Note) *FISIM = Financial Intermediation Services Indirectly Measured.Source: Statistical Yearbook, 2006, NSI.

626 771

Economic Activity Group

Gross Value Added in Each EconomicActivity Group at Basic Prices

Transport/Storage/Communications

OtherCommunity/Social/Personal

450 480 503

2,506 2,950

Public Administration/Compulsory Social Security 1,754 1,958 2,132 2,351 2,457

Trade/Repair of Motor Vehicles/Personal-Household Goods 1,937 2,105 2,186

2001 2002 2003 2004 2005




Table 5.3.2 Change of Share Rates by Economic Activities to GDP

Agriculture/Hunting/Forestry 11.85% 10.66% 10.09% 9.34% 7.93% 9.97%Fishing 0.04% 0.04% 0.04% 0.04% 0.03% 0.04%Mining/Quarrying 1.36% 1.28% 1.27% 1.38% 1.35% 1.33%Manufacturing 15.50% 15.36% 15.97% 15.65% 16.09% 15.71%Electricity/Gos/Water Supply 5.36% 5.05% 4.78% 4.50% 3.88% 4.71%Construction 4.05% 3.95% 3.95% 4.36% 4.83% 4.23%

6.59%

Hotels/Restaurants 1.80% 1.74% 1.81% 1.86% 2.14% 1.87%11.40% 12.22% 12.06% 11.94% 11.81% 11.88%

Financial Intermediation 2.80% 3.05% 3.32% 3.61% 4.01% 3.36%Real Estate/Renting 14.78% 14.69% 14.02% 13.56% 13.27% 14.07%

6.03%

Education 3.61% 3.49% 3.46% 3.49% 3.35% 3.48%Health/Social Work 2.23% 2.65% 2.78% 2.61% 2.46% 2.54%

1.59%

Total 88.71% 88.22% 87.50% 86.66% 85.87% 87.39%Adjustment 11.29% 11.78% 12.50% 13.34% 14.13% 12.61%FISIM* -1.82% -1.84% -2.18% -2.72% -3.24% -2.36%Import Duties 0.66% 0.58% 0.67% 0.76% 0.89% 0.71%Net Taxes on Products 3.56% 3.54% 4.15% 5.06% 5.04% 4.27%VAT 8.89% 9.50% 9.86% 10.24% 11.44% 9.99%GDP at Market Prices 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%(Note) *FISIM = Financial Intermediation Services Indirectly Measured.Source: Statistical Yearbook, 2006, NSI.

Average

5.86%

OtherCommunity/Social/Personal 1.51% 1.48% 1.46% 1.63% 1.84%

2005

Trade/Repair of Motor Vehicles/Personal-Household Goods 6.52% 6.51% 6.33% 6.55% 7.03%

Share Rate of Gross Value Added in Each EconomicActivity Group to the Total Gross Value Added

2001 2002 2003Economic Activity Group

2004

Public Administration/Compulsory Social Security 5.90% 6.06% 6.17% 6.14%

Transport/Storage/Communications

5.4




Table 5.4.1 Potential Area and Fluctuated Actual Irrigated Area

Irrigation Branch

Potential Irrigation Area (ha)

Actual Irrigated Area (ha) Average Irrigation Portion

(%) 2000 2001 2002 2003 2004 2005 Average

Burgas 19,922 1,390 499 379 349 63 64 457 2.29% Varna 17,246 3,276 2,301 2,849 3,306 485 757 2,162 12.54% Veliko Tarnovo 42,683 3,807 395 396 1,216 862 77 1,126 2.64% Vidin 20,737 1,208 782 870 822 306 34 670 3.23% Vratsa 47,224 4,949 1,835 720 1,085 1,103 290 1,664 3.52% Gotse Delchev 16,809 8,656 1,858 1,070 3,131 2,654 2,010 3,230 19.22% Dupnitsa 26,317 5,324 1,166 516 678 654 198 1,423 5.41% Montana 22,750 626 842 477 349 325 163 464 2.04% Pazardzhik 57,799 20,161 11,476 6,676 9,784 10,046 5,451 10,599 18.34% Pernik 16,045 1,542 570 368 426 331 339 596 3.72% Pleven 53,127 8,254 3,732 2,668 3,452 2,874 651 3,605 6.79% Plovdiv 106,878 30,600 24,792 12,441 20,024 17,598 9,233 19,115 17.88% Ruse 57,573 895 961 710 1,317 446 137 744 1.29% Sandanski 15,790 3,657 2,097 1,923 1,172 1,220 1,140 1,868 11.83% Sliven 199,816 9,738 5,595 4,880 5,469 2,408 1,557 4,941 2.47% Sofia 29,555 1,726 819 827 824 985 624 967 3.27% Stara Zagora 75,404 16,693 11,782 4,844 3,527 1,611 957 6,569 8.71% Targovishte 26,123 5,001 2,497 2,027 3,979 2,718 933 2,859 10.95% Haskovo 50,059 7,474 3,486 3,710 5,597 5,365 2,988 4,770 9.53% Shumen 37,398 2,312 2,512 2,113 3,475 1,629 604 2,107 5.64% Yambol 37,421 4,543 1,949 3,048 3,470 1,609 1,170 2,631 7.03% Total 976,673 141,834 81,946 53,513 73,451 55,289 29,376 72,568 7.43% (Remarks) West Aegean River Basin. East Aegean River Basin. (Note) Some irrigation branches cover several municipalities located in other river basins. Source: Irrigation Systems PLC.

5.5




CHAPTER 5

5.1

Main Report

Chapter 5

Figures




2005 341,873 0.1198% 341,873 0.1198% 341,873 0.1198%2006 342,770 0.2624% 342,508 0.1857% 342,296 0.1238%2007 343,546 0.2263% 343,142 0.1852% 342,719 0.1235%2008 344,321 0.2256% 343,776 0.1848% 343,142 0.1233%2009 345,096 0.2250% 344,410 0.1843% 343,564 0.1231%2010 345,870 0.2244% 345,043 0.1839% 343,986 0.1229%2011 346,644 0.2238% 345,676 0.1835% 344,408 0.1227%2012 347,418 0.2232% 346,309 0.1831% 344,830 0.1225%2013 348,191 0.2226% 346,942 0.1826% 345,252 0.1223%2014 348,964 0.2220% 347,574 0.1822% 345,673 0.1221%2015 349,736 0.2214% 348,206 0.1818% 346,095 0.1219%

Annual Average: 0.2277% 0.1837% 0.1228%

Year OptimisticCase

Increaseagainst

previousyear

MediumCase

Increaseagainst

previousyear

PessimisticCase

Increaseagainst

previousyear

Pessimistic caseMedium caseOptimistic case

340,000

342,500

345,000

347,500

350,000

352,500

355,000

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Year

Popu

latio

n

Opptimistic case: Based on the same trend of the last 3 yearsMedium case: Based on 1/2 trend of the last 3 yearsPessimistic case: Based on 1/4 trend of the last 4 years

Figure 5.1.1 Population Projection of the Municipality of Plovdiv

2005 77,462 0.0517% 77,462 0.0517% 77,462 0.0517%2006 77,502 0.0510% 77,482 0.0258% 77,472 0.0129%2007 77,541 0.0516% 77,502 0.0258% 77,482 0.0129%2008 77,581 0.0515% 77,522 0.0257% 77,492 0.0129%2009 77,621 0.0515% 77,542 0.0257% 77,502 0.0129%2010 77,661 0.0514% 77,562 0.0257% 77,512 0.0128%2011 77,701 0.0514% 77,582 0.0257% 77,522 0.0128%2012 77,741 0.0513% 77,602 0.0257% 77,532 0.0128%2013 77,781 0.0512% 77,621 0.0256% 77,542 0.0128%2014 77,821 0.0512% 77,641 0.0256% 77,552 0.0128%2015 77,860 0.0511% 77,661 0.0256% 77,562 0.0128%

Annual Average: 0.0513% 0.0257% 0.0128%

Increaseagainst

previousyear

PessimisticCase

Increaseagainst

previousyear

Year OptimisticCase

Increaseagainst

previousyear

MediumCase

Pessimistic case

Medium case

Optimistic case

77,200

77,300

77,400

77,500

77,600

77,700

77,800

77,900

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015Year

Popy

ulat

ion

Opptimistic case: Based on the same trend of the last 2 yearsMedium case: Based on 1/2 trend of the last 2 yearsPessimistic case: Based on 1/4 trend of the last 2 years

Figure 5.1.2 Population Projection of the Municipality of Blagoevgrad

4,000

5,000

6,000

7,000

2001 2002 2003 2004 2005Year

Inco

me

(Lev

s/Y

ear)

5.2

5.3

5.4

5.5

Figure 5.5.1 Changes of Income Level per Household in Bulgaria for Past Several




CHAPTER 6 RIVER BASIN MANAGEMENT PLAN

6.1 Formulation of River Basin Management Plan

6.1.1 Introduction

EABD and WABD have to prepare the River Basin Management Plan (RBMP) in accordance with the EU-WFD, of which the target is to attain the good physico-chemical and ecological status for surface water and groundwater by 2015. The main deadlines and milestones of the planning of the RBMP are set by the WFD as follows:

• Ecological status classification (Type-B) by 2004, • Impact review completed by member states and register of protected areas by

2004, • Summary reporting of impact review to Commission by 2005, • Monitoring programme operational by 2006, • Programme of measures to be established for achieving the environmental

objectives of the WFD based on sound monitoring and the analysis of the characteristics of the river basin; and the 1st River Basin Management Plan completed by 2009, including the designation of heavily modified water bodies,

• Cost recovery for water services in accordance with the polluters pay principal by 2010,

• Programmes of measures operational by 2012, • Revised overview of significant water issue by 2013, and • Evaluation of the first period and update the RBMP for the next two six-year

cycles of planning and implementation of measures by 2015.

The Government of Bulgaria established four river basin directorates from 2002 to 2003 in accordance with the Water Act of Bulgaria, which was enacted in 2000. The four basin directorates have started the arrangement of river basin management activities and also started the preparation for the RBMP in accordance with the EU-WFD and the Water Act of Bulgaria.

The output of the present study does not correspond one by one to the form of River Basin Management Plan defined by EU-WFD. The JICA Study considered both EU-WFD and Water Act, e.g. the share of water quantity is minimal in EU-WFD, but water quality and water quantity have been dealt as two pillars in the Study. The results of the present study would be considered in the forthcoming process of the preparation of the River Basin Management Plans.

The Study has supported EABD and WABD in preparation of RBMP, of which the planning process requires the participation of stakeholders through a series of Public Consultation Meetings. The public consultations have been conducted in three stages as follows:




Planning Stages Components according to EU- WFD Public Consultation

Current and foreseen scenarios assessment

- Monitoring the current status - Assessment of the current status

1st public consultation; Conducted in November 2006. Main topics: Current status of impacts

Target setting and preliminary programmes of measures

Setting up of the environmental objectives and preliminary programmes of measures

2nd public consultation; Conducted in September 2007 Topics: Direction of Programmes of measures

Alternative programmes of measures and actions taking

- Setting up of the programme of measures

- Establishment of monitoring programmes

- Development of River Basin Management Plans (RBMP)

3rd public consultation Conducted in December 2007 Topics: Programmes of measures and RBMP (Draft)

6.1.2 Pressures and Impacts in the River Basin Level

The current status of surface water and groundwater in the Study Area are studied and discussed in Chapter 2 in this report. Significant pressures and impacts to be caused by human activities are listed as follows:

• Discharges of wastewaters from settlements, industries and large animal breeding farms without WWTPs or with WWTPs without a proper treatment,

• Discharge of pollution loads from settlements without sewerage facilities,

• Discharge of pollution loads from agricultural lands and animal breeding farms,

• Impacts caused by inappropriate water intakes for water supply, irrigation and inter-basin water transfer,

• Physical impacts by river-morphological changes, caused by improper activities like heavy sand and gravel extraction in and along river channels,

• Impacts caused by informal or illegal activities like solid waste dumping into or along the rivers, and

• Combined effects of various improper management activities in and along the rivers.

6.1.3 Target Year for the Completion of Programmes of Measures

According to the time schedule set by the EU-WFD, the RBMP including improvement plans should be formulated by the end of 2008 and commenced in 2010. Bulgaria is paying effort to follow the schedule, however, it may not be an easy task to formulate the RBMP of the national level.

To start the implementation of programme of measures from 2010, the implementation of structural measures will require the three steps, “F/S”, “D/D” and “construction”, and require more than two years for tendering, selection of consultants and constructors.




When the conditions of lack of implementing organization and lack of experience are considered, it may be difficult to expect effective preparation activities.

There are many existing sewerage facilities, which need rehabilitation because of poor maintenance work and superannuation, and also there may be increment of many unexpected measures to cope with.

Implementation of the proposed River Basin Management Plan by the target year 2015 is thus deemed difficult, and hence, the target year should be set at 2021 or 2027, years for every six years review defined by EU-WFD.

6.1.4 Baseline Scenario for the RBMP

According to the Study on the current status of the surface water and groundwater it is clear that both the surface water and groundwater are heavily affected by the human activities and the water related facilities have been deteriorated or superannuated. The targets of the water quality are set as follows:

• To attain good physico-chemical status for surface water (Reference class-I and II), and

• To attain good ecological status for surface water (Reference class High and Good).

In order to attain the target, various measures composed of structural and non-structural measures shall be implemented duly within a limited period. Accordingly a systematic implementation of various measures for RBMP shall be required for the managing organization to the target by 2015.

RBMP is necessary to be formulated from integrated water resources management aspects. The programme of measures in the RBMP shall be required for improving qualitative, quantitative and river morphological conditions. The River Basin Management Plan shall be formulated based on the Integrated Water Resources Management approach. The basic scenario is proposed as follows:

• To improve water quality firstly to attain the good physico-chemical status for surface water and groundwater, and secondly to attain the ecological status for surface water and groundwater by 2015,

• To improve water quality by phased expansion of the municipal wastewater treatment capacities and treatment for nitrogen and phosphorous by new construction of WWTPs and also by phased rehabilitation of the existing WWTPs from major towns and settlements in priority zones,

• To renovate the existing sewer networks to reduce the sewage loss to increase the efficiency of wastewater treatment and also reduce the seepage of sewerage into the ground to avoid possible groundwater pollution,

• To rehabilitate water supply networks to reduce the high rate of water supply loss of 60-70%,

• To improve the management and regulation in order to conduct more strong control of reducing the discharge of untreated or improperly treated wastewaters from industries, mines and animal breeding farms,




• To improve facilities required for efficient water use of water use sectors like domestic water supply networks and irrigation facilities,

• To improve the permission of water intakes and the distribution of water resources based on the water balance of each river basin,

• To improve the management and regulation in order to conduct more systematic management for river morphology, river channels, river flows, sediment and also floods disaster, flood hazard areas, and

• To prepare programme of measures composed of the following components:

i) Water quality improvement and management

ii) Water quantity improvement and management

iii) Management of river morphology

iv) Implementation

6.1.5 Required Management Plans

The surface water and groundwater in the EABD and WABD have been studied. The programmes of measures for the RBMP are required to be studied. The RBMP requires programmes of measures:

• To improve the status of chemical and physical conditions,

• To improve the status of quantitative conditions,

• To improve the status of river morphological conditions, and

• To improve the status of prevention of flood disasters and incidental disasters caused by toxic waste or substances.

The RBMP is to be composed of the following plans:

• Water quality management plan,

• Water quantity management plan,

• Groundwater management plan,

• River management plan, and

• Implementation plan.

Each plan is to be discussed in the following sub-sections.




6.2 Water Quality Management Plan

6.2.1 Objectives of Water Quality Management Plan

• To attain good status of water in terms of ecology and common physico-chemical parameters by reducing organic pollutants and nutrients inflow to water bodies.

• To prevent direct discharge of wastewater without treatment (domestic, industrial, livestock wastewaters) into the surface water bodies and relating groundwater bodies.

• To reduce pollution loads from industries, livestock and agriculture mainly by strengthening of regulation.

• To propose programme of structural measures with rough cost estimation.

• To propose implementation plan for the programme of structural measures.

• To propose non-structural measures such as monitoring, improvement of regulation, etc.

6.2.2 Pollution Loads

(1) Methods of Estimating Pollution Loads

(a) Items of the Pollution Loads Estimation in the River Basins

Reduction of pollution loads from the river basins is only the way for improving water quality in the rivers and water bodies. The following items of pollution loads were estimated in the Study.

Domestic pollution loads plus industrial pollution loads, which are discharged into the sewerage systems (BOD5, TN and TP loads).

Industrial pollution loads, which are discharged directly into the rivers or water bodies (BOD5, TN and TP loads).

Livestock pollution loads, which are composed of the pollution loads from major livestock firms as the point sources and other small size livestock firms or livestock owned by farmers as non-point sources (BOD5, TN and TP loads).

Fertilizer as non-point pollution loads (TN and TP loads).

(b) Domestic Pollution Loads plus Industrial Pollution Loads discharged into the Sewerage Systems

Domestic pollution loads are generated and discharged from people. Therefore, population in each settlement and town is the basis for calculation.

The existing Water Supply and Sewerage Companies (WSSs) have contracts with industries, which discharge their wastewater into the sewerage networks. The WSSs have obligation to send copies of the above contracts to the Basin Directorates, but this rule is not followed in many cases.




Basin Directorates either RIEW have almost no information and data about such industries (list, contracted amount of water supply, and discharge quantity and quality of wastewater), which discharge into the sewerage system. Basin Directorates and RIEW have the information of discharge quantity and quality of wastewater (although not covering all) at the outlet of sewer pipes or outlet of the existing urban or municipal WWTPs.

Considering the above situation, the industrial loads, which are discharged into the sewerage systems, have to be estimated together with the domestic loads based on the population equivalent (PE). In order to overview and manage the total industrial loads in the river basins, it is very necessary to know the industrial loads which discharge into the sewerage systems too.

Applied Ratio of PE / Population

PE size of Town / Settlement Ratio of PE / Population

PE ≥ 10,000 • 1.5 in principle, or • Ratio in Document A.

2,000 ≤ PE < 10,000 • 1.2 in principle, or • Ratio in Document A.

500 ≤ PE < 2,000 • 1.2 in principle PE < 500 • 1.0

Document A: “Implementation Programme for Directive 91/271/EC concerning Urban Wastewater Treatment” (National Programme for WWTP).

The following table shows the applied unit loads for estimating the domestic loads and industrial loads, which are discharged into sewerage systems.

Unit Loads for Domestic and Industrial Load discharged into Sewerage Systems

Item BOD (g/day/PE)

TN (g/day/PE)

TP (g/day/PE)

1) Raw: 1pe 60 11 1.8 2) Sewered without treatment 60 11 1.8 3) With primary treatment by the

existing WWTP

35

11

1.8 4) With secondary treatment by

the existing WWTP

10 4

1

5) Without sewerage system 15 3 1 6) With new WWTP including TN

and TP treatment 6

2.5

0.9

(c) Loss of the Existing Sewer Networks

Based on the analysis of the self-monitoring data of some of the existing WWTPs in EABD and WABD, it can be known that the pollution loads, which flow through the sewer pipes, are lost, and significant dilution is occurred by infiltration of water from surrounding ground at the same time.

Percentages of above loss in terms of BOD5 are estimated at least about 40% for the sewer networks in the Maritsa and Tundzha River Basins, 50% in the Arda River Basin and 60% in the Struma, Mesta and Dospat River Basins in general.




The existing monitoring data of RIEWs at the outlet of the existing sewer pipes also show low concentration of BOD5 in general. This fact supports the above estimation of the significant pollution loss from the sewer networks. The lost pollutants contaminate surrounding groundwater. There is a fact that many groundwater wells have problem of nitrate (NO3) contamination, and this might be caused not only by fertilizers containing nitrogen, but also by the loss from the sewer networks.

Estimated Loss of Pollution Loads at the Inlet of the Existing WWTPs

WWTP

Inflow Outflow PE in 2005 (NSI data) Inflow

BOD Load to WWTP (kg/day)

Generated BOD Load

By PE (kg/day)

Loss of

BOD Load (%)

=1-F/G

Discharge (l/s)

BOD5 (mg/l)

BOD5(mg/l)

Total PE

TreatedPE

A B C D E F G H Kyustendil WWTP 210 81.3 6.1 70,688 65,638 1,477 3,938 62

Pernik WWTP 483 51.4 19.6 121,350 120,168 2,148 7,210 70

Radomir WWTP 51 53.3 2.5 21,621 19,367 236 1,162 80

Sliven WWTP 168 445.5 87.2 100,294 100,294 6,483 6,134 -

Plovdiv WWTP 1,667 125.0 - 666,652 599,987 18,005 35,999 50

Nova Zagora WWTP

162

301.4

21.2

58,463

32,388

4,318

1,943

-

Data sources: 1) Self monitoring data of the above WWTPs.

Estimated Loss of BOD5 at the Outlet of the Existing Sewer Pipes

River Basin

Average BOD5 at outlets of sewer

pipes (mg/l)

% of BOD5 against normal low value of sewage (150 mg/l)

% of BOD5 against normal value of

sewage (200 mg/l)

Maritsa River Basin 87 58 % (loss 42%) 44 % (loss 56%) Tundzha River Basin 114 76 % (loss 24%) 57 % (loss 43%) Arda River Basin 100 67 % (loss 33%) 50 % (loss 50%) Struma River Basin 64 43 % (loss 57%) 32 % (loss 68%) Mesta River Basin 70 47 % (loss 53%) 35 % (loss 65%) Data sources: 1) Data of EABD and WABD based on the monitoring data of RIEWs.

(d) Industrial Pollution Loads discharged directly into the River or Water Bodies

Industrial pollution loads, which are directly discharged into the rivers or water bodies are estimated based on the self monitoring data from such industries, monitoring data of RIEWs for the emission of the industrial wastewater, and permission data for the wastewater discharge by the Basin Directorates to the industries.

For estimating the TN and TP Loads from the industries, “Regulation No. 6 of 9 November 2000 on the Limit Values for Admissible Contents of Dangerous and




Harmful Substances in the Waste Water Discharged in the Water Bodies” is also referred.

Tables 6.2.1 and 6.2.2 show the major industries in EABD and WABD, which discharge their wastewater directly into the rivers or water bodies.

(e) Livestock Pollution Loads

Livestock pollution loads are composed of the pollution loads from major livestock farms as point sources, and pollution loads from small and medium livestock farms including small numbers of livestock owned by farmers as non-point livestock farms.

The data of the major livestock farms are based on the information from National Veterinary Medical Service. Tables 6.2.3 and 6.2.4 show the major livestock farms in EABD and WABD.

Numbers of heads of livestock are based on the Agro-statistics of MoAF in 2003, which was used for estimating the non-point livestock loads. Run-off rate of the non-point livestock load is set at 5%.

Following table shows the applied unit loads for estimating the livestock loads.

Unit Loads for Livestock

Livestock BOD (g/year/head)

TN (g/year/head)

TP (g/year/head)

1) Cattle 230 79 1.4 2) Pig 7.98 4.0 0.75 3) Hens for egg production 0.7 0.4 0.12 4) Slaughter chicken 0.05 0.03 0.002 5) Duck 0.2 0.1 0.006

(f) Fertilizer as Non-point Pollution Loads

As the pollution loads from agriculture, fertilizer as non-point pollution loads are estimated based on the data of the fertilizer amount by district in Bulgaria, which were collected from the “National Plant Protection Service”. Run-off coefficient of 10% is applied for the estimation. Unit load of fertilizer is as shown below




Average Amount of Fertilizer by District and Unit Load

Area Average Fertilizer Amount (Year 1999 to 2005) Unit Load of Fertilizer

(km2) (kgN/year) (kgP/year) (kgN/y/m2) (kgP/y/m2) Plovdiv 5,961 7,366,998 234,339 0.00124 0.000039 Burgas 7,741 8,189,752 81,045 0.00106 0.000010 Blagoevgrad 6,458 1,743,346 103,836 0.00027 0.000016 Pazardzhik 4,459 2,350,964 164,106 0.00053 0.000037 Kardzhali 3,210 633,216 1,366 0.00020 0.000000 Kyustendil 3,060 760,438 20,776 0.00025 0.000007 Sofia 7,071 2,093,932 94,665 0.00030 0.000013 Stara Zagora 5,148 7,857,141 141,730 0.00153 0.000028 Haskovo 5,528 4,740,222 75,958 0.00086 0.000014 Smolyan 3,204 1,648,178 209,222 0.00051 0.000065 Sliven 3,542 4,183,851 28,153 0.00118 0.000008 Yambol 3,353 6,222,461 86,337 0.00186 0.000026 Pernik 2,397 710,138 3,531 0.00030 0.000001 Gabrovo 2,022 903,478 17,075 0.00045 0.000008 Veliko Tarnovo

5,961 7,366,998 234,339 0.00124 0.000039

Plovdiv 7,741 8,189,752 81,045 0.00106 0.000010

(2) Pollution Loads and Pollution Mechanism in EABD

(a) Present Pollution Loads and Pollution Mechanism in EABD

Present BOD loads by NAM catchment in EABD are estimated as shown in Figures 6.2.1 and 6.2.2 shows the BOD loads from unit area (= total BOD load of NAM catchment / area of NAM catchment). From these figures, it is clear that the area around Pazardjik, Plovdiv and Stara Zagora are the highest producers of BOD loads, which followed by the Dimitrovgrad and Haskovo Areas. In the Tundzha River Basin, Yambol to Elhovo areas is the highest producer of BOD loads. Sliven and Kazanlak Areas also produce high BOD loads from small areas. For the Arda River Basin, Kardzhali and Smolyan Areas are the highest producers of BOD loads.

These tendencies of the BOD load distributions coincide with the current pollution conditions along the Maritsa and Tundzha Rivers, where water quality is generally poor to moderate conditions from the upstream to the downstream. For the Arda River, the BOD load distribution also coincides with the tendency of river water quality, where the tributary along Smolyan Town and the river reach around Kardzhali Town is in poor condition.

These tendencies of BOD load distribution also coincide with the results of the Risk Analysis for the Surface Water Bodies made by the EABD Directorate.

In addition to the BOD Loads, Figures 6.2.5 and 6.2.7 show the Present TN and TP loads in EABD.

(b) Near Future BOD Loads in EABD

There are nine numbers of new WWTPs, which are under-construction. They are Pazardjik, Dimitrovgrad, Stara Zagora, Haskovo, Karlovo and Koprivshtitsa




WWTPs in the Maritsa River Basin, and Madan, Rudozem and Zlatograd WWTPs in the Arda River Basin. All of the new WWTPs can treat up to secondary treatment for BOD. Stara Zagora and Dimitrovgrad WWTPs have facilities of higher treatment for treating nitrogen and phosphorous. In Karlovo, construction of the new WWTP has been started only a part. However, it looks that the budget for the Karlovo WWTP construction is insufficient.

In addition to the above nine new WWTPs, rehabilitation of the existing Sliven WWTP including some improvement of sewer networks has been committed by ISPA, and it is under-tendering. New Smolyan WWTP including some improvements of sewer networks has also been committed by ISPA, and it has been already contracted with the contractor in 2007.

Figure 6.2.3 shows the BOD loads in the Near Future Conditions in EABD and Figure 6.2.4 shows the BOD loads from unit area. By the above under-constructed and soon constructed WWTPs, BOD loads will be reduced around Pazardjik, Stara Zagora, Dimitrovgrad, Haskovo, and Smolyan areas. Figure 6.2.6 and Figure 6.2.8 show the TN and TP loads in EABD in the Near Future Condition.

(3) Pollution Loads and Pollution Mechanism in WABD

(a) Present Pollution Loads and Pollution Mechanism in WABD

Present BOD loads by NAM catchment in WABD are estimated as shown in Figure 6.2.9 and 6.2.10 shows the BOD loads from unit area. In terms of BOD load in NAM catchments, Blagoevgrad area is the highest producer followed by Pernik, Dupnitsa, Sandanski and Petrich area. In terms of BOD load from unit area, Blagoevgrad, Sandanski, Gotse Delchev area are the highest density of BOD load, followed by Pernik, Dupnitsa, Bansko and Razlog area.

These tendencies of the BOD load distributions coincide with the current pollution conditions along the Struma and Mesta Rivers, and the results of the Risk Analysis for the Surface Water Bodies made by the WABD office.

Figures 6.2.13 and 6.2.15 show the Present TN and TP loads in WABD.

(b) Near Future Pollution Loads in WABD

There are two numbers of new WWTPs, which are under-construction. They are Blagoevgrad WWTP in the Struma River Basin and Razlog WWTP in the Mesta River Basin. These two new WWTPs can treat BOD up to secondary level. Razlog WWTP, which has almost completed construction by September 2007, has a partial function of nitrogen reduction.

In addition to the above two new WWTPs, rehabilitation of the existing Kyustendil WWTP including some improvements of sewer networks has been committed by ISPA, and it is under-tendering.

Figure 6.2.11 shows the BOD loads in the Near Future Conditions in WABD and Figure 6.2.12 shows the BOD loads from unit area. By the above under-constructed and soon renovated WWTPs, BOD loads will be reduced around Blagoevgrad,




Razlog areas. Figures 6.2.14 and 6.2.16 show the TN and TP loads in WABD in the Near Future Condition.

(4) Co-relation between Catchment BOD Load and River BOD Load

Co-relation between the accumulated catchment BOD load, which accumulate BOD load of NAM catchments locating upstream from certain calculation point in the river, and the river BOD Load in dry season (July to September) is calculated.

Accumulated catchment BOD load = ∑ (BOD load of NAM catchment i)

River BOD load = (BOD concentration in the river: C) x (Average discharge of river in dry season: Q)

Discharge : Q BOD concentration: C

NAM Catchment 1 River

NAM Catchment 2 Calculation point

Figures 6.2.17 and 6.2.18 show co-relation between the “Accumulated catchment BOD load” and “River BOD load”. Discharge of the river is based on the MIKE 11 Water Quantity Simulation results. BOD concentration (normal maximum values in dry season) in the river is based on the monitoring data of ExEA. Followings are the findings of this analysis.

There are very high co-relation between the “Accumulated catchment BOD load” and “River BOD load” for the Maritsa, Tundzha, Arda, Stuma and Mesta Rivers in general. The above high co-relations mean that the BOD loads in the upper catchment areas reflect the BOD concentration at certain location along the river. Considering the above fact, in order to improve water quality at certain location in the river, it is necessary to reduce the accumulated catchment load upstream from that location.

6.2.3 Structural Measures of the Programme of Measures

(1) Planning Principle

Based on the analysis of the pollution loads in the present and near future conditions as well as the water quality conditions in the rivers, followings are the procedure of planning the programme of measures, which is mainly applied for planning the structural measures for water quality management and improvement.

• BOD load is focused as a key parameter for the reduction of catchment pollution loads.




• The current water quality (in terms of BOD, etc.) in the rivers is reflected by the significant loss from sewer networks (at least 40% in Maritsa and Tundzha River Basins, 50% in Arda River Basin, and 60% in Struma and Mesta River Basins). However, the loss should be reduced from now on, which is hopefully up to 10% in the long time future. This reduction of loss is necessary to stop the pollution of groundwater by the loss from the sewer networks.

• In case the loss of the sewer networks will be reduced up to 10% and the treatment conditions of towns and settlements in EABD and WABD areas will be the same as the Near Future Conditions, the water quality in the river will be much worse than the present. This assumption is the basis for planning for reducing the catchment pollution loads as well as for improving future water quality conditions in the rivers.

• Based on the rough estimation of the required BOD loads in the river basins for attaining the good status of water in terms of BOD (Class II: target of BOD 3.0 mg/l), the accumulated catchment BOD loads are necessary to be reduced about 50% for Maritsa, Tundzha, Stuma and mid to downstream of Mesta River Basins. For the Arda River Basin, reduction of BOD load around Kardzhali Town is required.

• Based on polluter pay principle, reduction of catchment loads shall be shouldered by domestic, industry, livestock and the other sectors.

• For reducing domestic loads plus industrial loads into sewerage system, new WWTPs and rehabilitation of the existing WWTPs are planned as the structural measures.

• For reducing the industrial loads and the major livestock loads, strengthening of regulations are to be considered as the non-structural measures.

• Based on the distribution of the catchment BOD loads and its loads from unit areas (load density), high priority zones are identified for reference.

• Considering practical implementation by 2015 or 2021, the towns and settlements to be treated are selected based on the contribution for reducing the catchment BOD loads and the above zoning in principle. The target reduction of BOD loads by the high priority towns are provisionally to be set about 30%. Expert judgments are also introduced to select some additional high priority towns and settlements.

• For the proposed new and to be renovated WWTPs, higher level of treatment for reducing nitrogen and phosphorous are included.

• For the proposed high priority towns and settlements, improvement as well as expansion of the sewer networks are also proposed.

• It is recommendable to consider how to reduce pollution loads from smaller settlements such as improvement of septic tanks to be sealed septic tank or individual treatment of houses or some small size WWTP etc. from the settlements which locate in the high priority zones. In case of improvement of septic tanks or individual treatment, their sludge should be taken out periodically and to be treated in the nearby WWTPs or brought to sanitary landfill sites for temporary solution. Financial support systems are necessary to be considered for




the improvement of septic tanks and installing individual treatment facilities to the houses.

(2) High Priority Towns to be Treated in EABD

Considering the impacts to river basin in terms of reduction percentage of BOD Loads some other consideration to the impacts to the main rivers has been introduced. Figure 6.2.19 shows the selected high priority towns to be treated as well as the reference high priority zones. The selected high priority towns are shown in the table below. The sewer networks of these towns are also to be improved including renovation and expansion.

High Priority Towns (22 Towns) for Treatment in EABD Areas

Priority Town River Basin PE in 2015 WWTP Sewerage Remarks

I. New WWTPs in the Maritsa River Basin I-1 Asenovgrad Maritsa 78,054 New Improvement I-2 Plovdiv Maritsa 681,985 Existing Improvement Only SW

improve. I-3 Karlovo Maritsa 37,181 New Improvement Under

construction (only a part). Increase the budget is required.

I-4 Velingrad Maritsa 28,752 New Improvement I-5 Peshtera Maritsa 28,691 New Improvement I-6 Harmanli Maritsa 28,538 New Improvement I-7 Svilengrad Maritsa 28,050 New Improvement I-8 Chirpan Maritsa 25,413 New Improvement I-9 Rakovski Maritsa 23,453 New New I-10 Panagyurishte Maritsa 23,029 New Improvement I-11 Parvomay Maritsa 22,200 New Improvement I-12 Stamboliyski Maritsa 18,068 New Improvement I-13 Kostenets Maritsa 11,048 New Improvement Most

upstream town.

II. New WWTPs in the Tundzha River Basin II-1 Yambol Tundzha 118,971 New Improvement II-2 Karnobat Tundzha 28,916 New Improvement II-3 Elhovo Tundzha 16,808 New Improvement II-4 Kalofer Tundzha 4,229 New Improvement Most

upstream town.

III. New WWTPs in the Arda River Basin III-1 Kardzhali Arda 67,346 New Improvement IV. Renovation of the Existing WWTPs IV-1 Nova Zagora Maritsa 36,185 Renovation Improvement IV-2 Radnevo Maritsa 20,691 Renovation Improvement IV-3 Ihtiman Maritsa 20,234 Renovation Improvement IV-4 Pavel banya Tundhza 4,407 Renovation Improvement




(3) High Priority Towns to be Treated in WABD

In the same way as EABD, Figure 6.2.20 shows the selected high priority towns to be treated as well as the high priority zones for reference. The selected high priority towns are shown in the table below. The sewer networks of these towns are also to be improved including renovation and expansion.

High Priority Towns (9 Towns) for Treatment in WABD Areas

Priority Town River Basin PE in 2015 WWTP Sewerage Remarks

I. New WWTPs in the Struma River Basin I-1 Petrich Struma 45,020 New Improvement I-2 Sandanski Struma 40,358 New Improvement I-3 Simitli Struma 8,242 New Improvement II. New WWTPs in the Mesta River Basin II-1 Gotse

Delchev Mesta 30,185 New Improvement

II-2 Bansko Mesta 11,493 New Improvement III. New WWTPs in the Dospat River Basin III-1 Dospat Dospat 3,218 New Improvement Currently,

only sewage from the town flow in the river.

IV. Renovation of the Existing WWTPs IV-1 Pernik Struma 121,350 Renovation Improvement IV-2 Dupnitsa Struma 55,224 Renovation Improvement IV-3 Radomir Struma 21,621 Renovation Improvement

(4) High and Medium Priority Towns for EABD and WABD

In order to reduce pollution loads up to around 40%, high and medium priority towns are also studied. Figures 6.2.21 and 6.2.22 show the high and medium priority towns, where new WWTPs or renovation of the existing WWTPs as well as improvement or expansion or new sewer networks are to be constructed. As the numbers of the towns/settlements are total 56 in EABD, and 20 in WABD. Considering the realistic programme for constructing the proposed WWTPs, these numbers of the WWTPs may be too heavy for implementation by 2015 or by 2021. Therefore, these plans can be considered as reference for the future plans.

(5) Estimated Amount of Reduction Loss by Improvement of Sewer Networks

By improvement of the existing sewer networks, loss of pollutants from the sewer pipes to the ground will be reduced. This will improve the condition of pollution in the surrounding groundwater by the loss from the sewer pipes.

It is difficult to estimate the amount of groundwater, which is contaminated by the loss from the sewer pipes. However, supposing that the NH4 in sewer pipes (about 20 to 25




mg/l) is leaked out to the ground and contaminate the groundwater, about 20 times dilution is required to reach 0.5 mg/l of standard permissible level.

Setting the target of loss from the sewer networks to be 10% in the future, Table 6.2.5 shows the estimated amount of reduction of groundwater contamination by the loss from sewer networks in the high priority towns. In this calculation, dilution is set at 10 times for conservative calculation. This table also shows the amount of newly treated sewage by the proposed plans for the high priority towns.

Estimated Amount of Reduction of Polluted Groundwater by Improvement of Sewer

Networks

Basin District

Amount of Sewage Loss(m3/year)

Amount of polluted groundwater by the sewage

loss (m3/year)

Reduction amount of polluted groundwater by improvement of sewer

pipes (m3/year) EABD 32,282,000 322,820,000 290,538,000WABD 13,833,000 138,331,000 124,498,000Total 46,115,000 461,151,000 415,036,000

(6) Cost Estimation for the Proposed Structural Measures

(a) Construction Cost for WWTPs and Sewer Networks Data on the construction costs of recently completed WWTPs and under-constructed WWTPs are collected and analyzed. For the analysis, all the construction costs are converted to the current price level in the middle of 2007. Based on the analysis, Unit construction cost of WWTP by PE is estimated. The cost includes the normal secondary treatment for BOD as well as tertiary treatments for TN and TP load reduction facilities.

Required length and cost of sewer pipes by PE is estimated.

Table 6.2.6 shows the estimated rough construction costs (without VAT) for the new or rehabilitation of WWTPs and related improvements of sewer networks for the proposed high priority towns in EABD and WABD areas. Summary of the estimated costs is shown below:

Estimated Rough Construction Cost for the New and Renovation of WWTPs and

Improvement of Sewer Networks in EABD and WABD Areas

Basin District

WWTPs (in1000 euros)

Sewer Networks (in 1000 euros)

Total (in 1000 euros)

EABD 206,050 1,628,082 1,834,133 WABD 72,074 536,553 608,627 Total 278,124 2,164,635 2,442,760

(b) Operation and Maintenance Costs for WWTPs and Sewer Networks Operation and maintenance cost for WWTPs are estimated based on the annual rate of 7.5% to the direct construction cost.

Operation and maintenance costs for sewer networks are estimated based on the annual rate of 1.5% to the direct construction cost.




Table 6.2.7 shows the estimated operation and maintenance costs (without VAT) for the proposed WWTPs and sewer improvements for the high priority towns.

(7) Implementation Plan of the Structural Measures

For implementing the proposed WWTPs and improvement of sewer networks, following two scenarios are considered.

(a) Optimistic Scenario: All will be implemented from 2012 to the end of 2014

(b) Practical Scenario: Divided into first group and second group.

The first group will be implemented from 2012 to the end of 2014.

The second group will be implemented from 2018 to the end of 2020.

Figure 6.2.23 shows the tentative practical scenario. It can be modified based on updated information.

6.2.4 Non-Structural Measures of the Programme of Measures

(1) Cooperation with Municipality for Water Quality Management

The coverage area of each Basin Directorate is very wide, number of staff of each Basin Directorate, however, is very limited between 50 to 60 people. Even with the RIEW, number of the staff for monitoring and managing the water in the Basin District Area is very limited. It is thus physically rather difficult to monitor what is happening in the whole area of the Basin District in every moment. This will delay the actions for improving the situation. The following are proposed for the proper management.

In order to conduct river basin management for the River Basins more properly and timely, it is highly recommendable to conduct monitoring for the important or problematic places such as the key monitoring stations in the river basins under cooperation from the municipality offices.

Daily patrol with ocular observation is the basic way. Furthermore, it is better to conduct simple on-site measurement of water such as temperature, pH, turbidity, DO, EC and others.

If any strange facts such as strange color, floating of many fish, abnormal values of pH, DO and others can be found by the daily patrol and simple measurement, it should be reported to the Basin Directorates for immediate actions including more detailed investigation, regulation to the polluters, etc. as well as warning to the people.

Legislative arrangement is necessary to be made for realizing the cooperation with municipality offices for water management.




(2) Strengthening of Regulation for Wastewater Discharge

(a) Monitoring of Industrial Wastewater discharged into Sewerage System

Wastewater discharge into the sewerage system from industries and other private sectors is controlled and managed by Water Supply and Sewerage Companies (WSSs), because WSSs have contracts with such industries under the current law. Furthermore, although the Basin Directorates issue permission for wastewater discharge into the rivers or water bodies from sewerage systems including discharge from urban or municipal WWTPs, the Basin Directorates have almost no information about the wastewater from the industries etc., which discharge into the sewerage systems. Due to this reason, it is very difficult to grasp the total view of the pollution loads in the river basin.

As the distribution pollution loads is one of the most important information for managing or improving water quality, it is very necessary to monitor the wastewater discharge from industries, etc. into the sewerage systems.

Therefore Water Act and related laws should be revised so that the Basin Directorates can collect information of the industrial wastewater, which is discharged into the sewerage systems.

(b) Treatment of Wastewater by Industries and Animal Breeding Farms by Themselves

Very often, industries discharge harmful substances such as petrol and heavy metals, which cannot be treated by urban or municipal WWTPs.

It is necessary to strengthen regulation, so that industries and large animal breeding farms shall treat their wastewater by themselves.

It is not recommendable to include industries into sewerage system, which discharge harmful substances or huge amount of wastewater.

Furthermore, it should not be allowed that industries or large animal breeding farms to pay the fines many times, which are imposed to them in case of discharge untreated wastewater. If industries or large animal breeding farms do not improve the condition of discharging untreated wastewater by themselves such as installing wastewater treatment plants for industrial discharge or discharge from large animal breeding farms, Basin Directorates should not issue discharge permit to those industries or animal breeding farms.

(3) Strengthening of Individual Wastewater Treatment

Improvement of septic tanks to sealed type or to introduce individual treatment shall be promoted. Sludge should periodically be extracted and treated. Financial support system to people shall be necessary for the improvement.




(4) Reduction in Pollution Load in Agricultural Area

Reduction of pollution load from the agricultural lands by changing farming methods and technology to reduce chemical fertilizer and pesticide will be introduced.

6.2.5 Improvement of Surface Monitoring System for Water Quality

(a) New Monitoring Programme for Surface Water

Based on the risk assessment of surface water bodies and groundwater bodies, MoEW and the Basin Directorates formulated a New Monitoring Programs in March 2007, which is composed of new programmes for surface water monitoring and groundwater monitoring. This sub-section proposes further improvement for the new programme for surface water monitoring.

In compliance with the requirements of the EU-WFD, the new programme for surface water monitoring includes surveillance monitoring (control monitoring) and operational monitoring. The surveillance monitoring will make overview the condition of the basin, give idea for efficient monitoring programme, and monitor long-term changes of the basin. The operational monitoring will monitor the status of the water bodies at risk, and assess the impact of the programme of measures. Figure 6.2.24 shows the locations of the surveillance and operational monitoring points.

The surveillance monitoring and the operational monitoring will monitor surface water quality in terms of hydro-biological indicators and physico-chemical parameters. Hydro-biological indicators to be monitored are Phytoplankton, Macrophytes, Phytobenthos, Macrozo benthos / Bottom invertebrate, Fishes and others. Physico-chemical parameters to be monitored are 1st Group (common parameters such as pH, temperature, DO, BOD5, COD, NH4-N, NO2-N, NO3-N, and PO4-P etc.), 2nd Group (TN, TP, Ca, Mg, hardness etc.), the Group of Priority substances (33 parameters), and the Group of Specific polluters (organic substances and heavy metals). Number of parameters to be monitored and frequency of monitoring differs for the monitoring stations. The number of the monitoring points is shown in the table below.




Number of the New Surveillance (Control) Monitoring Points for Surface Water

Basin Directorate River Lake Coastal Water DRBD 92 41 - BSBD 26 12 7 EABD 27 5 - WABD 33 16 - Sub-Total 178 74 7 Total 259

Number of the New Operational Monitoring Points for Surface Water

Basin Directorate River Lake Coastal Water DRBD 55 - - BSBD 32 16 6 EABD 58 4 - WABD 80 12 - Sub-Total 225 32 6 Total 263




(b) Proposals for Improvement

(i) Setting Key Monitoring Stations to Ensure Stable Monitoring

Total number of the monitoring points of the New Surface Water Monitoring Programme in the country is 522 points, which is slightly more than the number of the points of the existing surface water monitoring of ExEA. However, the parameters to be monitored are very much increased and their frequency for monitoring is also rather high (ex. 12 times per year for the priority substances for surveillance monitoring for one year at least). Furthermore, Bulgaria has no enough experience for measuring many items of the priority substances.

Considering this situation, it is recommendable to set Key Monitoring Stations as well as Important Monitoring Stations among the surveillance monitoring points to ensure stable monitoring and to overview the water quality conditions of the river basins. Furthermore, at these Key stations, it is necessary to measure the water quantity as well. In order to conduct this kind of permanent monitoring at the Key Monitoring Stations, the Basin Directorates are necessary to establish their own monitoring stations both for water quality and water quantity. Figure 6.2.25 shows the proposed Key Monitoring Zones as well as Important Monitoring Zones in EABD and WABD by the Study, where the Key Monitoring Stations and Important Monitoring Stations are recommendable to be set within these zones.

Proposed Key Monitoring Zones and Important Monitoring Zones in EABD and WABD

Key/Important Monitoring Zones EABD WABD Monitoring

Key Monitoring Zone 12 places 7 places Daily ocular observation and simple on-site measurement. Monthly sampling and analysis.

Important Monitoring Zone 10 places 4 places Weekly ocular observation and simple on-site measurement. Monthly sampling and analysis.

Total 22 places 11 places

If Key Monitoring Zones and Important Monitoring Zones will be set in DRBD and BSBD area as well, order of the Key Monitoring Zones in the country will be around 50 places and Important Monitoring Zones will be around 25 places.

It is recommendable to start monitoring in the above Key and Important Monitoring Zones under cooperation from some of the municipalities as the pilot cases, and will be extended to all over the Basin District Areas.

Furthermore, the results of the monitoring at the Key Monitoring Zones and Important Monitoring Zones will be reported to EU instead of above 259 surveillance stations.




(ii) Capacity Building and Stage-wise Implementation of the New Monitoring

Programme

The new monitoring programme for surface water includes several hydro-bilogical indicators. As the existing hydro-biological monitoring is mainly based on the macrozo benthos / bottom invertebrate, there are not so much experience and experts for other indicators. Furthermore, the new monitoring programme requires for measuring many priority substances, which are also new for Bulgaria.

Therefore, it is necessary to consider the way of developing human resources to conduct these measurements, and consider stage-wise implementation of the new monitoring programme, so that all of the required indicators and parameters by EU-WFD can be measured properly with sufficient accuracy.

(iii) Quality Control Programme to be formulated and implemented

In terms of physico-chemical measurement, the existing data such as BOD5, CODMn, and heavy metals seem to be unreliable in many cases. Therefore, it is very necessary to formulate quality control programme for sampling and laboratory analysis. As many priority substances are required to be measured, quality control is also important. It is recommendable to include followings in the quality control programme.

• Central laboratory in ExEA shall formulate quality control teams with qualified experts.

• In order to check the quality of the sampling and analysis by different laboratories, conduct inter-calibrations (analyze the same sample by different laboratories at the same time). In this case, the central laboratory (ExEA) should coordinate the checking activity.

• Send samples to the reliable laboratories of other countries and compare the test results made by the laboratories in Bulgaria (heavy metals and priority substances, etc.)

• The quality control team of the central laboratory shall periodically go around the regional laboratories in the country for checking the results of analysis, and make guidance and training to the staff of the regional laboratories.




6.3 Water Quantity Management Plan

6.3.1 Programme of Measures for Water Supply Improvement

(1) Direction of Structural Measures

Direction of structural measures is the improvement of water supply pipes to reduce water loss, mainly for asbestos cement and steel pipes.

(2) Necessary Length of Pipes to be improved in Bulgaria and Rough Cost Estimation

The existing asbestos cement pipes and the steel pipes are necessary to be replaced for reducing the loss of water from the pipes. For a reference, Table 6.3.1 shows the necessary length of pipes to be replaced together with rough cost estimation for all over Bulgaria. To estimate the cost, information of length of pipes with their composition of pipe diameter for different population size of towns were collected and analyzed. Based on this analysis and unit price of pipe, unit construction cost for water supply pipes are estimated, and applied for estimating the construction cost.

(3) Necessary Length of Pipes to be improved for Some Sample Municipalities in EABD and WABD and Rough Cost Estimation

In order to study feasibility for improving water supply pipe networks, based on the limited answers to the questionnaire to WSSs in EABD and WABD to JICA Study Team by August 2007, some sample municipalities are selected for further analysis. They are Haskovo, Yambol and Kardhali in EABD and Kyustendil in WABD.

The following table shows the estimated cost for the improvement of the water supply pipes in these 4 municipalities. Total estimated cost of improvement for these municipalities will be 325.84 million euros.

Economic feasibility has finally been conducted for each WSS as presented in Table 6.3.1 applying the same rule for the benefit calculation as shown in the next page as “Water Loss Reduction by the Improvement of Water Supply Networks of 4 Sample Municipalities”.




Improvement of Water Supply Networks of 4 Sample Municipalities

Asbestoscement Steel Cast iron PVC +

HDPE Other Total lengthInformat.NecessaryImprove.

(m) (m) (m) (m) (m) (m) (m)1 Haskovo Haskovo State EABD 98,697 461,171 156,429 627 3,702 621,929 12,6102 Yambol Yambol State EABD 79,235 136,745 59,450 5,962 12,246 214,403

3 Kardzhali KardzhaliState &Municp. EABD 64,847 231,858 24,786 0 21,301 22,549 300,494 166,000

4 Kyustendil KyustendilState &Municp. WABD 66,298 669,409 172,903 12,212 19,553 113,074 987,151

Total 309,077 1,499,183 413,568 12,212 47,443 151,571 2,123,977

Replace-mentLength of

Pipe(AS+ST)

Unit Cost Direct Cost (A)EngineeringCost (5% of

A)

Administration Cost (5 %

of A)

PhysicalContingency(10% of A)

Total Cost

(m) (EUR / m) (EUR) (EUR) (EUR) (EUR) (EUR)1 Haskovo Haskovo State EABD 617,600 160 98,816,000 4,940,800 4,940,800 9,881,600 118,579,2002 Yambol Yambol State EABD 196,195 160 31,391,200 1,569,560 1,569,560 3,139,120 37,669,440

3 Kardzhali KardzhaliState &Municp. EABD 256,644 150 38,542,437 1,927,122 1,927,122 3,854,244 46,250,924

4 Kyustendil KyustendilState &Municp. WABD 842,312 151 127,474,993 6,373,750 6,373,750 12,747,499 152,969,991

Total 1,912,751 622 296,224,629 14,811,231 14,811,231 29,622,463 355,469,555

Note: Estimated cost is without VAT.

Data Source:1) Answer to the questionnaires to the WSS Companies in EABD and WABD areas by the end of August 2007, which have been received by this Study.

Estimated Necessary Improvement of WS Pipes

Existing Pipes for Water Supply

Municipality OwnerWSS Co.No.RelatedBasin

District

Servedpopulat. by

WS

No. Municipality WSS Co. OwnerRelatedBasin

District

The following table shows possible reduction of water supply loss by the above improvement. In this calculation, per-capita water consumption is supposed to be 220 l/day/person in the future condition. By the improvement, about 22 million m3 per year of water can be saved in these 4 municipalities.

Water Loss Reduction by the Improvement of Water Supply Networks of 4 Sample

Municipalities

Remarks

CurrentSupplied Water

(m3/day) (m3/year) (m3/year) (m3/year) (m3/year) (m3/year)1 Haskovo Haskovo State EABD 98,697 21,713 7,925,369 15,850,738 8,805,966 7,044,773 10,320,0002 Yambol Yambol State EABD 79,235 17,432 6,362,571 12,725,141 7,069,523 5,655,618 14,432,000

3 Kardzhali KardzhaliState &Municp. EABD 64,847 14,266 5,207,214 10,414,428 5,785,793 4,628,635 5,148,000

4 Kyustendil KyustendilState &Municp. WABD 66,298 14,586 5,323,729 10,647,459 5,915,255 4,732,204 2,062,000

Total 309,077 67,997 24,818,883 49,637,766 27,576,537 22,061,229 31,962,000Note1) Per-capita water demand in the future is supposed to be 220 l/day.

2) Served population by watter supply in 2015 is supposed to be same as the current served population.

No. Municipality WSS Co. OwnerRelatedBasin

District

Servedpopulat. by

WS

Water Demand

NecessarySupplied

Water withimproved

physical loss(10%)

Difference ofNecessary

Supplied Water

NecessarySupplied

Water withcurrent

physical loss(50%)




6.3.2 Programme of Measures for Irrigation Facility Improvement

(1) Introduction

The agricultural lands cover about a half of the country and the agriculture is one of the fundamental sectors in the country. The stability of agricultural production will be the basis for sustainable development of the rural areas. The irrigation facilities are basic infrastructure for stable agricultural production. The country had developed about 1.2 million ha during the old order by 1980s, however, currently the potential irrigation area is about 500,000 ha, of which irrigation systems are owned by the government and managed by Irrigation Systems Co. (IS).

In 1980s the irrigation area covered over 1.0 million ha and used water resources, as much as 3.5 billion m³/year, but in the new order, the agricultural sectors has not rebuilt yet. The current utilized irrigation areas are estimated at a level of 20,000 ha to 30,000 ha with the water at 100 to 200 million m³/year.

The irrigation systems and facilities are deteriorated and reported having large water losses over 60-70% because of poor maintenance. The existing irrigation systems were designed only for the original scale of irrigation, but not for small scale or controlled irrigation. The current water loss is by far larger than the reported volume. The irrigation area and water are supposed to be increased in future and the existing irrigation systems should be improved in order to provide irrigation water properly to the demand areas and to reduce the loss in the system.

(2) Direction of Improvement

(a) Structural Measures

Improvement of irrigation facilities aims to provide irrigation area with the optimum water volume and to make efficient water use including reduction of water loss.

Basic concepts for improvement are as follows:

• The existing irrigation systems are deteriorated with high water loss over 60-70%, and need rehabilitation in order to utilize the systems.

• Although real water consumption is small, water abstraction seems by far larger due to water loss and poor intake facilities and distribution facilities (gate and canal).

• It will be necessary for the region to renovate the irrigation system considering the efficient water use based on the current and future demands of irrigation water.

• Irrigation improvement will be one of the key improvements for sustainable water use and also for the sustainable development of agriculture and regional development based on the efficient water abstraction and use.




(b) Non-structural measures

For water quantity management and improvement purposes necessary measures are as follows:

• To review and improve the current water use permissions to conduct optimum water intake and use, and also the water transfer to the other river basins,

• To conduct monitoring the volume at water intakes by installing measurement devices by water users for intake sides as well as Basin Directorate at key locations in the rivers,

• To improve the quality of data required for water quantity management, including collaboration with National Institute for Meteorology and Hydrology (NIMH) as well as other relevant institutes, and

• To establish a system for a good coordination among RBDs, MoAF and related municipalities for implementation of the proposed project.

(3) Objectives for Irrigation Water Improvement

The objectives for irrigation water improvement are:

• to use water resources efficiently, and

• to supply irrigation water in response to the demand by improving irrigation facilities and reducing a high level of loss in the irrigation systems.

(4) Management Organization

Irrigation System Co. (IS), which is 100% owned by the MoAF manages all the state owned facilities (water reservoirs, canals, pumping stations and compensating basins). The company has 21 regional branches, of which 12 branches are located in EABD/WABD. They are as follows:

• EABD: Sliven, Yambol, Stara Zagora, Haskovo, Plovdiv, Pazardijik, Sofia.

• WABD: Pernik, Dupnitsa, Gotse delchev and Sandanski.

The location of each irrigation branch is shown in Figures 6.3.1 and 6.3.2. The irrigation branches and proposed improvement area are 316,468.6 ha in EABD and 50,738.3 ha in WABD as shown in the following tables.




Irrigation Branches and Potential Areas in EABD

Irrigation Branch

Potential area (ha)

Area fit for irrigation (ha)

Number of Irrigation systems

1 Burgas 3,246.7 2,863.4 2 2 Haskovo 48,338.6 29,154.2 47 3 Pazardzhik 57,799.0 26,181.3 6 4 Plovdiv 106,116.3 72,041.0 15 5 Sliven 33,116.8 25,698.3 1 6 Sofia 3,901.3 3,901.3 1 7 Stara Zagora 38,515.6 36,004.7 6 8 Yambol 25,434.3 23,197.2 4

Sub total 316,468.6 219,041.4 82

Irrigation Branches and Potential Areas in WABD

Irrigation Branch

Potential area (ha)

Area fit for irrigation (ha)

Number of Irrigation systems

1 Dupnitsa 13,581.7 11,487.0 6

2 Gotse Delcev 8,201.0 5,950.8 3

3 Pernik 14,864.6 13,258.1 23

4 Sandanski 14,091.0 12,780.8 9 Sub Total 50,738.3 43,476.7 41

Some of the former state and cooperative property are managed and maintained by the established 74 Irrigation Associations registered in Bulgaria, 32 associations are located in WABD/EABD

The overall coordination and supervision of the management and maintenance is carried out by the Executive Agency of Irrigation and Drainage of the Ministry of Agriculture and Forestry. This agency carries out all activities related to planning, management and control of the irrigation and drainage systems throughout the country.

(5) Improvement of Existing Irrigation Systems in EABD and WABD

The existing systems are required to be improved with their facilities including construction of new intake structures, rehabilitation of intake structures, distribution structures, etc. The detailed data of facilities for improvement, the cost estimation are shown in Tables 6.3.2 and 6.3.3. The total costs estimated for the improvement are shown as follows:

EABD • A total of 8 irrigation branches composed of 82 irrigation systems with

total irrigation area at 316,468.6 ha • Total project cost: 230.7 million euros




WABD

• A total of 4 irrigation branches composed of 41 irrigation systems with total irrigation area at 50,738.3 ha

• Total project cost: 42.0 million euros

It should be noted that the total costs shown here are composed of construction cost, administration cost (5% of construction cost), engineering service cost (10% of construction cost) and physical contingency cost (10% of construction cost).

(6) Priority Irrigation System for Improvement

The irrigation systems are classified into three groups considering the assumed improvement of water use efficiency and also expected development effects, and the first group is selected as the priority group for early implementation. The priority irrigation systems are listed as follows:




First Group for Implementation

EABD: A total of 2 irrigation branches composed of 5 irrigation systems with total irrigation areas at 94,948.0 ha.

EABD Irrigation Branch Irrigation System

1. Provdiv Topolnitsa Stryama-Chirpan

2. Pazardzhik Topolnitsa Aleko pazardzhik Karabunar

WABD: A total of 4 irrigation branches composed of 22 irrigation systems with total irrigation areas at 17,730.6 ha.

WABD Irrigation Branch Irrigation System 1. Pernik Kjustendil composed of 18 small systems

2. Sandanski Sandanska Bistritsa Mendovo-Karvrakirovo Strumeshnitsa

3. Gotse Delcev Gotse Delchev

Total construction cost of the priority group is as follows:

EABD: 84 million euros WABD: 20 million euros

The total costs shown here are also composed of construction cost, administration cost (5% of construction cost), engineering service cost (10% of construction cost) and physical contingency cost (10% of construction cost).

Second Group for Implementation

EABD: A total of 5 branches composed of 7 irrigation systems with total irrigation areas at 106,030.0 ha

WABD: A total of 1 branch composed of 10 irrigation systems with total irrigation areas at 20,237.1 ha.

Total project costs:

EABD: 83.2 million euros

WABD: 14.4 million euros




Third Group for Implementation

EABD: A total of 8 irrigation branches composed of 70 irrigation systems with total irrigation areas at 115,490.6 ha.

WABD: A total of 4 branches composed of 9 irrigation systems with total irrigation areas at 12,770.6 ha.

Total project cost:

EABD: 63.1 million euros

WABD: 7.2 million euros

Implementation plan of the improvement measure for implementing the proposed improvement of irrigation systems the implementation plan are as follows:

Implementing agency: • Leading implementing agency shall be MoAF, and cooperating

organizations shall be composed of RBD and the related municipalities, considering effective water use and sustainable regional development.

• In order to improve the irrigation systems for promoting the sustainable regional development it is necessary for the implementing agency to conduct the study on required extension services and marketing systems for the region and also the analysis on the role of the reservoirs in the annual water use.

Implementation: • First group shall be improved in structural measures as a pilot project by

2015 and activities for water management and regional development shall be started.

• Second and Third groups shall be prepared for the implementation by 2015 and improved in structural measures by 2021 and activities for water management and regional development shall be started.




6.4 Preliminary Programme of Measures for Groundwater Management (Directions)

6.4.1 Introduction

In this sub-section, preliminary programme of measures for groundwater management is proposed in the sense of directions for improvement and management of the groundwater. Furthermore, some recommendations are also presented for the New Monitoring Plan for groundwater, which was formulated by MoEW and the RBDs in March 2007.

6.4.2 Directions for Groundwater Management (Some Recommendations)

(1) General Recommendations

Some general problems exist that hamper real work:

• The inter-institutional interaction and cooperation are not sufficient and efficient in some cases. This hampers effective work in the domain of the environment protection.

• Access to data is rather difficult and costly (e.g. the geological record office “Geofond” at MoEW).

• Young people are low motivated to be employed in Laboratories and Institutes.

Maybe the only positive example of free data access in Internet is “General Master Plans for Utilization of the Water Resources in Bulgaria”, 2000 available in web-page (http://www.bluelink.net/water/) prepared jointly by NGO “ECOSOUTHWEST” with assistance of MoEW and Institute of Water Problems at Bulgarian Academy of Sciences. Public accessibility of data was realized thanks to assistance of the Bluelink electronic network.

(a) General Recommendations To improve inter-institutional interaction and cooperation, to ameliorate data exchange, to set information networks where appropriate. To make easier access to available reports, data, publications, etc. This will facilitate competence development of the staff in RBDs, institutes, universities and private companies, and contribute to timely solving of pressing problems. To find ways for motivation of personnel and attracting of young people in RBDs. To find forms for proper education of young staff in RBDs – balance between Bulgarian traditions and new European practice. Involvement of retired specialists in some activities is desirable under appropriate form. Special attention should be paid to protect groundwater resources, control the protection of water supply wells and to work on abandonment for unused wells. Abandoned mine sites inventory and cleanup programme for investigation and remediation are necessary.




(b) Recommendations related to Providing Data for GW Models

Different groundwater related problems might arise, both regional and local.

Groundwater modeling is a powerful tool for solving a variety of groundwater problems concerning groundwater flow, resources and contamination. Data acquisition is important in initial phase for preceding modelling.

Before the proper application, the model should be calibrated. Different data are necessary both for calibration of the model and for forecasts based on GW modeling:

• Right GW abstraction volume for water supply wells, including its variability,

• Data on GWL drawdown both in observational and water supply wells,

• GWL in monitoring stations expressed in altitudes a.s.l. Exact altitude of the measuring (reference) point is necessary,

• Water stage in rivers (expressed in altitudes a.s.l.),

• Spring discharge (if applicable), along with its inherent variability,

• River discharge, especially during low flows, and

• GW quality parameters.

To expedite preparatory work for the model, many data should be obtained. Data that are not registered on time are lost, and hence correct and comprehensive documentation are necessary.

In general, good documentation concerning different groundwater use aspects is necessary. If possible, different databases should be made.

(2) Specific Recommendations for EABD Main ore mining sites are concentrated in EABD. There are old tailings that present threat to ecological safety.

Database and GIS-map of old pollutions, especially tailings, is necessary. Abandoned mine sites inventory and cleanup programme for remediation are especially important for EABD. There are cases of low quality rehabilitation of mining areas. An appropriate cleanup programme will improve water quality and enhance public safety.

The problem with arsenic in drinking waters in Poibrene village is not yet solved. It is situated downstream from mining area; pollution from old tailing may occur from that point. It is a hot spot problem and necessary to assist the WSS in solving this problem.

To apply good agricultural practices to reduce nitrate content in the region of Stara Zagora.

To plan regional model of the groundwater flow in the region of Yambol-Elhovo area.

(3) Specific Recommendations for WABD To pay special attention to quantitative monitoring of Blagoevgrad GWB – “At risk”.




Groundwater research and modeling should be planned to re-assess groundwater resources of this groundwater body.

To use existing data on chemical composition from reports (for assessment of specific natural GW quality in mountain regions impacted by ore mineralization – for reference) – for the Upper Struma region. Establishment of database is necessary.

To control carefully groundwater abstractions in the region of the winter resort Bansko.

6.4.3 Some Recommendations for the New Monitoring Plan

(1) New Groundwater Monitoring Plans for River Basin Managements

The New Groundwater Monitoring Plans for River Basin Managements have been developed in implementation of the requirements of the WFD. The number of monitoring sites to be reported in EU is presented in the Table for different River Basins.

Number of Monitoring Sites from the New Monitoring Programmes

Monitoring network EABD WABD Danube BD BSBD

Surveillance 38 33 49 66 Operational 12 - 21 37 Quantitative 41 34 86 63

Quantitative network is planned most usually with frequency of four, sometimes 12 times per year, and encompasses monitoring of the next parameters:

• Groundwater levels in boreholes or wells,

• Spring flows, and

• Discharge from artesian wells and drains.

There are cases of multiple uses of monitoring sites for different networks.

Operational monitoring is planned for all groundwater bodies “At risk” along with groundwater bodies “At risk” with low confidence in the risk assessment, for which additional information is necessary (see table below).




GWBs at Risk and Operational Monitoring

Number of GWBs EABD WABD Danube BD BSBD ‘At risk’ 4 - 21 3 ‘At risk’ with low confidence in the risk assessment 3 - - 7

Total ‘At risk’ 7 - 21 10 With operational monitoring planned 7 - 21 10

No groundwater bodies “At risk” have been identified in WABD. On the one hand, there are only sparse monitoring data about pollutants in groundwater, and the pressure is lower compared to the other river basins. As a result, no operational monitoring has been planned up to now in WABD.

RBDs report almost total coverage of GWBs with GW monitoring networks. Because of their importance for national or regional development, large regional groundwater systems have received a higher priority than local-scale systems. Networks do not cover only GWBs with local importance and low pressure. They are usually difficult of access and with low population density.

New Groundwater Monitoring Plans are presented on Figures 6.4.1 and 6.4.2.

The proposed monitoring frequencies for surveillance monitoring are usually four times yearly for the basic physico-chemical indicators, and rarely for specific pollutants. This monitoring has an intention to conduct only one year within the operation of the River Basin Plan. For operational monitoring, they are usually one to four times yearly for the specific indicators, which present a real threat. Many of sampling points from surveillance and operative monitoring refer to the groundwater for drinking purpose.

(2) Recommendations for Improvement of the Groundwater Monitoring

(a) Evaluation of the Proposed New Monitoring Programmes

The proposed groundwater monitoring programmes by EABD and WABD are very ambitious. Its overview shows some weaknesses and obstacles, some of them are foreseen by the RBDs. The difficulties marked by RBDs are as follows:

• Possible cooperation with NIMH and WSSs has no legal basis – no agreements signed between MoEW and NIMH and WSSs.

• Laboratories have low human resource to respond to increasing tasks due to insufficient staff. Several vacancies are in laboratories in Blagoevgrad and Sofia.

In our opinion, additional problems are:

• Technical infrastructure for GW quantity measurements is lacking,

• Need for trained technical staff, and

• Need of hydrogeological work that requires involvement of experienced staff.




The staff of the RBDs has made preliminary agreement of the owners of private wells concerning access for the monitoring purposes. Later clear arrangements should be made with them.

At present, the proposed groundwater monitoring programmes do not fully correspond to the existing capacity of RBDs. Here general recommendations are presented, which are related to the improvement of GW monitoring.

(b) General Recommendations

• RBDs are institutions engaged in GW monitoring. To fulfill this task, capacity building is the most important prerequisite. Monitoring requires knowledge and experience. There is a need of experienced hydrogeologists, dealing with groundwater issues, involved in planning and implementation of GW monitoring. On the other hand, technical staff is necessary, which should be well trained.

• Analysis of institutional setting is necessary. RBDs are institutions having the responsibility and mandates for groundwater monitoring. Possible involvement of other institutions (NIMH, WSSs or other) through delegated tasks to them should be considered. Roles and administrative responsibilities should be cleared.

• To furnish GW monitoring handbook (for quantitative monitoring) that documents procedures, which must be followed to ensure good quality and integrity of the data collected.

(c) Some Practical Recommendations

• Gradual growth of the monitoring network from low profile to the right level of groundwater monitoring, always adjusted to the needs.

• To begin with small number of points.

• To carefully plan tasks.

• To provide for high standard and full documentation concerning implementation of the monitoring programme.

Important aspects of GW monitoring are presented below. Groundwater monitoring programmes should be developed based on inventory of data needs and specification of the objectives. Here some of the possible objectives are presented:

• Characterization of the groundwater system(s),

• Identification of possible trends in relation to groundwater use,

• Estimation of the potential for further groundwater development,

• Provision of historical and reference values for detailed investigations,

• Meeting the requirements of the WFD, and

• Early warning system for GW related problems.




GW monitoring programmes have been developed taking into account specific data needs and are based on conceptual model for HG systems. The data needs are often related to possible or identified GW related problems. Evidently, additional work is necessary.

• Need of additional preparatory work

• List of (main) stakeholders.

• Inventory of data needs - what data for what needs, for what stakeholders.

• To set priorities of data needs.

• To set priorities of monitoring points.

• Inventory of available wells with compiled fact sheets (information passports/sheets).

• Need of thorough hydrogeological work

• Preparation of conceptual model for HG systems. To a large extent, the conceptual model represents a statement by the professional hydrogeologist on how the groundwater system being studied “works”.

• Analysis of the available data for GW quantity and quality.

• Synthetic representation of the above mentioned aspects (maps, cross-sections, tables, graphs, problem statement).

• Preparation of options for GW monitoring. Good practice says that groundwater monitoring programmes should be adopted based on considering and weighting different options.

This work may be done in parallel with implementation of the first stage of the monitoring programme.

(d) Recommendations for Three Specific Cases

• For unconfined aquifers that are subject to diffuse pollution from the land surface, a reference monitoring point should exist within non-impacted zones (i.e. forests, protected areas) for comparative assessments.

• To prioritize the monitoring points, it is worthwhile to assess whether the measured value is a limiting factor for GW management or not.

• For alluvial aquifers along rivers, GW levels are usually close to the water stage in the river. In this case, an option of complex monitoring including surface and GW has to be considered. High accuracy of topographic measurements is necessary.

Documentation of groundwater monitoring is an important aspect. Examples of standard forms may be found in Annex E (Guideline, 2006), and are enumerated below. A proper monitoring programme should encompass:




• A monitoring handbook that documents procedures which must be followed to ensure good quality and integrity of the data collected,

• A monitoring station file of each well that contains all important information, and

• A field report form sheet that must be filled out upon arrival at the site and contains all relevant information about the fieldwork conducted.

(e) Conclusion

Establishing of appropriate GW monitoring network is a gradual and iterative process. Good idea is to apply a phased start of the GW monitoring programme. Such approach will allow for more gradual investments and means prioritizing monitoring efforts.

Our proposal is to prepare GW monitoring programme for the period up to 1.VII.2008, and to continue work for the next period. Much preparatory work should be done to propose a good and feasible monitoring programme.

The design of GW monitoring starts with defining of objectives. In our opinion, the main objective should be: “Groundwater monitoring integrated in water resources management and environmental protection”. That is why it is important to know specific data needs. State of the art presumes the design of the GW monitoring network to be based on conceptual model of the hydrogeological system. On the other hand, the monitoring programme has to be feasible. Different examples of approaches used in designing GW monitoring in Europe may be useful.

(f) General Recommendation for the New Groundwater Monitoring Plan

• To prioritise monitoring efforts based on specific data needs.

• To reconsider feasibility of the plans.

• To revise fact sheets of sites in respect of their long-term use in the networks.

• To reconsider involvement of other institutions through delegated tasks to them.

(g) Some Recommendations for the New Groundwater Monitoring Plans of EABD and WABD:

• To reconsider the new plan for quantitative monitoring – who will measure and data flow.

• To pay special attention to quantitative monitoring of Blagoevgrad GWB - “At risk”.

• To use existing data on chemical composition from reports (for assessment of specific natural GW quality in mountain regions impacted by ore mineralization – for reference) – for Upper Struma region, for example.

• Special attention to the region of the winter resort Bansko (WABD) and related impacts.




6.5 River Management

6.5.1 Introduction

There are non-pollution pressures such as water abstraction, water flow regulation and morphological changes have a major impact on water body quality. These pressures are often caused by improper human activities, and should be reduced by the proper river management. Also there are pressures from flood disasters, of which pressures and impacts should be assessed and preventive measures should be prepared in order to reduce the risks of flood disasters.

As for the river management, there are many agencies and organizations along the river and they have been conducting the management activities ad hoc manners within their responsibilities and authorities, without considering about the effects to the upper and lower reaches from river engineering aspects.

In the country the river course is owned partly by the government and partly by municipalities, MoAF and others including private sectors. Accordingly the responsibility and authority for management of the river reach and river facilities are divided into many segments and facilities due to their ownerships of them. Figure 6.5.1 shows the ownership and maintenance responsibility of dykes in Bulgaria. The River Basin Directorates are difficult to control the improper activities along rivers to reduce the adverse impacts because of their lacking responsibilities and authorities in managing the river course and morphology. Improvement of river management is to strengthen the RBD to conduct a better management of the river basin. For river basin management purposes it is necessary for the RBD to be a dominant managing agency for the river basin from technical aspects.

6.5.2 River Morphology Management

In the study area the river morphology is the product of water use and the other economic activities. The rivers are not so intensively used, though there are dams for power generation, intakes for irrigations and dikes for flood protection. However, major problems caused by human activities are the intensive and extensive sand and gravel extractions in and along rivers, which are affecting the river courses and river flows, by causing instability of river courses and eroding of river beds and banks, also scoring the foundation of structures and flood dykes.

There are identified many improper activities as well as the sand and gravel extraction activities, development works and solid waste dumping into rivers. In order to reduce pressures and impacts caused by human activities, the direction of required programme of measures for river management is proposed as follows:

• To regulate sand/gravel extraction more strictly, so that the river channel and surrounding flood plain areas have not unstable conditions,

• To control any illegal activities or improper activities along the river, including solid waste dumping and land development,




• To conduct a study on “ River Maintenance Plan for Floods Control and Sediment Yield ” for the basis of prevention of flood damages and control sand and gravel extraction, and

• To conduct study on pressures and impacts caused by priority substances, heavy metals and closed mines to protect people from the possible hazard caused by toxic materials.

6.5.3 Floods and Prevention Measures

(1) Responsible Organization

The new European Flood Directive 2007/60/EC on the assessment and management of the flood risk has been in force from November 2007 for all members of the EU.

The government enacted legislation “Disaster Protection Act” against natural disasters in response to the critical situation caused by the floods of 2005, and created “the Ministry of State Policy for Disasters and Accidents (MoSPDA).

The Minister develops, coordinates, and supervises the implementation of the state policy for prevention of disasters and accidents, and also the Minister manages the implementation of the state policy of taking control of and recovering from the impact of disasters and accidents.

As for the emergency measures MoSPDA as the successor of the Civil Defense shall organize and discharge on the basis of regional plans for performance of rescue and emergency repair and recovery works. Ministries, district governor’s offices, Municipalities and Basin Directorates have already had their emergency units for emergency responses. However, preventive measures should be prepared urgently.

(2) Direction of Required Measures

Preparedness against floods is very important to reduce damages caused by floods. The prevention measures are also composed of structural and non-structural measures. There is numerous flood protection dykes constructed by MoAF and municipalities etc., but still no flood warning system has not established yet, though some international studies are on going in EABD.

For establish flood warning systems directions of the required measures to be conducted are as follows:

• It is necessary for MoEW, EABD and WABD to conduct a basic technical study for formulation of flood disaster prevention plan as the river basin managing organization.

• It is necessary for MoEW, EABD and WABD to conduct technical assist to MoSPDA and municipalities to protect people in flood hazard areas from flood damages.

• Based on the basic study it is necessary for EABD and WABD to install automatic rainfall stations and river stages required for implementation of the flood prevention plans. In establishment of observation networks it is better to collaborate with NIMH.




• Based on the basic study it is necessary for MoEW, EABD and WABD to assess the existing flood protection facilities and to prepare improvement plan of them.

(3) Prevention Measures against Floods

For disaster prevention measures it is necessary for EABD and WABD to conduct:

• To establish warning systems for floods and incidental pollutions, and

• To assess the existing flood prevention facilities and conduct remedial works if necessary. There are many existing flood prevention dykes required remedial works.

For formulation of flood warning systems basic information is as follows:

• Identification of flood areas in the past,

• Preparation of flood maps based on the past flood events,

• Analysis of the hydrological data, which caused floods in the past,

• Assumption of possible flood areas by the design flood events,

• Establishment of flood warning system composed of observation systems and information system among related organizations, municipalities and communities, EABD, WABD, MoEW and MoSPDA, and

• Enhancement of public awareness for disasters caused by flood events.

(4) Measure against Incidental Pollution

There may be various possible risk areas from incidental pollution. As well as for floods an early warning for risk areas of incidental (or accidental) pollution is required. For formulation of warning system basic measures required are as follows:

• Identification of possible risks caused by incidental pollutions,

• Identification of risk areas from incidental pollution,

• Assessment of risk areas caused by incidental pollution sources, including tailing dams, mining, industry etc,

• Analysis of the incidental pollution events, which caused incidental pollutions in the past, and

• Establishment of an early warning system composed of observation or inspection systems and information system among communities, municipalities, RBDs, MoEW and MoSPDA.

6.5.4 Future Studies Related to the River Basin Management to be conducted

It is recommended that the RBD conduct further basic studies for the river basin management as follows:

The study on “River Management Plan” for the basis for prevention of flood damages and controlling sand and gravel extraction as well as improvement of environmental




status, including river structures like dykes, weirs and fish passages, of water bodies from the view point of river morphology. • The study on pressures and impacts from discharges or priority substances, which are

33 harmful substances defined by the EU-WFD, and heavy metals, and also closed mines in the basin necessary to protect people from possible hazard caused by discharge of toxic substances.

In addition, the present study is of the viewpoint of basin management, thus water resources development aspect has not been included. Furthermore, the data related to water resources used in the present study is limited due to constraints on availability of the data. It is also recommended that the study shall be conducted on water resources development and river flow regulation, which include the following items:

• The detailed and/or localized regime of the river flow, including the more detailed and/or localized water transfer, water use, and environmental flow.

• The detailed assessment of the needs of additional hydro-technical facilities to be constructed as well as the restarting of construction of the suspended ones to regulate water flow for more efficient use of water resources, as a part of the integrated water management in Bulgaria and to meet the challenges of global climate change.




6.6 Result of Water Quantity Simulation

6.6.1 Water Resources Potential

In Bulgaria, almost all of the observed water quantities at hydrometric stations are under disturbed condition. The measured disturbed water quantities have been traditionally used for the statistical analysis for estimating available water resources with different probability, although it may be difficult to know quasi-natural water resources.

In the present study, probable water quantities are estimated based on the calibrated rainfall-runoff model. Firstly, quasi-natural water quantities are estimated under the precipitation with different probability. Secondly, by assuming the reservoir operation pattern, potential flows under influence of significant reservoirs are estimated. The estimated water quantities can be regarded as water resources potential, especially for surface water.

For setting the meteorological conditions for the rainfall-runoff model, the following principles are applied.

• Precipitation amount in continues 2-year should be considered, because 2-year total precipitation amount seems to be related to water quantity more than one in a single year.

• Adjusting total precipitation amount uses precipitation pattern in the representative year.

• Temperature pattern in the representative year is used.

The results of the statistical analysis for precipitation in EABD and WABD show that year 2004 is almost average year in terms of precipitation amount. Therefore, in the present study, year 2004 is selected as the representative year for considering water resources.

Continuous 2-year simulations have been conducted using the calibrated NAM model, which is rainfall runoff module of MIKE11 (see Chapter 4). Initial condition for the simulation has been set as same as the condition at the beginning of year 2004 for the existing condition. The simulated result shows that the runoff volume in the 2nd year is almost always smaller than the one in the 1st year, even though the precipitation amount in the 2nd year is larger. This seems to be because of the influence of smaller precipitation amount in summer time in the 1st year. In the present study, the result in the 2nd year is utilized for further analysis.

The results have been imported to the Simple Model. Then, quasi-natural water quantities for x% probability of exceedence are estimated. The Simple Model_ver_Potential is utilized for estimating potential flow with significant reservoirs. For estimating potential flows with influence of significant reservoirs, the followings are assumed.




• Outflow volume

• Annual Total Outflow = Annual Total Inflow is assumed.

• Same outflow pattern as the one in the representative year (2004) with adjustment to attain “Annual Total Outflow = Annual Total Inflow” is applied.

• Transfer by feeder channels

• Average transfer rate during 2001-2005 is applied.

The estimated probable water quantities at the downstream end (country border) of each river basin for quasi-natural flow and potential flow are shown below.

Probable Water Quantity at the Downstream End (Country Border) of Each River Basin

Struma Mesta Dospat Arda Biala Tundzha Maritsa

Average Year (2004)

Quasi- Natural

Flow (NF) 66.79 34.22 6.82 63.30 2.64 31.79 103.66

Potential Flow (PF) 65.35 30.58 2.40 50.09 2.64 22.50 113.85

Probability of Exceedence

75%

Quasi- Natural

Flow (NF) 51.62 23.65 5.06 47.87 0.83 28.34 80.04



90%

Quasi- Natural

Flow (NF) 39.43 20.01 3.88 39.20 0.55 19.62 61.98



95%

Quasi- Natural

Flow (NF) 31.04 13.25 2.99 33.61 0.43 14.66 51.68


Unit: m3/s

The year with 95% of probability of exceedence (equivalent to drought with 1/20) provides almost half water quantity compared to one in the average year.

The estimated probable water quantities are stored in the Simple model_ver_Permit and the Simple model_ver_Demand. Using those tools, one can check water quantity including monthly variation at several different points in the river basin.




6.6.2 Water Resources Potential and Demand Analysis

Balance of water resources potential and water demand under several scenarios are analyzed. Because condition of irrigation water use gives most significant impact on water balance, several scenarios on irrigation water use are analyzed under the following situations.

• Drinking Water Demand

• To keep current surface water dependency

• Unit water use = 220 litter/day /person

• Loss rate =50%

• Industrial Water Demand

• No change from current condition (Increase by GDP growth, but recycling rate will also increase)

• Irrigation Water Demand

• To keep current unit water demand for each irrigation branch

• For current loss rate, the value showed by Irrigation Systems Ltd. is used.

The Simple Model is used for the analysis. Examples of the simulated results are shown in Figures 6.6.1 to 6.6.5. Based on the simulated results, the followings are discussed for each river basin.

(1) The Struma River Basin

• Ratio of water demand against potential water resource is high in upstream area and low in downstream area. It is not spatially well balanced. At upstream of the confluence with the Dzherman River, water resources potential is quite limited compared to water demand. Demand control could be required for drinking, industrial and irrigation water.

• On the other hand, from downstream reach of the confluence with the Dzherman River, water resources potential is rather large compared to water demand.

• Under current loss rate (48 to 74%) and current unit water demand for irrigation water, about 40% of potential irrigation area can be irrigated with almost no water flow at the confluence with the Dzherman River in the Struma River when precipitation amount is 75% probability of exceedence. When we consider river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 40% of the potential area.

• Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with almost no water flow at the confluence with the Dzherman River in the Struma River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 100% of the potential area.




(2) The Mesta River Basin

• Water resources potential is large enough compared to water demand.

• Ratio of water demand against potential water resource is large in downstream area and small in upstream area in general.

• Under current loss rate (64%) and current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with about 20% of potential water flow being kept at the reach near Gotche Dolchev to the downstream end of the Mesta River when precipitation amount is 75% probability of exceedence.

• Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 100% of potential irrigation area can be irrigated with about 50% of potential water flow being kept at the reach near Gotche Dolchev to the downstream end of the Mesta River when precipitation amount is 75% probability of exceedence.

• However, water resources balance at local level should be further investigated using more detailed data. Especially, it should be careful on effect of water abstraction for local hydro power plant.

(3) The Arda River Basin

• Water resources potential is generally large enough against water demand along main channel of the Arda River.

• Under current loss rate (73%) and current unit water demand for irrigation water, about 100% of potential irrigation area can be irrigated without significant impact on main channel of the Arda River.

• However, water resources balance at local level should be further investigated using more detailed data. Generally, annual water resources seem to be enough. To utilize water resources more in drought season, local reservoir or pond could be useful.

(4) The Tundzha River Basin

• Ratio of water demand against potential water resource is large in upstream area and small in downstream area. It is not spatially well balanced. This is mainly because of decrease of water resources potential in the upstream area due to water transfer from the Koprinka Reservoir to the Maritsa River Basin.

• Reduction of water resources potential at the area between the Koprinka Reservoir and the Zhrebchebo Reservoir can be constraints against recovering of irrigation activity in the area. If the current water transfer will be kept, demand control may be required in this area.

• Under current loss rate (61-84%) and current unit water demand for irrigation water, about 35% of potential irrigation area can be irrigated with almost no water flow at the reach from the Zhrebchebo Reservoir to Yambol in the Tundzha River when precipitation amount is 75% probability of exceedence. When we consider




river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 35% of the potential area.

• In the current situation, almost all of water can be abstracted at the reach from the Zhrebchebo Reservoir to Yambol according to the permission issued to irrigation purpose．On the other hand, actually irrigated area in this area (Mainly Sliven branch) is less than 10% according to the record provided by Irrigation Systems Ltd. Water abstraction in this area is obviously too much compared to actual demand. Proper control of water abstraction based on actual demand is necessary.

• Under the condition that loss rate is 30% with current unit water demand for irrigation water, almost 70% of potential irrigation area can be irrigated with almost no water flow at the reach from the Zhrebchebo Reservoir to Yambol in the Tundzha River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 70% of the potential area.

(5) The Maritsa River Basin

• Water demand against potential water resource is spatially rather well balanced from upstream to downstream of the Maritsa River.

• Without water transfer from other basins, water resources potential against water demand would be very small.

• Under current loss rate (60 to 74%) and current unit water demand for irrigation water, about 15% of potential irrigation area can be irrigated with almost no water flow in the Maritsa River when precipitation amount is 75% probability of exceedence. When we consider river environmental condition, at least minimum water should be kept. In this case, possible irrigation area is less than 15% of the potential area.

• Under the condition that loss rate is 30% with current unit water demand for irrigation water, about 30% of potential irrigation area can be irrigated with almost no water flow in the Maritsa River when precipitation amount is 75% probability of exceedence. Considering necessity of minimum environmental flow, possible irrigation area is less than 30% of the potential area.




6.7 Result of Water Quality Simulation

The calibrated MIKE11 water quality models, which is described in Chapter 3, have been used for simulation of the scenarios:

• Present situation (corresponds to the calibration simulation) • Near Future • Near Future with 10% loss • High Priority Future • High and Medium Priority Future

For all of the scenarios the hydrological and hydraulic condition from year 2004 has been used as was done for the calibration. The time axis on all plots are therefore showing dates in 2004 although the represent different future years / scenarios.

The results are illustrated with plan plots of the rivers with colours corresponding to the Bulgarian Water Quality Classes with respect to BOD concentrations show in the following figure. Furthermore, the BOD concentration has been shown for selected station (cross section) in the river systems in Figures 6.7.1 to 6.7.10.

18.00 <

<

7.00 18.00.50 7.003

2.00 503. 2.00

Color Legend for Plan plot of Concentration of Organic Pollutants (BOD) in the Rivers (mg/l)




6.8 Summary of the Programmes of Measures

6.8.1 Introduction

The proposed programmes of measures are composed of structural measures and non-structural measures, and the non-structural measures are including proposed basic studies for the management of morphology in river basin.

The Structural measures will require feasibility studies and detailed designs for their implementation, and non-structural measures will require necessary arrangement for the execution.

6.8.2 Proposed Structural Measures

The proposed structural measures are composed of measures as follows:

(1) Water Quality Improvement and Management

• Construction of new WWTPs.

• Renovation of existing WWTPs, and

• Renovation and expansion of sewer pipe networks.

(2) Water Quantity Improvement and Management

• Improvement and replacement of water supply pipe networks, and

• Improvement of irrigation systems with intake, water, transfer and distribution facilities.

The more detailed information is shown in Table 6.8.1.

6.8.3 Proposed Non Structural Measures

The proposed non-structural measures are summarized as follows:

(1) Measures for Water Quality Improvement and Management

• Regulation for controlling and reducing pollution loads from industries and big livestock farms by strengthening of regulation.

• Regulation for improving septic tanks to sealed type or for introducing individual treatment and periodical sludge extraction and treatment. Financial support system to people for improvement and installation of sealed type septic tanks and individual treatment is to be considered.

• Regulation for controlling and reducing pollution load from the agricultural lands by changing agricultural methods and technology to reduce chemical fertilizer and pesticide, and

• Establishment of a system to conduct a good cooperation with municipalities for monitoring and river basin management activities.




(2) Measures for Water Quantity Improvement and Management

• Regulation for reviewing and improving the current water use permissions to conduct optimum water intake and use, and also the water transfer to other river basin.

• Regulation for conducting monitoring the water volume at water intakes by installing measurement devices by water users for intake sides as well as Basin Directorate at key locations in the rivers.

• Regulation for controlling and improving the quality of data required for water quantity management, and

• Regulation for establishing a system for a good coordination among RBDs, MoAF and related municipalities for river basin management and for implementation of the proposed project.

(3) Measures for River Morphology Improvement and Management To set up a new regulation for controlling and regulating sand/gravel extraction more strictly in order to protect the river channel and surrounding flood plain areas from unstable conditions.

• Regulation for controlling any illegal activities or improper activities along the river, including solid waste dumping and land development, and

• Regulation for establishing a good coordination system between the RBDs and the relating agencies/organizations responsible for management of forest areas, national parks and protection areas in the basin in order to cooperate in the RBM activities, particularly in the upstream of the river basin.

(4) Basic Study for River Basin Management and Flood Disaster Prevention

• To conduct a study on “River Management Plan” for the basis for prevention of flood damages and controlling sand and gravel extraction as well as improvement of environmental status of water bodies from the view point of river morphology,

• To conduct a basic study on pressures and impacts from discharges of priority substances and heavy metals, and also on pressures and impacts from the existing and closed mines in the basin for protect people from possible hazard caused by discharge of toxic substances, and

• To conduct a study on water resources development and river flow regulation, which includes the following items:

• The detailed and/or localized regime of the river flow, including the more detailed and/or localized water transfer, water use, and environmental flow.

• The detailed assessment of the needs of additional hydro-technical facilities to be constructed as well as the restarting of construction of the suspended ones to regulate water flow for more efficient use of water resources, as a part of the integrated water management in Bulgaria and to meet the challenges of global climate change.




CHAPTER 6

6.1

Main Report

Chapter 6

Tables

6.2



Table 6.2.1 Major Industries in EABD: Directly Discharging Wastewater into the Rivers or Water Bodies

Sett

lem

ent

Mun

icip

ality

1. M

arits

a R

iver

Bas

in1

NEO

HIM

JSC

oC

hem

ical

indu

stry

Mar

itsa

Dim

itrov

grad

Dim

itrov

grad

Mar

itsa

river

MA

_M2

0.25

234

.427

3238

10.0

7947

10.

7055

9

2Tr

akya

Pap

er JS

Co

Prod

uctio

n of

pap

er, c

orru

gate

d ca

rdbo

ard

and

pack

ings

Mar

itsa

Paza

rdzh

ikPa

zard

zhik

Pish

man

ska

river

MA

_M5

0.07

725

5989

75.

011

979

0.20

479

3G

orub

sо L

aki -

Orc

-dre

ssin

g w

ith ta

iling

pon

d "L

aki-2

-com

plex

"M

inin

gM

arits

aLa

kiLa

kiD

zhur

ovsk

a riv

erM

A_Y

UG

0.06

725

5269

71.

123

190.

013

4K

amen

itsa

JSC

o, P

lovd

iv, b

rew

ery

Has

kovo

Bre

wer

yM

arits

aH

asko

voH

asko

vogu

llyM

A_H

AR

10.

018

9051

088

10.0

5676

5.00

283

5B

iove

t JSC

oPr

oduc

tion

of v

eter

inar

y pr

oduc

tsM

arits

aPe

shte

raPe

shte

raSt

ara

reka

rive

rM

A_S

TA2

0.02

080

.13

5054

06

KC

M-S

.A.,

Plov

div

met

allu

rgy

Mar

itsa

land

, mun

icip

ality

K


3 0 8

uKuk

len

Che

pela

rska

rive

rM

A_M

40.

097

1545

989

1.1

3373

1.95

597

7TT

P "M

arits

a 3"

Dim

itrov

grad

Elec

tric

pow

er -

prod

uctio

nM

arits

aD

imitr

ovgr

adD

imitr

ovgr

adM

arits

a riv

erM

A_M

20.

032

2530

764

1.0

1203

0.20

241

8B

imak

JSC

o/C

helo

pech

Mai

ning

EA

DC

uppe

r ore

dre

ssin

gM

arits

av.

Che

lope

chC

helo

pech

Voz

odel

/Che

lope

shka

/riv

er;

MA

_TO

P30.

025

3426

764

27.3

2131

32.

0015

59

Asa

rel-M

edet

JSC

oEx

tract

ion

and

proc

essi

ng o

f cop

per o

reM

arits

aPa

nagy

uris

hte

Pana

gyur

isht

eY

ana

Luda

rive

rM

A_L

UD

20.

030

2523

950

1.1

1054

0.20

192

10El

it 95

Ltd

, vD

albo

k iz

vor,

Dai

ryD

airy

Mar

itsa

v.D

albo

k iz

vor

Parv

omay

Topo

lnits

a riv

erM

A_M

30.

000

1438

2099

510

.014

62.

002

11B

elov

o - P

aper

Mill

JSC

- B

elov

oPr

oduc

tion

of p

aper

, cor

ruga

ted

card

boar

d an

dpa

ckin

gsM

arits

aB

elov

oB

elov

oM

arits

a riv

erM

A_M

60.

014

33.0

7614

488

12El

atsi

te -

Med

JSC

oC

uppe

r ore

dre

ssin

gM

arits

av.

Mirk

ovo

Sofia

Mal

ka re

ka ri

ver

MA

_TO

P30.

030

1514

250

14.0

1333

80.

2019

013

Kon

ex T

iva

Ltd,

v.O

rizov

oPr

oces

sing

of v

eget

able

sM

arits

av.

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ovo

Bra

tya

Das

kalo

viSu

ho d

ere

river

MA

_M3

0.00

650

9617

10.0

1923

.33

5.0

962

14G

orub

sо L

aki -

Min

ing

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zhba

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inin

gM

arits

aLa

kiLa

kiD

zhur

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erM

A_Y

UG

0.01

225

9463

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0.

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grya

JSC

o, P

lovd

iv F

UN

GIC

IDES

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SEC

TIC

IDES

, HER

BIC

IDES

Mar

itsa

land

, mun

icip

ality

K

9 9 9

0 026

uKuk

len

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pela

rska

rive

rM

A_M

40.

012

2591

45

16Pa

per F

acto

ry A

D, S

tam

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ski

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r pro

duct

sM

arits

aSt

ambo

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ambo

liysk

iM

arits

a riv

erM

A_M

40.

029

9.2

8414

17V

ulka

n JS

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rubb

er /

tyre

retre

adin

gM

arits

aD

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adD

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A_M

20.

010

2578

7510

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500.

518

618

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om -

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e-pr

oduc

tion

Mar

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Bre

zovo

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ovet

ska

river

MA

_M3

0.00

020

5062

3234

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41.

119

Kris

tal J

SCo

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ss w

are

- cry

stal

Mar

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ingr

adV

elin

grad

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pins

ka ri

ver

MA

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10.

006

3058

842.

855

12.

3920

Min

es"T

raya

novo

seve

r" a

nd "T

raya

novo

1"

Extra

ctio

n of

bro

wn

coal

Mar

itsa

v.Tr

oyan

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nevo

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char

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river

MA

_SA

Z10.

004

2532

725.

065

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m -

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rgi B

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vski

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TD -

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div

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ry te

chni

cs, a

erop

lane

sM

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av.

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f Ign

atie

voM

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asac

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40.

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1530

832.

139

95.

9522

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raya

novo

3",

v.M

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karo

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alM

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av.

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nika

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abov

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kolit

sa ri

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MA

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Z10.

003

2526

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063

51.

1123

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i Obo

rot 2

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ng o

f mea

tM

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aV

elin

grad

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ingr

adC

hepi

nska

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rM

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PI1

0.00

165

2600

0.4

162.

0080

24R

emot

ex R

adne

vo E

AD

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l out

put

Mar

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a riv

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A_B

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003

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1125

SKF

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Bul

garia

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nare

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lovo

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re /g

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0.00

325

2502

1.1

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hugu

nole

ene

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st J

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cast

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Mar

itsa

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omay

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river

MA

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0.00

415

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0.2

27B

DZ

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ver

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0.00

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760.

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sa O

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of p

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and

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tene

tsK

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nets

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itsa

river

MA

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0.00

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993

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0.20

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001

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al P

mg/

lN

AM

Cat

ch.

BO

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/yea

rkg

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mg/

lT

otal

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000

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000

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Tot

al P r

Tabl

e 6.

2.1

Maj

or In

dust

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in E

AB

D: D

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tly D

isch

argi

ng W

aste

wat

er in

to th

e R

iver

s or W

ater

Bod

ies (

1/2)



6-51

JICA CTI Engineering International Co., Ltd.

Sett

lem

ent

Mun

icip

ality

41B

or C

hvor

- D

.Min

ev, v

.Dal

bok

izvo

r, D

airy

Dai

ryM

arits

av.

Dal

bok

izvo

rPa

rvam

ayTo

poln

itsa

river

MA

_M3

0.00

028

042

Bul

garia

n R

ose

JSC

o, K

arlo

voPa

rfum

e / r

ose

oil

Mar

itsa

v.H

risto

Dan

ovK

arlo

voB

elya

ta ri

ver

MA

_STR

20.

000

5043

Opt

ikoe

lekt

ron

SPLT

DFa

ctor

y fo

r opi

tcs

Mar

itsa

Pana

gyur

isht

ePa

nagy

uris

hte

Yan

a Lu

da ri

ver

MA

_LU

D2

0.00

115

44Y

ulit

- AS

Ltd

, Plo

vdiv

tow

nPr

oduc

tion

of ti

ling-

ston

e fr

om m

arbl

e,lim

esto

neM

arits

aB

rezo

voB

rezo

vogu

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garia

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0.02

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kove

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0.00

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00

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al JS

Co

Wea

pons

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lizh

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0.00

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strie

s Ltd

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rain

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S In

dust

ries L

tdA

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drin

ks B

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ets

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20.

002

258

SKF

Bea

rings

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garia

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ia /I

W/

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hine

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g el

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K JS

Co

Text

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Tund

zha

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anla

kK

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lak

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a va

da ri

ver

TU_M

70.

001

2010

Vig

anle

x Lt

d So

fiaW

orks

hop

for p

rodu

ctio

n of

ess

entia

l oils

Tund

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Gur

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ver

TU_M

60.

001

30

3. A

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river

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rA

R_M

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025

254

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95

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t pro

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proc

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cess

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adan

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ing

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anM

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ansk

a riv

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R_M

50.

003

258

Prog

ress

troy

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ldin

gA

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R_M

50.

001

259

Bet

onst

roy

Ltd

Prod

uctio

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con

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Mad

anM

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000

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atio

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IVE

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ch.

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ines

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00

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315

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21.

1066

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9.00

343

5.00

191

911

6.00

273

1.10

5075

06.

0015

01.

1028

4517

56

1084

20.

027

48.7

9

3942

06

9461

0.20

031

5.36

1978

96

4749

0.92

172

9.25

1255

256

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584.

110

257.

9479

176

1900

0.04

012

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4096

698

30.

200

32.7

7

2288

654

90.

200

18.3

040

56

970.

200

3.24

228

655

0.20

01.

82

mat

eria

lsK

lade

nets

"10

46

250.

200

0.84

Tot

al N

kg/y

ear

Tot

al P

mg/

lT

otal

Pkg

/yea

rB

OD

kg/y

ear

Tot

al N

mg/

l

Ta

ble

6.2.

1 M

ajor

Indu

stri

es in

EA

BD

: Dir

ectly

Dis

char

ging

Was

tew

ater

into

the

Riv

ers o

r Wat

er B

odie

s (2/

2)



., Ltd.

Table 6.2.2 Major Industries in WABD: Directly Discharging Wastewater into the Rivers or Water Bodies

Sett

lem

ent

Mun

icip

ality

1. S

trum

a R

iver

Bas

in1

WW

TP L

eko

Co

SPLT

DPa

int

Stru

ma

Rad

omir

Rad

omir

Stru

ma

Riv

erST

_M9

0.48

922

3342

388.

212

PSK

Spa

rtak

Sand

ext

ract

ion

Stru

ma

v.Sk

lave

Sand

ansk

iSt

ream

ST_M

10.

500

2031

9039

7.83

3B

odzh

inov

& C

o Lt

dC

ar-w

ash

and

serv

ice-

stat

ion

Stru

ma

Sand

ansk

iSa

ndan

ski

Gul

lyST

_SA

N0.

500

1929

9592

10.0

01

4Th

erm

al P

ower

Pla

nt B

obov

Dol

SPJ

6-52 JICA CTI Engineering International Co

1266

502.

0030

853

1235

160.

3555

1957

680

1.34

2112

9SE

nerg

etic

sSt

rum

aB

obov

Dol

Bob

ov d

olR

azm

etan

itsa

Riv

erST

_DZH

10.

701

919

6643

4.00

5M

ines

Bob

ov D

ol JS

Co

Min

e in

dust

rySt

rum

aB

obov

Dol

Bob

ov d

olR

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etan

itsa

Riv

erST

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10.

099

5717

7015

5.75

6V

ersa

y Lt

dno

dat

aSt

rum

aPe

trich

Petri

chC

olle

ctor

ST_S

TR1

0.33

310

1050

154.

00

7G

aust

o-go

ld JS

Co

Min

e in

dust

ry a

nd tr

ansp

ort

Stru

ma

Kyu

sten

dil

Kyu

sten

dil

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r wat

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0.08

525

6662

08.

008

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ana

indu

stry

JSC

oSt

eel p

rodu

ctio

nSt

rum

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rnik

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ikSt

rum

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iver

ST_M

90.

051

3962

778

41.3

09

Topl

ofic

atsi

a - P

erni

k EA

D

Taili

ng p

ond

Stru

ma

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ikPe

rnik

Der

e "K

alka

s" /g

ully

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_M9

0.27

86

5613

410

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10V

&V

GD

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ndzh

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ch L

tdgr

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ouse

/ ag

ricul

tura

l-pla

nts

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ma

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chPe

trich

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inag

e ch

anne

lST

_STR

10.

012

135

5301

924

.00

11B

elas

itsa

S.A

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echa

nica

ls /W

ater

-met

erSt

rum

aPe

trich

Petri

chC

olle

ctor

ST_S

TR1

0.00

713

630

077

8.00

12B

enet

Ltd

Food

- m

ea

8842

70.

6714

850

1793

60.

9329

0942

006

0.43

4551

2131

80.

3387

365

965

50.6

580

894

9498

90.

4035

2793

9819

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7440

1766

5.00

1104

tSt

rum

aB

rezn

ikPe

rnik

Turs

ka R

iver

ST_K

ON

0.00

316

415

468

6.00

13Sa

nel J

SCo

Stee

l / m

etal

s arti

cles

Stru

ma

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ski

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lect

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012

7914

874

3.00

14M

ines

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rit V

agle

dobi

v JS

Co

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e in

dust

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rum

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ikK

rivob

arsk

a R

iver

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90.

010

3611

733

21.0

915

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govo

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AD

/san

itry

sew

age/

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ing

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ma

v. G

arly

ano

Kyu

sten

dil

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yans

ka B

istri

tsa

ST_S

OV

0.01

425

1095

06.

00

568

1.10

104

1135

0.27

101

6910

50.4

916

544

2628

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koop

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rukt

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dust

ry -

frui

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rum

av.

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ilovt

siK

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endi

lSt

rum

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iver

ST_M

60.

013

2510

157

4.00

1625

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17ZI

IU S

tand

art J

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hani

cals

/ m

eter

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rum

aB

lago

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lago

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olle

ctor

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RA

0.00

840

1009

23.

0075

70.

2718

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sto-

gold

JSC

oM

ine

indu

stry

, tra

nspo

r

0 9 68t

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ma

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sten

dil

Kyu

sten

dil

avar

age

load

ST_M

60.

002

123

8452

2.32

160

1.31

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eore

surs

SPL

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tract

ion

of b

alla

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rum

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iver

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40.

012

1863

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2280

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3010

720

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g - P

M S

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nium

min

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okos

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rive

rST

_M4

0.00

825

6306

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0.27

621

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trits

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tract

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of b

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rovn

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lago

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2750

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3822

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60.

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2548

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640.

4323

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es O

tkrit

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ledo

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ine

indu

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ma

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0.00

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978

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524

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trik

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ma

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lect

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_M9

0.00

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2.76

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iani

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319

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9.84

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139

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spea

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rum

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lect

orST

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005

697

83.

7058

32.

0031

539

Ros

ela

Ltd

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oupi

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rum

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3139

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Hyd

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roy

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97

JSC

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and

and

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el

8 73 85 2 5 39

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Kat

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ski

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ska

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0.00

125

919

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036

81.

5055

41M

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ombi

nat -

San

dans

ki S

PLTD

Food

indu

stry

- m

eat

Stru

ma

Sand

ansk

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ndan

ski

Sand

ansk

a B

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650

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mon

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Stru

ma

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hile

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iver

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60.

000

156

616

12.0

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2.10

8

NA

M C

atch

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oN

ame

of in

dust

ryB

usin

ess

RIV

ER

BA

SIN

Tot

al P

mg/

lT

otal

Pkg

/yea

rT

otal

Nm

g/l

Tot

al N

kg/y

ear

BO

D(k

g/ye

ar)

Loc

atio

nT

RIB

UT

AR

YR

IVE

RD

isch

arge

m3 /s

BO

D5

mg/

l

Tabl

e 6.

2.2

Maj

or In

dust

ries

in W

AB

D: D

irec

tly D

isch

argi

ng W

aste

wat

er in

to th

e R

iver

s or W

ater

Bod

ies (

1/2)



6-53

Sett

lem

ent

Mun

icip

ality

44M

es-C

o SP

LTD

Food

-m

eat

Stru

ma

Petri

chPe

trich

Col

lect

orST

_STR

10.

012

45D

B V

Ltd

-YM

SIIm

port

of e

lect

rics m

ater

ials

Stru

ma

Bob

oshe

voB

obos

hevo

Afte

r set

tling

ST_M

60.

006

46En

ergo

rem

ont-K

resn

a JS

Co

Elec

trica

l app

lianc

e.St

rum

aK

resn

aK

resn

aM

anho

leST

_M2

0.00

247

Gra

nit 9

7 SA

Roa

d bu

ildin

gSt

rum

av.

Nev

estin

oN

eves

tino

Stru

ma

Riv

erST

_M6

0.00

448

Tri B

ora

- Val

entin

Man

evno

dat

aSt

rum

aPe

trich

Petri

chIr

rigat

ion

chan

nel

ST_S

TR1

0.00

2

49Sa

obsh

titel

an T

ehni

ka JS

Co

Mac

hine

-bui

ldin

gSt

rum

aB

lago

evgr

adB

lago

evgr

adB

lago

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tsa

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0.00

050

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Inve

st JS

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Mea

t pro

duct

ion

Stru

ma

v.M

esht

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i

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11.

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63

540

3.00

540

0.23

415

388

10.0

073

61.

1484

333

12.

2024

30.

1315

529

03.

6022

70.

2415

7423

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7515

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Kriv

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esta

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er B

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1Pi

rinha

rd JS

Co

Sand

and

gra

vel w

ashi

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WW

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Raz

log

Bel

a riv

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181

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com

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ding

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and

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Mag

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JSC

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log

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JICA CTI Engineering International Co., Ltd.

2550

10.0

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1.50

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Mes

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ith ra

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Dos

pat

v. P

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kam

ak

Vel

ingr

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0.00

725

5566

5.00

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0.27

602

Ros

i Lt

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airy

Dos

pat

Dos

pat

Dos

pat

Dos

pat r

iver

DO

_M1

0.00

050

225

10.0

045

2.00

9

Tot

al P

mg/

lT

otal

Pkg

/yea

rB

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5

mg/

lB

OD

(kg/

year

)T

otal

Nm

g/l

Tot

al N

kg/y

ear

Loc

atio

nT

RIB

UT

AR

YR

IVE

RN

AM

Cat

ch.

Dis

char

gem

3 /sN

oN

ame

of in

dust

ryB

usin

ess

RIV

ER

BA

SIN

Tabl

e 6.

2.2

Maj

or In

dust

ries

in W

AB

D: D

irec

tly D

isch

argi

ng W

aste

wat

er in

to th

e R

iver

s or W

ater

Bod

ies (

2/2)



6-54 International Co., Ltd. JICA CTI Engineering

Table 6.2.3 Major Livestock Farms with their Pollution Loads in EABD

1. A

rda

Riv

er B

asin

BO

DT

N

Sett

lem

ent

Mun

icip

ality

kg /

year

/he

adkg

/ ye

ar /

head

12

34

56

78

1."F

uraz

hi 2

000"

PLC

TP

BO

DT

NT

Pkg

/ ye

ar /

head

kg /

year

kg /

year

kg /

year

910

1112

13

broy

lers

Mom

chilg

rad

Mom

chilg

rad

1200

00A

R_V

AR

10.

050.

02.

"Kok

oim

pex"

PLC

layi

ng h

ans

Smol

yan

- ind

ustri

al z

one

Smol

yan

9000

0A

R_C

HE

0.7

0.

2. T

undz

ha R

iver

Bas

inB

OD

TN

Sett

lem

ent

Mun

icip

ality

kg /

year

/he

adkg

/ ye

ar /

head

12

34

56

78

3."T

odor

Uzu

nov"

ST

CA

TTLE

SV

enet

s vill

age

Kar

noba

t30

0TU

_MO

C1

230

2."S

vine

kom

plex

" JS

Co

pigs

Kru

mov

o G

radi

shte

Kar

noba

t17

80TU

_MO

C1

7.98

4.0

6."B

ulm

aks -

DM

"pi

gsV

oden

icha

ne v

illag

eSt

rald

zha

1293

TU_M

OC

17.

984.

02.

"Gra

dus -

Ivan

Ang

elov

"

30.

002

6,00

03,

600

240

40.

1263

,000

36,0

0010

,800

Tota

l69

,000

39,6

0011

,040

TP

BO

DT

NT

Pkg

/ ye

ar /

head

kg /

year

kg /

year

kg /

year

910

1112

13

791.

469

,000

23,7

0042

03

0.73

8514

,204

7,17

31,

315

30.

7385

10,3

185,

211

955

broy

lers

Bol

yars

ko v

illag

eTu

ndzh

a12

0000

0TU

_KA

L0.

050.

4."R

epro

dukt

or p

o sv

inev

adstv

o"JS

Copi

gsK

alch

evo

villa

geTu

ndzh

a12

000

TU_M

27.

984.

05.

"Geo

mek

s"pi

gsY

ambo

lY

ambo

l42

26TU

_M2

7.98

4.0

6."M

CD

-02"

Ltd

.C

ATT

LES

Sam

uilo

vo v

illag

eSl

iven

TU_M

323

01.

"Eko

Far

m 2

005"

Ltd

.la

ying

han

sSa

mui

lovo

vill

age

Sliv

en60

000

TU_M

30.

70.

3."Z

K E

ko a

sorti

" ST

pigs

Mec

hkar

evo

villa

geSl

iven

1850

TU_M

47.

984.

07.

"SEL

EKT

- Iliy

a M

ihay

lov"

ST

CA

TTLE

STv

ardi

tsa

Tvar

dits

aTU

_M5

230

8."A

SKEN

T - P

lam

en P

ench

ev"

STC

ATT

LES

Tvar

dits

aTv

ardi

tsa

TU_M

523

0

Hea

dN

AM

Cat

chm

ent

NA

MC

atch

men

tH

ead

No

Reg

ion/

Nam

eSp

ecie

sL

ocat

ion

No

Reg

ion/

Nam

eL

ocat

ion

Spec

ies

030.

002

60,0

0036

,000

2,40

0

30.

7385

95,7

6048

,360

8,86

23

0.73

8533

,723

17,0

313,

121

791.

40

00

40.

1242

,000

24,0

007,

200

30.

7385

14,7

637,

456

1,36

679

1.4

00

079

1.4

00

05.

"Lyu

bom

ir Ly

uben

ov"

STC

ATT

LES

Loza

revo

vill

age

Sung

urla

re15

3TU

_MO

C2

230

791.

435

,190

12,0

8721

4To

tal

374,

959

181,

017

25,8

53

Tabl

e 6.

2.3

Maj

or L

ives

tock

Far

ms w

ith th

eir

Pollu

tion

Loa

ds in

EA

BD

(1/2

)




BO

DT

NT

PB

OD

TN

TP

Sett

lem

ent

Mun

icip

ality

kg /

year

/he

adkg

/ ye

ar /

head

kg /

year

/he

adkg

/ ye

arkg

/ ye

arkg

/ ye

ar

12

34

56

78

910

1112

13

8."D

IAN

A M

I" S

TC

ATT

LEK

orte

n vi

llage

Nov

a Za

gora

508

MA

_BLA

230

791.

411

6,84

040

,132

711

10.

"VZh

K -

Rod

opa"

PLC

pigs

Nov

a Za

gora

Nov

a Za

gora

5015

MA

_BLA

7.98

4.03

0.73

8540

,020

20,2

103,

704

10.

"Zhu

liv"P

LC

broy

lers

Nov

a Za

gora

Nov

a Za

gora

4100

00M

A_B

LA0.

050.

030.

002

20,5

0012

,300

820

9."D

enik

er -

Milk

" JS

CoC

ATT

LED

inev

o vi

llage

Has

kovo

200

MA

_HA

R123

079

1.4

46,0

0015

,800

280

8."G

alus

" JS

Co

duck

sH

asko

voH

asko

vo92

000

MA

_HA

R10.

20.

10.

006

18,4

009,

200

552

3."V

asil

Levs

ki"

Coo

pera

tion

CA

TTLE

Levs

ki v

illag

e12

0M

A_L

UD

123

079

1.4

27,6

009,

480

168

10.

"Em

il M

ihay

lov"

ST

CA

TTLE

Kre

post

vill

age

Dim

itrov

grad

100

MA

_M2

230

791.

423

,000

7,90

014

015

.PK

"A

grom

ax"

STpi

gsCh

erno

goro

vo v

illag

eD

imitr

ovgr

ad15

00M

A_M

27.

984.

030.

7385

11,9

706,

045

1,10

816

."E

lis"

PLC

pigs

Klo

kotn

itsa

villa

geH

asko

vo12

00M

A_M

27.

984.

030.

7385

9,57

64,

836

886

5."U

cheb

en ts

enta

r"C

ATT

LER

akov

ski

Rak

ovsk

i95

0M

A_M

323

079

1.4

218,

500

75,0

501,

330

6."Z

hK G

endo

v"C

ATT

LER

akov

ski

Rak

ovsk

i25

0M

A_M

323

079

1.4

57,5

0019

,750

350

3."S

tom

ar In

vest"

JSC

opi

gsB

eloz

emR

akov

ski

9800

MA

_M3

7.98

4.03

0.73

8578

,204

39,4

947,

237

6."R

eya

- 96"

ST

pigs

Bol

yarts

i vill

age

Sado

vo45

00M

A_M

37.

984.

030.

7385

35,9

1018

,135

3,32

38.

"Bra

tya

Kar

tevi

200

3" S

Tpi

gsM

anol

e vi

llage

Mar

itsa

7000

MA

_M3

7.98

4.03

0.73

8555

,860

28,2

105,

170

9."R

eya

- 96"

ST

pigs

Man

ole

villa

geM

arits

a10

000

MA

_M3

7.98

4.03

0.73

8579

,800

40,3

007,

385

6."G

radu

s" P

LCbr

oyle

rsC

hirp

anC

hirp

an56

0000

MA

_M3

0.05

0.03

0.00

228

,000

16,8

001,

120

4."K

OM

SO"

CA

TTLE

Tsal

apits

a vi

llage

1160

MA

_M4

230

791.

426

6,80

091

,640

1,62

4

4."D

imita

r Mad

zhar

ov -

svin

evad

stvo

pigs

Stam

boliy

ski

Stam

boliy

ski

1000

MA

_M4

7.98

4.03

0.73

857,

980

4,03

073

97.

"Elit

- 95

" ST

pigs

Kru

mov

o vi

llage

Rod

opi

2424

MA

_M4

7.98

4.03

0.73

8519

,344

9,76

91,

790

3."A

ndip

92"

ST

layi

ng h

ans

Plov

div

Plov

div

1550

00M

A_M

40.

70.

40.

1210

8,50

062

,000

18,6

004.

"Kal

mits

a" JS

Co

layi

ng h

ans

Tsal

apits

aR

odop

i80

000

MA

_M4

0.7

0.4

0.12

56,0

0032

,000

9,60

01.

ZK "

Mar

itsa

- 95"

CA

TTLE

Paza

rdzh

ikPa

zard

zhik

150

MA

_M5

230

791.

434

,500

11,8

5021

0

2."D

AN

IELA

90"

CA

TTLE

Ale

ko K

onst

antin

ovo

villa

ge11

0M

A_M

523

079

1.4

25,3

008,

690

154

1."S

VIK

OM

" JS

Co

pigs

Apr

iltsi

villa

gePa

zard

zhik

1200

0M

A_M

57.

984.

030.

7385

95,7

6048

,360

8,86

22.

"Ilm

a - I

l" L

tdla

ying

han

sPa

zard

zhi k

Paza

rdzh

ik66

000

MA

_M5

0.7

0.4

0.12

46,2

0026

,400

7,92

011

."A

yaks

- 95

"pi

gsB

ozdu

gano

vo v

illag

eR

adne

vo28

000

MA

_SA

Z27.

984.

030.

7385

223,

440

112,

840

20,6

78

12.

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aela

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asilk

a Zh

elya

zkov

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pigs

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ara

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8546

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23,3

744,

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in"

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pigs

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lave

n vi

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a Za

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7385

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2,88

014

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I - C

OM

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ryah

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7385

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3612

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2,36

37.

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tit"

PLC

broy

lers

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ukch

i vill

age

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000

3,00

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02.

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MI -

H. H

iuse

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hter

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14,5

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0014

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skar

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iril N

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erko

k" P

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lit -

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it - M

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172,

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3,06

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tal

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151,

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MC

atch

men

tH

ead

Spec

ies

No

Reg

ion/

Nam

e

Loc

atio

n

Tabl

e 6.

2.3

Maj

or L

ives

tock

Far

ms w

ith th

eir

Pollu

tion

Loa

ds in

EA

BD

(2/2

)




Table 6.2.4 Major Livestock Farms with their Pollution Loads in WABD 1.

Str

uma

Riv

er B

asin

BO

DT

NT

PB

OD

TN

T

Settl

emen

tM

unic

ipal

itykg

/ ye

ar /

head

kg /

year

/he

adkg

/ ye

ar /

head

kg /

year

kg /

year

kg /

year

12

34

56

78

910

1112

13

1."A

tana

s "Y

osifo

v"C

ATT

LEB

ersi

n vi

llage

106

ST_M

623

079

1.4

24,3

808,

374

148

1Po

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farm

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aldi

s"

layi

ng h

ens

Shis

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tsi v

illag

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endi

l85

850

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60.

70.

40.

1260

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2."B

oris

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v"C

ATT

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791.

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9,32

216

51.

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ola

Mal

inov

" C

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LEK

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ik v

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136

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01.

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baro

u M

M 5

" JS

Co

pigs

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n D

ol v

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eB

lago

evgr

ad10

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_M5

7.98

4.03

0.73

857,

980

4,03

073

9To

tal

150,

875

66,8

1011

,545

2. M

esta

Riv

er B

asin

BO

DT

NT

PB

OD

TN

T

Settl

emen

tM

unic

ipal

itykg

/ ye

ar /

head

kg /

year

/he

adkg

/ ye

ar /

head

kg /

year

kg /

year

kg /

year

12

34

56

78

910

1112

131.

"GH

T - P

irin

plas

t"

pigs

Bor

ovo

villa

geG

otse

Del

chev

1200

ME_

M3

7.98

4.03

0.73

859,

576

4,83

688

6To

tal

9,57

64,

836

886

No

Reg

ion/

Nam

e Sp

ecie

sL

ocat

ion

Hea

dN

AM

Cat

chm

ent

Hea

dN

AM

Cat

chm

ent

No

Reg

ion/

Nam

e Sp

ecie

sL

ocat

ion

P P

Tabl

e 6.

2.4

Maj

or L

ives

tock

Far

ms w

ith th

eir

Pollu

tion

Loa

ds in

WA

BD




Table 6.2.5 Estimated Quantity of Newly Treated Sewage and Reduction of Wastewater Loss for the High Priority Towns in EABD and WABD

New Renovat.

Renovat.

Newor

Expansion

(m3/year) (m3/year) (m3/year) (%) (m3/year) (m3/year) (m3/year)I. EABD Area1. New WWTPs and Improvements of SW in the Maritsa River Basin

1-1 Asenovgrad 78,054 x 46% x x 5,697,942 5,697,942 2,621,053 40% 1,048,421 10,484,213 9,435,7921-2 Plovdiv 681,985 85% x x 49,784,920 7,467,738 42,317,182 40% 16,926,873 169,268,727 152,341,8541-3 Karlovo 37,181 x 85% x x 2,714,177 2,714,177 2,307,050 40% 922,820 9,228,200 8,305,3801-4 Velingrad 28,752 x 90% x x 2,098,896 2,098,896 1,889,006 40% 755,603 7,556,026 6,800,4231-5 Peshtera 28,691 x 99% x x 2,094,407 2,094,407 2,073,462 40% 829,385 8,293,850 7,464,4651-6 Harmanli 28,538 x 67% x x 2,083,238 2,083,238 1,395,769 40% 558,308 5,583,077 5,024,7691-7 Svilengrad 28,050 x 38% x x 2,047,650 2,047,650 778,107 40% 311,243 3,112,428 2,801,1851-8 Chirpan 25,413 x 85% x x 1,855,149 1,855,149 1,576,877 40% 630,751 6,307,507 5,676,7561-9 Rakovski 23,453 x 0% x 1,712,033 1,712,033 0

1-10 Panagyurishte 23,029 x 86% x x 1,681,137 1,681,137 1,445,778 40% 578,311 5,783,113 5,204,8021-11 Parvomay 22,200 x 65% x x 1,620,600 1,620,600 1,053,390 40% 421,356 4,213,560 3,792,2041-12 Stamboliyski 18,068 x 74% x x 1,318,928 1,318,928 976,006 40% 390,403 3,904,025 3,513,6231-13 Kostenets 11,048 x 95% x x 806,533 806,533 766,207 40% 306,483 3,064,826 2,758,344

1,034,460 75,515,608 33,198,426 59,199,888 23,679,955 236,799,551 213,119,5962. New WWTPs and Improvements of SW in the Tundzha River Basin

2-1 Yambol 118,971 x 80% x x 8,684,883 8,684,883 6,947,906 40% 2,779,163 27,791,626 25,012,4632-2 Karnobat 28,916 x 100% x 2,110,832 2,110,832 2,110,832 40% 844,333 8,443,326 7,598,9932-3 Elhovo 16,808 x 84% x x 1,226,948 1,226,948 1,030,636 40% 412,254 4,122,544 3,710,2892-4 Kalofer 4,229 x 70% x x 308,702 308,702 216,092 40% 86,437 864,367 777,930

168,923 12,331,364 12,331,364 10,305,465 4,122,186 41,221,862 37,099,6763. New WWTPs and Improvements of SW in the Arda River Basin

3-1 Kardzhali 67,346 x 90% x x 4,916,252 4,916,252 4,424,627 50% 2,212,313 22,123,135 19,910,82167,346 4,916,252 4,916,252 4,424,627 2,212,313 22,123,135 19,910,821

4. Renovation of the Existing WWTPs and Improvements of SW4-1 Nova Zagora 36,185 x 97% x x 2,641,469 79,244 2,562,224 40% 1,024,890 10,248,898 9,224,0084-2 Radnevo 20,691 x 100% x 1,510,443 0 1,510,443 40% 604,177 6,041,772 5,437,5954-3 Ihtiman 20,234 x 95% x x 1,477,046 73,852 1,403,193 40% 561,277 5,612,773 5,051,4964-4 Pavel banya 4,407 x 60% x x 321,711 128,684 193,027 40% 77,211 772,106 694,896

81,516 5,950,668 281,781 5,668,887 2,267,555 22,675,549 20,407,9941,352,245 98,713,892 50,727,823 79,598,867 32,282,010 322,820,097 290,538,087

II. WABD Area1. New WWTPs and Improvements of SW in the Struma River Basin

1-1 Petrich 45,020 x 100% x 3,286,424 3,286,424 3,286,424 60% 1,971,854 19,718,541 17,746,6871-2 Sandanski 40,358 x 100% x 2,946,098 2,946,098 2,946,098 60% 1,767,659 17,676,585 15,908,9271-3 Simitli 8,242 x 100% x 601,637 601,637 601,637 60% 360,982 3,609,821 3,248,839

93,619 6,834,158 6,834,158 6,834,158 4,100,495 41,004,947 36,904,4522. New WWTPs and Improvements of SW in the Mesta River Basin

2-1 Gotse Delchev 30,185 x 96% x x 2,203,469 2,203,469 2,115,330 60% 1,269,198 12,691,979 11,422,7812-2 Bansko 11,493 x 71% x x 839,011 839,011 595,698 60% 357,419 3,574,186 3,216,768

41,678 3,042,479 3,042,479 2,711,027 1,626,616 16,266,165 14,639,5483. New WWTPs and Improvements of SW in the Dospat River Basin

3-1 Dospat 3,218 x 40% x x 234,943 234,943 93,977 60% 56,386 563,864 507,4773,218 234,943 234,943 93,977 56,386 563,864 507,477

4. Renovation of the Existing WWTPs and Improvements of SW4-1 Pernik 121,350 x 94% x x 8,858,550 531,513 8,327,037 60% 4,996,222 49,962,222 44,966,0004-2 Dupnitsa 55,224 x 91% x x 4,031,352 362,822 3,668,530 60% 2,201,118 22,011,182 19,810,0644-3 Radomir 21,621 x 90% x x 1,578,333 157,833 1,420,500 60% 852,300 8,522,998 7,670,698

198,195 14,468,235 1,052,168 13,416,067 8,049,640 80,496,402 72,446,762336,710 24,579,815 11,163,748 23,055,230 13,833,138 138,331,378 124,498,240

Note:1) Loss of new or renovated sewer pipes is assumed to be 10 %.2) Loss from the newly expanded sewer networks is assumed to be almost same as the current condition with the loss from the septec tanks.

Sewage to benewly treated:

BNo. Town /

Settlement PE in 2015

Improvementof WWTP

Improvementof Sewerage

Networks Total Sewageto be treated:A=200 l/d x

PE

Existingcoverageof SW: P

(%)

Reduction ofGroundwaterPollution by

Renovation ofSewer pipes:

F=0.9 x E

Currentlydischarged

sewage into theexisting sewerpipes: C=A*P

Estimated

Loss ofSW: L

Currently lostsewage into

ground: D=Cx L

Estimatedpolluted

groundwater bythe loss sewage:suppose E=10 x

D

The Study on Integrated Water Management Final Report - Main Reportin the Republic of Bulgaria Chapter 6


Table 6.2.6 Estimated Construction Cost for the Proposed Wastewater Treatment Plants and Sewerage Improvements for the High Priority Towns in EABD and WABD

Newor

Renovat.

UnitCost Direct Cost Civil Works Mechani.

WorksElectrical

Works

Non-construction

Activities

EngineeringCost: DirectCost x 10 %

Administration Cost: Direct

Cost x 5 %

PhysicalContingency:Direct Cost x

10 %

Sub-total Cost ofWWTPs

Improv. /New

Required

Lengthper PE

RequiredLength

UnitCost Direct Cost

EngineeringCost: DirectCost x 5 %

Administration Cost: Direct

Cost x 5 %

PhysicalContingency:

Direct Cost x 10%

Sub-total Cost ofSewer

Improvement

(EUR/PE) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR) (m /

PE) (m) (EUR/m) (EUR) (EUR) (EUR) (EUR) (EUR) (EUR)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25I. High Priority Towns and Settlements in EABD

I-1 New WWTPs and Improvements of SW in the Maritsa River BasinI-1-1 Asenovgrad Asenovgrad 78,054 New 210 16,391,340 7,376,103 4,917,402 2,458,701 1,639,134 737,610 819,567 1,639,134 19,587,651 Improv. 3.2 249,773 398 99,409,574 4,970,479 4,970,479 9,940,957 119,291,489 138,879,141I-1-2 Plovdiv Plovdiv 681,985 - 0 Improv. 0.9 613,787 750 460,340,010 23,017,001 23,017,001 46,034,001 552,408,012 552,408,012I-1-3 Karlovo Karlovo 37,181 New 295 10,968,248 4,935,711 3,290,474 1,645,237 1,096,825 493,571 548,412 1,096,825 13,107,056 Improv. 4.0 148,722 340 50,565,480 2,528,274 2,528,274 5,056,548 60,678,576 73,785,632I-1-4 Velingrad Velingrad 28,752 New 320 9,200,640 4,140,288 2,760,192 1,380,096 920,064 414,029 460,032 920,064 10,994,765 Improv. 4.1 117,883 333 39,255,106 1,962,755 1,962,755 3,925,511 47,106,127 58,100,892I-1-5 Peshtera Peshtera 28,691 New 320 9,180,960 4,131,432 2,754,288 1,377,144 918,096 413,143 459,048 918,096 10,971,247 Improv. 4.1 117,631 333 39,171,140 1,958,557 1,958,557 3,917,114 47,005,368 57,976,615I-1-6 Harmanli Harmanli 28,538 New 320 9,132,000 4,109,400 2,739,600 1,369,800 913,200 410,940 456,600 913,200 10,912,740 Improv. 4.1 117,004 333 38,962,249 1,948,112 1,948,112 3,896,225 46,754,699 57,667,439I-1-7 Svilengrad Svilengrad 28,050 New 320 8,976,000 4,039,200 2,692,800 1,346,400 897,600 403,920 448,800 897,600 10,726,320 Improv. 4.1 115,005 332 38,181,660 1,909,083 1,909,083 3,818,166 45,817,992 56,544,312I-1-8 Chirpan Chirpan 25,413 New 335 8,513,355 3,831,010 2,554,007 1,277,003 851,336 383,101 425,668 851,336 10,173,459 Improv. 4.2 106,735 330 35,222,418 1,761,121 1,761,121 3,522,242 42,266,902 52,440,361I-1-9 Rakovski Rakovski 23,453 New 340 7,973,850 3,588,233 2,392,155 1,196,078 797,385 358,823 398,693 797,385 9,528,751 New 4.2 98,501 329 32,406,665 1,620,333 1,620,333 3,240,666 38,887,997 48,416,748

I-1-10 Panagyurishte Panagyurishte 23,029 New 340 7,829,955 3,523,480 2,348,987 1,174,493 782,996 352,348 391,498 782,996 9,356,796 Improv. 4.2 96,723 329 31,821,859 1,591,093 1,591,093 3,182,186 38,186,231 47,543,027I-1-11 Parvomay Parvomay 22,200 New 340 7,548,000 3,396,600 2,264,400 1,132,200 754,800 339,660 377,400 754,800 9,019,860 Improv. 4.2 93,240 328 30,582,720 1,529,136 1,529,136 3,058,272 36,699,264 45,719,124I-1-12 Stamboliyski Stamboliyski 18,068 New 380 6,865,650 3,089,543 2,059,695 1,029,848 686,565 308,954 343,283 686,565 8,204,452 Improv. 4.6 83,111 325 27,010,913 1,350,546 1,350,546 2,701,091 32,413,095 40,617,547I-1-13 Kostenets Kostenets 11,048 New 395 4,364,118 1,963,853 1,309,235 654,618 436,412 196,385 218,206 436,412 5,215,121 Improv. 5.7 62,976 320 20,152,282 1,007,614 1,007,614 2,015,228 24,182,738 29,397,859

Sub-total I-1 1,034,460 106,944,116 48,124,852 32,083,235 16,041,617 10,694,412 4,812,485 5,347,206 10,694,412 127,798,218 2,021,089 943,082,074 47,154,104 47,154,104 94,308,207 1,131,698,489 1,259,496,707I-2 New WWTPs and Improvements of SW in the Tundzha River Basin

I-2-1 Yambol Tundzha 118,971 New 145 17,250,795 7,762,858 5,175,239 2,587,619 1,725,080 776,286 862,540 1,725,080 20,614,700 Improv. 2.5 297,428 455 135,329,513 6,766,476 6,766,476 13,532,951 162,395,415 183,010,115I-2-2 Karnobat Karnobat 28,916 New 320 9,252,960 4,163,832 2,775,888 1,387,944 925,296 416,383 462,648 925,296 11,057,287 Improv. 4.1 118,554 333 39,478,332 1,973,917 1,973,917 3,947,833 47,373,999 58,431,286I-2-3 Elhovo Elhovo 16,808 New 365 6,134,738 2,760,632 1,840,421 920,211 613,474 276,063 306,737 613,474 7,331,011 Improv. 4.8 80,676 324 26,139,024 1,306,951 1,306,951 2,613,902 31,366,829 38,697,840I-2-4 Kalofer Karlovo 4,229 New 455 1,924,104 865,847 577,231 288,616 192,410 86,585 96,205 192,410 2,299,304 Improv. 7.2 30,447 299 9,103,761 455,188 455,188 910,376 10,924,513 13,223,817

Sub-total I-2 168,923 34,562,597 15,553,168 10,368,779 5,184,389 3,456,260 1,555,317 1,728,130 3,456,260 41,302,303 527,104 210,050,629 10,502,531 10,502,531 21,005,063 252,060,755 293,363,058I-3 New WWTPs and Improvements of SW in the Arda River Basin

I-3-1 Kardzhali Kardzhali 67,346 New 215 14,479,373 6,515,718 4,343,812 2,171,906 1,447,937 651,572 723,969 1,447,937 17,302,850 Improv. 3.4 228,976 382 87,468,881 4,373,444 4,373,444 8,746,888 104,962,657 122,265,508Sub-total I-3 67,346 14,479,373 6,515,718 4,343,812 2,171,906 1,447,937 651,572 723,969 1,447,937 17,302,850 228,976 87,468,881 4,373,444 4,373,444 8,746,888 104,962,657 122,265,508

I-4 Renovation of the Existing WWTPs and Improvements of SWI-4-1 Nova Zagora Nova Zagora 36,185 Renovat 140 5,065,830 1,773,041 2,026,332 1,013,166 253,292 177,304 253,292 506,583 6,003,009 Improv. 4.0 144,738 340 49,210,920 2,460,546 2,460,546 4,921,092 59,053,104 65,056,113I-4-2 Radnevo Radnevo 20,691 Renovat 245 5,069,295 1,774,253 2,027,718 1,013,859 253,465 177,425 253,465 506,930 6,007,115 Improv. 4.3 88,971 326 29,004,644 1,450,232 1,450,232 2,900,464 34,805,573 40,812,687I-4-3 Ihtiman Ihtiman 20,234 Renovat 245 4,957,208 1,735,023 1,982,883 991,442 247,860 173,502 247,860 495,721 5,874,291 Improv. 4.3 87,004 326 28,363,320 1,418,166 1,418,166 2,836,332 34,035,984 39,910,275I-4-4 Pavel banya Pavel banya 4,407 Renovat 338 1,487,363 520,577 594,945 297,473 74,368 52,058 74,368 148,736 1,762,525 Improv. 7.3 32,171 297 9,554,817 477,741 477,741 955,482 11,465,780 13,228,305

Sub-total I-4 81,516 16,579,695 5,802,893 6,631,878 3,315,939 828,985 580,289 828,985 1,657,970 19,646,939 352,884 116,133,701 5,806,685 5,806,685 11,613,370 139,360,441 159,007,380Total of I. 1,352,245 172,565,780 75,996,632 53,427,704 26,713,852 16,427,593 7,599,663 8,628,289 17,256,578 206,050,310 3,130,054 1,356,735,285 67,836,764 67,836,764 135,673,529 1,628,082,342 1,834,132,652

II. High Priority Towns and Settlements in WABDII-1 New WWTPs and Improvements of SW in the Struma River Basin

II-1-1 Petrich Petrich 45,020 New 250 11,254,875 5,064,694 3,376,463 1,688,231 1,125,488 506,469 562,744 1,125,488 12,324,088 Improv. 3.8 171,074 347 59,362,713 2,968,136 2,968,136 5,936,271 71,235,255 83,559,343II-1-2 Sandanski Sandanski 40,358 New 260 10,492,950 4,721,828 3,147,885 1,573,943 1,049,295 472,183 524,648 1,049,295 11,489,780 Improv. 3.9 157,394 343 53,986,228 2,699,311 2,699,311 5,398,623 64,783,473 76,273,254II-1-3 Simitli Simitli 8,242 New 420 3,461,472 1,557,662 1,038,442 519,221 346,147 155,766 173,074 346,147 3,790,312 No info. 6.3 51,922 313 16,251,611 812,581 812,581 1,625,161 19,501,933 23,292,245

Sub-total II-1 93,619 25,209,297 11,344,184 7,562,789 3,781,395 2,520,930 1,134,418 1,260,465 2,520,930 27,604,180 380,390 129,600,551 6,480,028 6,480,028 12,960,055 155,520,662 183,124,842II-2 New WWTPs and Improvements of SW in the Mesta River Basin

II-2-1 Gotse Delchev Gotse Delchev 30,185 New 320 9,659,040 4,346,568 2,897,712 1,448,856 965,904 434,657 482,952 965,904 10,576,649 Improv. 4.1 123,756 335 41,458,411 2,072,921 2,072,921 4,145,841 49,750,093 60,326,742II-2-2 Bansko Bansko 11,493 New 400 4,597,320 2,068,794 1,379,196 689,598 459,732 206,879 229,866 459,732 5,034,065 Improv. 5.6 64,362 320 20,595,994 1,029,800 1,029,800 2,059,599 24,715,192 29,749,258

Sub-total II-2 41,678 14,256,360 6,415,362 4,276,908 2,138,454 1,425,636 641,536 712,818 1,425,636 15,610,714 188,119 62,054,404 3,102,720 3,102,720 6,205,440 74,465,285 90,075,999II-3 New WWTPs and Improvements of SW in the Dospat River Basin

II-3-1 Dospat Dospat 3,218 New 430 1,383,912 622,760 415,174 207,587 138,391 62,276 69,196 138,391 1,515,384 Improv. 7.3 23,494 300 7,048,296 352,415 352,415 704,830 8,457,955 9,973,339Sub-total II-3 3,218 1,383,912 622,760 415,174 207,587 138,391 62,276 69,196 138,391 1,515,384 23,494 7,048,296 352,415 352,415 704,830 8,457,955 9,973,339

II-4 Renovation of the Existing WWTPs and Improvements of SWII-4-1 Pernik Pernik 121,350 Renovat 84 10,193,400 4,077,360 3,567,690 2,038,680 509,670 407,736 509,670 1,019,340 11,110,806 Improv. 2.7 327,645 445 145,802,025 7,290,101 7,290,101 14,580,203 174,962,430 186,073,236II-4-2 Dupnitsa Dupnitsa 55,224 Renovat 175 9,664,200 3,382,470 3,865,680 1,932,840 483,210 338,247 483,210 966,420 10,485,657 Improv. 3.7 204,329 353 72,128,066 3,606,403 3,606,403 7,212,807 86,553,680 97,039,337II-4-3 Radomir Radomir 21,621 Renovat 245 5,297,145 1,854,001 2,118,858 1,059,429 264,857 185,400 264,857 529,715 5,747,402 Improv. 4.3 92,970 328 30,494,258 1,524,713 1,524,713 3,049,426 36,593,110 42,340,512

Sub-total II-4 198,195 25,154,745 9,313,831 9,552,228 5,030,949 1,257,737 931,383 1,257,737 2,515,475 27,343,865 624,944 248,424,350 12,421,217 12,421,217 24,842,435 298,109,220 325,453,085Total of II. 336,710 66,004,314 27,696,137 21,807,099 11,158,384 5,342,694 2,769,614 3,300,216 6,600,431 72,074,143 1,216,948 447,127,602 22,356,380 22,356,380 44,712,760 536,553,122 608,627,265

Total of I. and II. 278,124,454 Total of I. and II. 2,164,635,464 2,442,759,918

Total Cost ofWWTPs and

Sewer NetworksNo. Town /

Settlement Municipality PE in 2015

New Construction or Renovation of the WWTPs Improvement (including Expansion) or New Sewer Networks




Table 6.2.7 Estimated Operation and Maintenance Cost for the Proposed WWTPs and Sewer Improvements

New orRenovat. Direct Cost O&M Cost Improv. /

New Direct Cost O&M Cost

(EUR) (EUR/year) (EUR) (EUR/year) (EUR)I. High Priority Towns and Settlements in EABD

I-1 New WWTPs and Improvements of SW in the Maritsa River BasinI-1-1 Asenovgrad Asenovgrad 78,054 New 16,391,340 1,229,351 Improv. 99,409,574 1,491,144 2,720,494I-1-2 Plovdiv Plovdiv 681,985 - 0 Improv. 460,340,010 4,603,400 4,603,400I-1-3 Karlovo Karlovo 37,181 New 10,968,248 822,619 Improv. 50,565,480 758,482 1,581,101I-1-4 Velingrad Velingrad 28,752 New 9,200,640 690,048 Improv. 39,255,106 588,827 1,278,875I-1-5 Peshtera Peshtera 28,691 New 9,180,960 688,572 Improv. 39,171,140 587,567 1,276,139I-1-6 Harmanli Harmanli 28,538 New 9,132,000 684,900 Improv. 38,962,249 584,434 1,269,334I-1-7 Svilengrad Svilengrad 28,050 New 8,976,000 673,200 Improv. 38,181,660 572,725 1,245,925I-1-8 Chirpan Chirpan 25,413 New 8,513,355 638,502 Improv. 35,222,418 528,336 1,166,838I-1-9 Rakovski Rakovski 23,453 New 7,973,850 598,039 New 32,406,665 486,100 1,084,139

I-1-10 Panagyurishte Panagyurishte 23,029 New 7,829,955 587,247 Improv. 31,821,859 477,328 1,064,575I-1-11 Parvomay Parvomay 22,200 New 7,548,000 566,100 Improv. 30,582,720 458,741 1,024,841I-1-12 Stamboliyski Stamboliyski 18,068 New 6,865,650 514,924 Improv. 27,010,913 405,164 920,087I-1-13 Kostenets Kostenets 11,048 New 4,364,118 327,309 Improv. 20,152,282 302,284 629,593

Sub-total I-1 1,034,460 106,944,116 8,020,809 943,082,074 11,844,531 19,865,340I-2 New WWTPs and Improvements of SW in the Tundzha River Basin

I-2-1 Yambol Tundzha 118,971 New 17,250,795 1,293,810 Improv. 135,329,513 2,029,943 3,323,752I-2-2 Karnobat Karnobat 28,916 New 9,252,960 693,972 Improv. 39,478,332 592,175 1,286,147I-2-3 Elhovo Elhovo 16,808 New 6,134,738 460,105 Improv. 26,139,024 392,085 852,191I-2-4 Kalofer Karlovo 4,229 New 1,924,104 144,308 Improv. 9,103,761 136,556 280,864

Sub-total I-2 168,923 34,562,597 2,592,195 210,050,629 3,150,759 5,742,954I-3 New WWTPs and Improvements of SW in the Arda River Basin

I-3-1 Kardzhali Kardzhali 67,346 New 14,479,373 1,085,953 Improv. 87,468,881 1,312,033 2,397,986Sub-total I-3 67,346 14,479,373 1,085,953 87,468,881 1,312,033 2,397,986

I-4 Renovation of the Existing WWTPs and Improvements of SW in EABDI-4-1 Nova Zagora Nova Zagora 36,185 Renovat. 5,065,830 542,768 Improv. 49,210,920 738,164 1,280,931I-4-2 Radnevo Radnevo 20,691 Renovat. 5,069,295 543,139 Improv. 29,004,644 435,070 978,208I-4-3 Ihtiman Ihtiman 20,234 Renovat. 4,957,208 531,129 Improv. 28,363,320 425,450 956,579I-4-4 Pavel banya Pavel banya 4,407 Renovat. 1,487,363 148,736 Improv. 9,554,817 143,322 292,059

Sub-total I-4 81,516 16,579,695 1,765,772 116,133,701 1,742,006 3,507,777Total of I. 1,352,245 172,565,780 13,464,728 1,356,735,285 18,049,329 31,514,057

II. High Priority Towns and Settlements in WABDII-1 New WWTPs and Improvements of SW in the Struma River Basin

II-1-1 Petrich Petrich 45,020 New 11,254,875 844,116 Improv. 59,362,713 890,441 1,734,556II-1-2 Sandanski Sandanski 40,358 New 10,492,950 786,971 Improv. 53,986,228 809,793 1,596,765II-1-3 Simitli Simitli 8,242 New 3,461,472 259,610 No info. 16,251,611 243,774 503,385

Sub-total II-1 93,619 25,209,297 1,890,697 129,600,551 1,944,008 3,834,706II-2 New WWTPs and Improvements of SW in the Mesta River Basin

II-2-1 Gotse Delchev Gotse Delchev 30,185 New 9,659,040 724,428 Improv. 41,458,411 621,876 1,346,304II-2-2 Bansko Bansko 11,493 New 4,597,320 344,799 Improv. 20,595,994 308,940 653,739

Sub-total II-2 41,678 14,256,360 1,069,227 62,054,404 930,816 2,000,043II-3 New WWTPs and Improvements of SW in the Dospat River Basin

II-3-1 Dospat Dospat 3,218 New 1,383,912 103,793 Improv. 7,048,296 105,724 209,518Sub-total II-3 3,218 1,383,912 103,793 7,048,296 105,724 209,518

II-4 Renovation of the Existing WWTPs and Improvements of SW in WABDII-4-1 Pernik Pernik 121,350 Renovat. 10,193,400 1,274,175 Improv. 145,802,025 2,187,030 3,461,205II-4-2 Dupnitsa Dupnitsa 55,224 Renovat. 9,664,200 1,035,450 Improv. 72,128,066 1,081,921 2,117,371II-4-3 Radomir Radomir 21,621 Renovat. 5,297,145 567,551 Improv. 30,494,258 457,414 1,024,965

Sub-total II-4 198,195 25,154,745 2,877,176 248,424,350 3,726,365 6,603,541Total of II. 336,710 66,004,314 5,940,894 447,127,602 6,706,914 12,647,808

Total 19,405,622 24,756,243 44,161,865

Total O&M CostNo. Town / Settlement Municipality PE in 2015

New Construction or Renovation of theWWTPs

Improvement (including Expansion) or NewSewerage Networks

6.3



Table 6.3.1 Water Supply Networks to be Improoved in Bulgaria

Asbestoscement (AS) Steel (ST) Cast iron PVC +

HDPE Other Total lengthInformat.NecessaryImprove.

ReplacementLength of Pipe

(AS+ST)Unit Cost Direct Cost (A) Engineering

Cost (5% of A)AdministrationCost (5 % of A)

PhysicalContingency(10% of A)

Total Cost

(m) (m) (m) (m) (m) (m) (m) (m) (EUR / m) (EUR) (EUR) (EUR) (EUR) (EUR)1 Burgas State BSBD 14 424,080 2,471,360 923,855 75,547 32,752 201,486 3,705,000 3,395,215 160 543,234,400 27,161,720 27,161,720 54,323,440 651,881,2802 Dobrich State BSBD 8 225,987 2,975,000 181,000 4,000 52,000 52,000 3,264,000 3,156,000 160 504,960,000 25,248,000 25,248,000 50,496,000 605,952,0003 Shumen State & Municp. BSBD 10 214,880 1,857,607 442,894 33,496 3,550 0 2,337,547 2,300,501 160 368,080,160 18,404,008 18,404,008 36,808,016 441,696,1924 Varna State & Municp. BSBD 12 461,126 3,207,775 432,270 212,556 14,692 833,707 4,701,000 3,640,045 160 582,407,200 29,120,360 29,120,360 58,240,720 698,888,640

Sub-total 44 1,326,073 10,511,742 1,980,019 325,599 102,994 1,087,193 14,007,547 12,491,761 160 1,998,681,760 99,934,088 99,934,088 199,868,176 2,398,418,1125 Pleven State DRBD 10 314,965 2,461,471 527,336 8,692 47,771 8,730 3,054,000 2,988,807 160 478,209,120 23,910,456 23,910,456 47,820,912 573,850,9446 Razgrad State DRBD 5 133,122 1,271,700 306,720 6,200 5,480 0 1,590,100 1,578,420 160 252,547,200 12,627,360 12,627,360 25,254,720 303,056,6407 Vidin State DRBD 11 149,382 1,432,572 100,621 29,636 92,968 0 1,655,797 1,533,193 160 245,310,880 12,265,544 12,265,544 24,531,088 294,373,0568 Sofia-district State DRBD & EABD 21 218,509 2,289,400 751,400 16,600 32,400 206,200 3,296,000 3,040,800 160 486,528,000 24,326,400 24,326,400 48,652,800 583,833,6009 Gabrovo State & Municp. DRBD 3 100,927 910,230 48,480 27,000 21,430 99,860 1,107,000 958,710 160 153,393,600 7,669,680 7,669,680 15,339,360 184,072,320

10 Isperih State & Municp. DRBD 3 47,727 500,900 171,100 31,800 0 31,200 735,000 672,000 136 91,716,307 4,585,815 4,585,815 9,171,631 110,059,56911 Lovech State & Municp. DRBD 7 137,323 1,334,140 354,822 3,600 18,092 44,346 1,755,000 1,688,962 160 270,233,920 13,511,696 13,511,696 27,023,392 324,280,70412 Montana State & Municp. DRBD 10 148,096 1,252,100 167,980 3,700 59,926 17,294 1,501,000 1,420,080 160 227,212,800 11,360,640 11,360,640 22,721,280 272,655,36013 Russe State & Municp. DRBD 8 275,538 1,846,008 364,123 122,370 107,281 408,218 2,848,000 2,210,131 160 353,620,960 17,681,048 17,681,048 35,362,096 424,345,15214 Silistra State & Municp. DRBD 7 142,786 1,707,308 47,280 24,661 72,555 0 1,851,804 1,754,588 160 280,734,080 14,036,704 14,036,704 28,073,408 336,880,89615 Targovishte State & Municp. DRBD 3 99,205 1,313,615 65,576 2,156 2,559 22,094 1,406,000 1,379,191 160 220,670,560 11,033,528 11,033,528 22,067,056 264,804,67216 Veliko Tarnovo State & Municp. DRBD 9 266,229 2,387,936 252,647 30,180 9,893 239,344 2,920,000 2,640,583 160 422,493,280 21,124,664 21,124,664 42,249,328 506,991,93617 Vratsa State & Municp. DRBD 10 242,975 2,311,842 302,967 52,460 25,174 0 2,692,443 2,614,809 160 418,369,440 20,918,472 20,918,472 41,836,944 502,043,32818 Berkovitsa Municipality DRBD 1 21,466 173 20,294 0 147 20,614 20,467 115 2,363,426 118,171 118,171 236,343 2,836,11119 Botevgrad Municipality DRBD 1 41,203 282,943 32,191 0 2,300 317,434 315,134 131 41,365,560 2,068,278 2,068,278 4,136,556 49,638,67220 Knezha Municipality DRBD 1 17,501 188,910 1,700 0 1,690 192,300 190,610 112 21,405,846 1,070,292 1,070,292 2,140,585 25,687,01521 Kubrat Municipality DRBD 1 28,357 227,275 99,883 0 3,161 330,319 327,158 121 39,581,734 1,979,087 1,979,087 3,958,173 47,498,08122 Sevlievo Municipality DRBD 40,989 551,755 38,388 0 6,811 596,954 590,143 131 77,363,144 3,868,157 3,868,157 7,736,314 92,835,77323 Sofia City Municipality DRBD 1 1,177,577 878,000 1,105,000 812,000 455,000 3,250,000 1,983,000 160 317,280,000 15,864,000 15,864,000 31,728,000 380,736,00024 Svishtov Municipality DRBD 1 50,000 360,000 80,000 0 20,000 460,000 440,000 138 60,852,440 3,042,622 3,042,622 6,085,244 73,022,92825 Troyan Municipality DRBD

Sub-total 113 3,653,877 23,508,278 4,838,508 1,171,055 984,638 1,077,286 31,579,765 28,346,786 157 4,461,252,298 223,062,615 223,062,615 446,125,230 5,353,502,75726 Haskovo (*) State EABD 9 194,895 1,861,319 229,800 3,027 7,176 20,606 2,121,928 27,420 2,091,119 160 334,579,040 16,728,952 16,728,952 33,457,904 401,494,84827 Pazardzhik State EABD 3 165,426 749,680 162,511 116 31,980 0 944,287 912,191 160 145,950,560 7,297,528 7,297,528 14,595,056 175,140,67228 Plovdov State EABD 16 720,416 3,187,898 332,965 75,404 27,921 1,581,812 5,206,000 3,520,863 160 563,338,080 28,166,904 28,166,904 56,333,808 676,005,69629 Smolyan State EABD 11 141,013 1,015,171 215,940 2,619 36,424 120,846 1,391,000 1,231,111 160 196,977,760 9,848,888 9,848,888 19,697,776 236,373,31230 Stara Zagora State EABD 18 388,182 2,418,375 444,124 65,344 75,736 310,421 3,314,000 2,862,499 160 457,999,840 22,899,992 22,899,992 45,799,984 549,599,80831 Yambol (*) State EABD 5 145,948 1,420,653 311,865 0 34,488 26,369 1,793,375 1,732,518 160 277,202,880 13,860,144 13,860,144 27,720,288 332,643,45632 Dimitrovgrad State & Municp. EABD 1 64,981 465,000 36,000 20,300 16,698 0 537,998 501,000 150 75,293,186 3,764,659 3,764,659 7,529,319 90,351,82333 Kardzhali (*) State & Municp. EABD 7 140,175 1,059,464 74,958 0 121,432 65,955 1,321,809 692,000 1,134,422 160 181,507,520 9,075,376 9,075,376 18,150,752 217,809,02434 Sliven State & Municp. EABD 4 234,000 1,301,000 537,000 10,000 17,000 14,000 1,879,000 1,838,000 160 294,080,000 14,704,000 14,704,000 29,408,000 352,896,00035 Batak Municipality EABD 1 7,000 66,000 15,000 0 1,500 82,500 81,000 104 8,415,981 420,799 420,799 841,598 10,099,17736 Belovo Municipality EABD 1 12,000 45,000 3,000 0 1,200 49,200 48,000 108 5,179,248 258,962 258,962 517,925 6,215,09837 Bratsigovo Municipality EABD38 Panagyurishte Municipality EABD 1 31,000 76,000 60,000 0 2,000 138,000 136,000 123 16,741,736 837,087 837,087 1,674,174 20,090,08339 Peshtera Municipality EABD 1 25,000 95,000 25,000 4,000 3,000 127,000 120,000 118 14,196,120 709,806 709,806 1,419,612 17,035,34440 Rakitovo Municipality EABD 1 16,200 32,000 1,200 0 2,100 35,300 33,200 111 3,693,865 184,693 184,693 369,387 4,432,63841 Strelcha Municipality EABD 1 6,000 46,020 23,610 0 10,070 79,700 69,630 103 7,178,923 358,946 358,946 717,892 8,614,70742 Velingrad Municipality EABD 1 41,450 250,236 2,070 41,031 4,800 298,137 252,306 131 33,168,399 1,658,420 1,658,420 3,316,840 39,802,07943 Sub-total 81 2,333,686 14,088,816 2,475,043 221,841 393,525 2,140,009 19,319,234 16,563,859 158 2,615,503,138 130,775,157 130,775,157 261,550,314 3,138,603,76544 Blagoevgrad State WABD 10 219,629 947,639 416,836 9,226 35,055 19,244 1,428,000 1,364,475 160 218,316,000 10,915,800 10,915,800 21,831,600 261,979,20045 Kyustendil (*) State & Municp. WABD 8 103,211 1,159,066 276,962 27,348 31,753 184,740 1,679,869 1,479,600 1,436,028 160 229,764,480 11,488,224 11,488,224 22,976,448 275,717,37646 Pernik State & Municp. WABD 6 105,867 1,005,034 217,607 38,258 1,075 97,026 1,359,000 1,222,641 160 195,622,560 9,781,128 9,781,128 19,562,256 234,747,07247 Breznik Municipality WABD48 Dupnitsa Municipality WABD 1 51,715 113,718 89,644 16,273 9,949 229,584 203,362 140 28,404,181 1,420,209 1,420,209 2,840,418 34,085,01749 Kovachevtsi Municipality WABD50 Kresna Municipality WABD51 Petrich Municipality WABD 1 65,000 310,290 9,970 700 3,300 324,260 320,260 150 48,135,398 2,406,770 2,406,770 4,813,540 57,762,47852 Sandanski Municipality WABD 1 43,943 301,594 37,373 0 3,214 342,181 338,967 133 45,236,977 2,261,849 2,261,849 4,523,698 54,284,372

Sub-total 27 589,365 3,837,341 1,048,392 91,805 84,346 301,010 5,362,894 4,885,733 765,479,595 38,273,980 38,273,980 76,547,960 918,575,515Total 265 7,903,001 51,946,177 10,341,962 1,810,300 1,565,503 4,605,498 70,269,440 62,288,139 158 9,840,916,791 492,045,840 492,045,840 984,091,679 11,809,100,149

Note: Estimated cost is without VAT.Data Source: 1) "Management and Development Strategy for Water Supply and Sewerage Sector in the Republic of Bulgaria", MoRDPW, 2004

2) WSS Companies with (*) mark and gray color are based on the answer to the questionnaires to the WSS Companies in EABD and WABD areas by the end of August 2007, which have been received by this Study.

No. Related BasinDistrict

Numberof

municip.supplied

Servedpopulat. by

WS

Existing Pipes for Water Supply Estimated Necessary Improvement of WS Pipes

WSS Co. Owner



Table 6.3.2 Rehabilitation of Irrigation System List (EABD)

Irrigationcanal

New Intakestructure

RenovationITS, DP, DS,

S, T, A

RehabilitationITS, DP, DS,

S, A, T

Lining ofcanal Const. cost Machinery

costElectricity

cost TOTAL

Pazardzhik Topolnitsa 70 121,968 39,217 Lesichevo weir WI 15.0 117,738 1 137,000 0 0.0 317 0 22 0 12 0 4,500 3,154,550 10,646,583 13,805,633 655,970 400,000 14,861,603 3,715,401 18,577,004Pazardzhik Aleko-Pazardzhik 73 240,353 111,750 Zlokuchene WI, Pasha ark WI 18.0 157,522 0 0 2 1,490.0 359 0 25 0 11 0 40,649 2,300,800 11,316,510 13,657,959 305,346 68,000 14,031,305 3,507,826 17,539,131Pazardzhik Karabunar 71 88,602 48,013 Momina klisura WI, Boshulsko dere WI 7.5 168,410 0 0 0 0.0 417 0 58 2 28 50,000 27,375 3,534,000 7,264,946 10,876,321 83,072 42,000 11,001,393 2,750,348 13,751,741Plovdiv Stryama-Chirpan 132 132,800 92,907 Ivan Vazovo WI 17.0 82,453 1 20 0 0.0 0 93 0 11 0 0 12,000 1,048,500 6,202,576 7,263,076 1,074,500 0 8,337,576 2,084,394 10,421,970

Plovdiv Topolnitsa 130 365,757 274,789

Potoka RI km8 + 300, WI of Kachana maindrianage channel-1 km 0+476, WI ofPelinitsa main drainage channel-1 km2+986, WI main drainage channel-5 ,Strelcha WI, Chernozem weir WI

10.7 213,796 5 213,300 0 0.0 375 8 48 0 63 50,000 164,440 3,922,500 15,085,136 19,222,076 80,900 5,500 19,308,476 4,827,119 24,135,595

Sub Total 949,480 566,676 Sub Total 68.2 739,919 7 350,320 2 1,490.0 1,468 101 153 13 114 100,000 248,964 13,960,350 50,515,751 64,825,065 2,199,788 515,500 67,540,353 16,885,088 84,425,441Haskovo Trakiets 186 136,899 70,568 N/A 0.0 128,790 2 115,260 2 1,925.0 228 0 21 3 19 0 43,250 1,575,900 6,770,818 8,389,968 26,000 31,000 8,446,968 2,111,742 10,558,710Plovdiv Karavelovo 125 19,549 11,357 N/A 0.0 18,133 2 5,600 1 48.0 43 0 6 0 2 0 25,825 98,200 372,502 496,527 1,225 500 498,252 124,563 622,815Plovdiv Plovdiv 127 68,666 51,377 Polatovo weir 10.0 67,556 0 0 0 3,000.0 80 0 7 0 10 150,000 38,500 599,500 4,309,417 5,097,417 7,450 0 5,104,867 1,276,217 6,381,084Plovdiv Rozino 126 7,196 1,000 Saraysoyu WI 0.3 10,507 0 0 0 0.0 24 0 2 0 0 0 22,000 65,500 251,015 338,515 0 0 338,515 84,629 423,144

Sliven Sredna Tundzha 155 331,168 256,983 Binkos weir intake,Mechkarevo weir, Thebridge of Samuilovo intake 47.0 198,801 0 400,000 6 4,390.0 213 3 23 4 14 0 41,299 3,571,330 19,809,165 23,439,794 1,275,570 19,500 24,714,864 6,178,716 30,893,580

Stara Zagora Stara Zagora 169 355,606 337,677Saltachnitsa RI, Stara RI, Maglizhka RI,Dabovska RI, Tundzha RI (serving YagodaPS) , Suytliyka RI

0.8 222,400 0 0 3 3,965.0 491 5 75 0 11 27,000 49,900 3,370,500 21,265,441 24,712,841 71,800 106,220 24,890,861 6,222,715 31,113,576

Yambol Sredna Tundzha 243 141,216 136,679 N/A 0.0 21,575 1 855 0 0.0 12 0 1 0 8 0 10,000 341,000 2,210,503 2,561,503 40,000 0 2,601,503 650,376 3,251,879Sub Total 1,060,300 865,641 Sub Total 58.1 667,762 5 521,715 12 13,328.0 1,091 8 135 7 64 177,000 230,774 9,621,930 54,988,861 65,036,565 1,422,045 157,220 66,595,830 16,648,958 83,244,788

Burgas Tserkovski 6 6,362 3,664 Azmak RI 2.0 8,660 1 6,500 0 0.0 4 0 3 0 0 0 12,000 51,600 340,941 404,541 0 0 404,541 101,135 505,676Burgas Kayabash 8 26,105 24,970 N/A 0.0 15,911 6 12,266 0 0.0 10 0 0 0 6 0 22,000 99,200 738,068 859,268 5,000 2,500 866,768 216,692 1,083,460Haskovo Brod IA 197 6,687 N/A 0.0 7,740 0 0 1 1,400.0 29 0 2 0 0 0 0 169,000 175,974 344,974 52,000 56,000 452,974 113,244 566,218Haskovo Ezerovo IA 195 11,704 4,144 Varbishka RI 0.7 17,231 1 5,500 0 0.0 26 0 3 0 4 0 18,000 82,000 463,746 563,746 11,000 0 574,746 143,687 718,433Haskovo Dimitrovgrad IA 198 1,557 N/A 0.0 890 0 0 1 1,000.0 1 0 2 1 0 0 4,000 115,000 34,000 153,000 27,000 38,000 218,000 54,500 272,500Haskovo Trakiets-VІІ 193 65,387 64,387 Banska RI 0.8 0 1 25,000 6 2,810.0 0 0 0 0 0 0 17,000 295,800 0 337,800 44,800 192,400 575,000 143,750 718,750Haskovo Garvanovo IA 194 8,035 7,001 N/A 0.0 0 0 0 2 918.0 0 0 0 0 0 0 0 20,000 0 20,000 2,000 15,000 37,000 9,250 46,250Haskovo Bolyartsi IA 241 2,000 2,000 N/A 0.0 0 1 260 0 0.0 0 0 0 0 0 0 0 0 0 2,600 0 0 2,600 650 3,250Haskovo Nevestino IA 234 506 506 N/A 0.0 1,898 0 7 1 140.0 0 0 0 0 0 0 8,500 66,000 0 74,500 0 18,000 92,500 23,125 115,625Haskovo Zvinitsa IA 224 4,282 4,282 N/A 0.0 0 1 1,230 0 0.0 0 0 0 0 0 0 0 59,000 0 59,000 50,000 5,000 114,000 28,500 142,500Haskovo Prileptsi IA 230 3,870 3,870 N/A 0.0 0 0 0 2 680.0 0 0 0 0 0 0 5,000 17,000 0 22,000 5,500 4,000 31,500 7,875 39,375Haskovo Daskalovo-Yavoritsa IA 222 1,700 N/A 0.0 0 1 371 0 0.0 0 0 0 0 0 0 0 0 0 3,710 0 0 3,710 928 4,638Haskovo Petelovo IA 220 3,805 3,341 N/A 0.0 0 2 705 0 0.0 0 0 0 0 0 0 0 25,000 0 25,000 5,000 0 30,000 7,500 37,500Haskovo Minzuhar IA 227 1,593 1,593 N/A 0.0 0 1 560 0 0.0 0 0 0 0 0 0 0 0 0 5,600 0 0 5,600 1,400 7,000Haskovo Dyadovsko IA 228 2,548 2,548 N/A 0.0 0 1 544 0 0.0 0 0 0 0 0 0 8,000 0 0 8,000 5,000 0 13,000 3,250 16,250Haskovo Zagorsko IA 236 570 440 N/A 0.0 0 0 0 1 84.0 0 0 0 0 0 0 0 16,500 0 16,500 16,000 0 32,500 8,125 40,625Haskovo Iskril IA 237 1,250 1,250 N/A 0.0 0 0 0 1 56.0 0 0 0 0 0 0 0 70,000 0 70,000 25,000 25,000 120,000 30,000 150,000Haskovo Dobromirtsi-Benkovski 232 15,383 15,383 N/A 0.0 443 1 8,000 0 0.0 0 0 0 0 5 0 8,000 48,000 17,199 73,199 15,000 0 88,199 22,050 110,249Haskovo Parvitsa IA 233 2,698 2,298 Drainage WI Parvitsa 0.2 0 0 0 1 100.0 0 0 0 0 0 0 6,000 40,000 0 46,000 10,000 30,000 86,000 21,500 107,500Haskovo Gruevo IA 235 1,645 1,645 N/A 0.0 0 0 0 1 210.0 0 0 0 0 0 0 0 96,000 0 96,000 21,000 25,000 142,000 35,500 177,500Haskovo Momina salza IA 238 1,060 910 N/A 0.0 0 1 175 0 0.0 0 0 0 0 0 0 0 0 0 2,000 0 0 2,000 500 2,500Haskovo Nanovitsa IA 226 3,400 3,400 N/A 0.0 0 2 1,025 0 0.0 0 0 0 0 0 0 0 20,000 0 20,000 0 0 20,000 5,000 25,000Haskovo Lale IA 225 2,350 2,350 Drainage WI Nanovishka river 100.0 0 1 350 1 84.0 0 0 0 0 0 0 5,000 0 0 8,500 0 0 8,500 2,125 10,625Haskovo Karamfil-Sindeltsi IA 223 1,875 1,570 N/A 0.0 0 1 572 0 0.0 0 0 0 0 0 0 5,000 0 0 5,000 0 0 5,000 1,250 6,250Haskovo Kamenyane IA 240 800 800 Drainage WI Krumovitsa river 60.0 0 0 0 2 104.0 0 0 0 0 0 0 5,000 60,000 0 65,000 16,000 24,000 105,000 26,250 131,250Haskovo Strandzhevo IA 221 3,820 3,820 N/A 0.0 0 0 0 1 342.0 0 0 0 0 0 0 0 24,000 0 24,000 12,000 2,000 38,000 9,500 47,500Haskovo Knizhovnik IA 188 8,390 3,146 N/A 0.0 9,386 1 2,516 0 0.0 25 0 4 0 0 0 12,000 140,400 242,236 394,636 20,000 0 414,636 103,659 518,295Haskovo Sirakovo IA 189 5,220 3,840 N/A 0.0 1,811 1 2,172 0 0.0 2 0 0 0 0 0 0 17,500 45,467 62,967 10,000 0 72,967 18,242 91,209Haskovo Mandra IA 187 4,640 4,640 N/A 0.0 0 1 1,498 0 0.0 0 0 0 0 0 0 3,000 111,000 0 114,000 10,000 0 124,000 31,000 155,000Haskovo Krivo pole IA 190 8,660 8,660 N/A 0.0 0 1 2,820 1 354.0 0 0 0 0 0 0 10,000 15,200 0 25,200 7,100 11,000 43,300 10,825 54,125Haskovo Gledka IS 191 6,640 N/A 0.0 0 1 2,320 0 0.0 0 0 0 0 0 0 0 31,100 0 31,100 10,000 0 41,100 10,275 51,375Haskovo Troyan-Navasen 202 10,640 N/A 0.0 0 1 6,000 2 572.0 0 0 0 0 0 0 0 203,000 0 263,000 40,000 81,000 384,000 96,000 480,000Haskovo Polyanovo 204 10,970 10,970 N/A 0.0 0 0 8 1 800.0 0 0 0 0 0 0 5,000 130,000 0 135,000 50,000 50,000 235,000 58,750 293,750Haskovo Izvorovo 201 11,490 7,348 N/A 0.0 0 1 3,810 0 0.0 0 0 0 0 0 0 6,000 22,000 0 28,000 12,000 5,000 45,000 11,250 56,250Haskovo Dositeevo 200 30,482 26,255 N/A 0.0 0 1 9,000 1 1,350.0 0 0 0 0 0 0 0 150,000 0 240,000 40,000 70,000 350,000 87,500 437,500Haskovo Oreshets 203 7,400 7,400 N/A 0.0 0 0 12 0 0.0 0 0 0 0 0 0 6,000 0 0 6,000 0 0 6,000 1,500 7,500Haskovo Preslavets 205 8,451 N/A 0.0 12,000 0 0 1 1,050.0 8 0 3 0 0 0 0 127,000 371,325 498,325 25,000 30,000 553,325 138,331 691,656Haskovo Harmanli-greenhouse 207 1,880 N/A 0.0 3,950 0 0 1 245.0 12 0 0 0 0 0 0 48,000 70,225 118,225 5,000 20,000 143,225 35,806 179,031Haskovo Harmanli drop 206 936 N/A 0.0 0 0 0 1 64.0 0 0 0 0 0 0 0 40,000 0 40,000 10,000 25,000 75,000 18,750 93,750Haskovo Biser 209 35,377 10,590 N/A 0.0 42,832 3 2,070 1 1,660.0 31 0 7 0 1 0 0 230,000 2,122,076 2,363,776 10,000 0 2,373,776 593,444 2,967,220Haskovo Novo selo 211 9,006 N/A 0.0 8,160 0 5 1 880.0 48 0 1 0 0 0 3,000 209,000 255,062 467,062 30,000 50,000 547,062 136,766 683,828Haskovo Momkovo 212 17,091 5,572 N/A 0.0 12,049 0 0 1 1,260.0 1 0 5 0 0 0 0 78,500 340,471 418,971 5,000 0 423,971 105,993 529,964Haskovo Svilengrad 210 1,980 N/A 0.0 3,340 0 0 0 0.0 12 0 0 0 1 0 0 16,000 62,315 78,315 0 0 78,315 19,579 97,894Haskovo Lyubimets-1 217 8,100 N/A 0.0 7,600 0 0 1 800.0 14 0 2 0 0 0 0 60,000 207,920 267,920 0 0 267,920 66,980 334,900Haskovo Gugutka 215 3,583 1,188 Arpa dere RI 280.0 0 0 0 1 280.0 0 0 0 0 0 0 10,000 20,000 0 30,000 5,000 10,000 45,000 11,250 56,250Haskovo Dolno Lukovo 216 895 895 N/A 0.0 0 0 0 1 130.0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0Haskovo Mandaritsa 219 1,411 N/A 0.0 0 0 0 1 200.0 0 0 0 0 0 0 0 80,000 0 80,000 30,000 30,000 140,000 35,000 175,000Haskovo Bunarcha-Kapitan 208 4,720 2,932 N/A 0.0 0 1 2,336 0 0.0 0 0 0 0 0 0 0 0 0 23,360 0 0 23,360 5,840 29,200Pazardzhik Varvara 72 73,517 37,210 Vetren dol WI, Eli dere RI 5.2 64,104 0 0 0 0.0 183 0 39 0 23 0 51,081 907,000 3,181,067 4,139,148 29,765 0 4,168,913 1,042,228 5,211,141

Pazardzhik Velingrad 75 17,582 6,664 Kleptuza WI, Velingrad-2 PS WI, Maneroviskali WI 1.3 61,484 1 1,105 1 990.0 70 0 34 0 12 30,000 22,401 512,820 1,807,422 2,372,643 37,611 43,000 2,453,254 613,314 3,066,568

Pazardzhik Peshtera 74 35,968 18,959 Gerena WI, Kozarski ark WI, GG 0.0 36,337 0 0 0 0.0 97 0 3 0 2 20,000 20,900 245,500 1,255,287 1,541,687 4,440 0 1,546,127 386,532 1,932,659Plovdiv Domlyan 128 70,816 35,494 Kurtovo WI 7.5 57,244 3 28,914 0 0.0 82 0 13 3 11 0 66,620 585,000 2,933,579 3,585,199 1,000 1,060 3,587,259 896,815 4,484,074Plovdiv Chaya 1233 57,237 32,458 N/A 0.0 78,119 1 70 0 0.0 179 0 7 0 0 0 12,000 591,800 4,006,432 4,610,232 60,000 0 4,670,232 1,167,558 5,837,790Plovdiv Popovitsa 1246 38,484 24,751 Cherkezitsa WI 1.2 39,964 0 0 2 4,600.5 99 0 17 0 2 0 0 480,000 1,637,589 2,117,589 0 50,000 2,167,589 541,897 2,709,486Plovdiv Sushitsa 1232 19,925 15,465 N/A 0.0 4,750 1 4,600 0 0.0 8 0 1 0 0 0 0 106,000 175,449 281,449 50,000 15,000 346,449 86,612 433,061Plovdiv Bryagovo 1242 29,519 16,669 N/A 0.0 25,466 1 9,050 0 0.0 57 0 7 0 0 0 7,000 239,500 1,022,899 1,269,399 10,000 0 1,279,399 319,850 1,599,249Plovdiv Vacha 122 115,852 75,385 Krichim WI, Bash weir WI 68.5 128,250 0 0 0 0.0 229 3 25 0 4 0 30,000 1,430,500 8,267,713 9,728,213 90,000 30,000 9,848,213 2,462,053 12,310,266Plovdiv 40-te izvora 1231 27,495 27,253 N/A 0.0 13,202 1 3,800 0 0.0 45 0 2 0 0 0 3,000 139,000 487,934 667,934 0 0 667,934 166,984 834,918Plovdiv Lenovo 1244 26,178 23,228 N/A 0.0 12,250 2 7,780 0 0.0 26 0 10 0 0 0 0 133,000 1,415,000 1,625,800 0 0 1,625,800 406,450 2,032,250Plovdiv Mechka 1243 35,238 14,023 N/A 0.0 19,578 1 6,800 1 0.0 24 0 16 0 0 0 5,200 257,900 767,852 1,030,952 0 0 1,030,952 257,738 1,288,690Plovdiv Parvomay 124 46,451 24,254 Beliya kamak WI 1.2 30,934 2 229 2 4,460.0 43 0 11 0 1 0 26,000 259,500 1,045,874 1,331,374 50,000 0 1,381,374 345,344 1,726,718Sofia Ihtiman gravity 162 39,013 39,013 Baba RI (to B. dere) 1.2 21,578 1 11,100 0 0.0 12 0 0 8 0 0 8,000 92,000 783,212 894,212 0 0 894,212 223,553 1,117,765Stara Zagora Dobri Dol 171 13,279 10,854 N/A 0.0 3,228 1 3,465 4 1,754.0 0 0 2 0 0 0 27,000 130,000 126,543 283,543 79,800 37,500 400,843 100,211 501,054Stara Zagora Naydenovo 173 2,412 1,395 N/A 0.0 6,203 1 800 0 0.0 20 0 0 0 0 0 11,400 22,000 120,526 153,926 2,000 0 155,926 38,982 194,908Stara Zagora Dolno Novo Selo 174 3,888 3,138 N/A 0.0 6,000 1 1,200 1 50.0 12 0 2 0 0 0 4,000 20,000 96,126 132,126 0 0 132,126 33,032 165,158Stara Zagora IP-Chirpan PS IA 172 3,590 602 N/A 0.0 0 1 455 0 0.0 0 0 0 0 0 0 0 0 0 4,550 0 0 4,550 1,138 5,688Stara Zagora Yulievo 170 6,381 6,381 N/A 0.0 2,896 0 0 1 630.0 5 0 1 0 1 0 0 74,200 180,000 254,200 3,600 200 258,000 64,500 322,500Yambol Bolyarovo 246 49,754 49,754 N/A 0.0 4,573 2 44,860 0 0.0 2 0 1 0 0 0 12,000 44,400 317,051 373,451 6,000 3,000 382,451 95,613 478,064Yambol Elhovo 245 39,954 22,120 Popovska RI 2.0 29,915 1 12,600 4 1,550.0 6 0 2 1 0 0 19,600 96,270 856,098 971,968 41,350 25,620 1,038,938 259,735 1,298,673Yambol Yambol 244 23,419 23,419 Zaporna vrata intake 5.0 37,635 1 2,770 1 1,000.0 15 0 1 1 0 0 8,600 129,500 1,848,501 1,989,601 6,000 0 1,990,601 497,650 2,488,251

Sub Total 1,154,906 758,097 Sub Total 536.8 837,611 56 237,229 53 32,607.5 1,437 3 226 14 73 50,000 513,302 9,598,690 37,819,179 48,354,991 1,112,966 1,024,280 50,487,237 12,621,809 63,109,046

Total 3,164,686 2,190,414 Total 663.0 2,245,292 68 1,109,264 67 47,426 3,996 112 514 34 251 327,000 993,040 33,180,970 143,323,791 178,216,621 4,734,799 1,697,000 184,623,420 46,155,855 230,779,275

Priority

3

2

1

Pump station

Distributionstructures:

DS

Reservoir Other structures on the canal (number)

Siphon:S

Tunnel:T

Aqueduct:A

Volume(103 m3)

Totalcapacity(liter/sec)

TOTALcost

Number ofDam

Number ofPump

Type of rehabilitation Cost for rehabilitation 10 % design,5 % for control

acuities,10 % physicalcontingency

Distributionpoints:

DP

Required cost for improvement (EURO)Intake structure:ITS

Regional Branch Irrigation System:IS IS_ID Name of intake

( RI : River Intake , WI : Water Intake)Length

(m)Capacity

(m3/s)

Suitablearea

(dka=0.1ha)

Potentialarea

(dka=0.1ha)




Table 6.3.3 Rehabilitation of Irrigation System List (WABD)

Irrigationcanal

New Intakestructure

RenovationITS, DP, DS,

S, T, A

RehabilitationITS, DP, DS,

S, A, T

Lining ofcanal Const. cost Machinery

costElectricity

cost TOTAL

Gotse Delcev Gotse Delchev 56 50,818 39,130Gospodintsi village water intake, Tufchariver intake-MIC-4, Toplika river intake-MIC-8 and MIC-9

19.4 85,910 0 0 1 280 114 0 14 6 10 0 5,000 793,500 4,325,100 5,123,600 25,000 7,500 5,156,100 1,289,025 6,445,125

Pernik Svircha IC IA 91 614 614 Svircha water intake 0.1 6,357 0 0 0 0 10 0 0 0 0 0 5,300 59,500 65,189 129,989 32,000 0 161,989 40,497 202,486Pernik Dragovishtitsa 99 13,562 10,657 Dragovishtitsa water intake 2.5 33,490 1 150 0 0 66 0 2 0 1 0 4,000 232,500 1,308,088 1,544,588 113,000 12,000 1,669,588 417,397 2,086,985Pernik Yamborano IA 85 2,038 1,831 N/A 0.0 9,052 0 0 0 0 28 0 4 0 0 0 10,000 60,000 212,782 282,782 7,500 0 290,282 72,571 362,853Pernik Stensko PS IA 101 1,141 874 Stensko water intake 0.4 5,112 0 0 1 400 37 0 1 0 0 0 4,000 68,000 95,402 167,402 6,000 500 173,902 43,476 217,378Pernik Razhdavitsa PS IA 81 1,933 1,609 Razhdavitsa PS water intake 0.4 5,031 0 0 1 440 17 0 1 0 0 0 10,000 47,000 90,972 147,972 11,500 0 159,472 39,868 199,340

Pernik Kopilovski gravitychannel IC IA 87 5,913 5,913 Struma water intake 3.0 19,567 0 0 1 2,100 25 0 7 0 0 0 45,000 520,000 569,706 1,134,706 132,000 200,000 1,466,706 366,677 1,833,383

Pernik Konyavo IC IA 110 5,858 5,858 Konyavski gravity channel water intake 1.4 19,391 0 0 0 0 51 0 2 0 0 0 13,000 131,000 698,086 842,086 0 0 842,086 210,522 1,052,608Pernik Dolna Grashtitsa PS IA 88 1,430 N/A 0.0 267 0 0 0 0 0 0 0 0 0 0 0 5,000 0 5,000 0 0 5,000 1,250 6,250Pernik Katrishte PA IA 89 1,755 Girchevtsi water intake 2.0 3,205 0 0 2 1,090 7 0 0 0 0 0 0 278,500 90,000 368,500 24,000 176,500 569,000 142,250 711,250Pernik Lozno IA PS 84 2,100 2,100 Nov chiflik PS water intake 0.2 0 0 0 1 230 0 0 0 0 0 0 12,000 49,000 0 61,000 28,000 17,000 106,000 26,500 132,500Pernik Nevestino PS IA 83 1,396 896 Nevestino PS water intake 0.8 3,835 0 0 1 615 11 0 1 0 0 0 15,200 21,500 65,244 101,944 18,000 0 119,944 29,986 149,930Pernik Chetirtsi PS IA 108 849 609 Chetirtsi PS water intake 0.4 960 0 0 1 100 2 0 0 0 0 100,000 0 48,400 19,704 168,104 17,000 11,000 196,104 49,026 245,130

Pernik Gorna Grashtitsareservoir IA 100 1,521 1,521 N/A 0.0 1,839 1 200 0 0 16 0 0 0 0 0 9,000 19,000 21,862 49,862 11,200 0 61,062 15,266 76,328

Pernik Nikolichevska vada IC 104 100 100 N/A 0.0 1,858 0 0 0 0 3 0 0 0 0 0 0 6,000 20,289 26,289 0 0 26,289 6,572 32,861Pernik Dromuharska vada IC IA 105 248 248 N/A 0.0 5,110 0 0 0 0 5 0 0 0 0 0 0 8,000 72,144 80,144 0 0 80,144 20,036 100,180Pernik Drenov dol IA 96 12,288 8,180 Banska river water intake 1.0 11,277 2 3,505 0 0 2 0 0 0 0 0 13,000 34,000 198,757 245,757 30,000 0 275,757 68,939 344,696Pernik Bersin-Bagrentsi IA 86 20,193 18,544 M-1 Bersin water intake, Granitsa water 0.5 46,111 2 6,800 0 0 142 0 13 0 0 20,000 10,000 313,500 1,036,696 1,380,196 56,700 3,000 1,439,896 359,974 1,799,870Pernik Belia kamak IC IA 107 241 161 N/A 0.0 13,717 0 0 0 0 7 0 0 0 0 0 2,000 35,500 133,822 171,322 1,800 0 173,122 43,281 216,403

Sandanski Sandanska Bistritsa 154 37,495 31,754Water intake to HPP Sandanskicompensating basin 0.0 68,160 1 960 1 800 73 0 0 6 0 0 23,775 243,000 1,910,255 2,177,030 122,400 5,000 2,304,430 576,108 2,880,538

Sandanski Mendovo-Kavrakirovo 146 3,080 3,080 N/A 0.0 8,500 0 0 0 0 0 0 1 4 0 0 0 36,000 242,576 278,576 12,700 0 291,276 72,819 364,095Sandanski Strumeshnitsa 147 12,733 7,500 Water intake Petrich MIC 1.5 14,608 0 0 0 0 9 0 1 4 8 0 0 165,000 577,596 742,596 20,450 0 763,046 190,762 953,808

Sub Total 177,306 141,179 Sub Total 33.7 363,357 7 11,615 10 6,055 625 0 47 20 19 120,000 181,275 3,173,900 11,754,270 15,229,445 669,250 432,500 16,331,195 4,082,799 20,413,994

Dupnitsa Boboshevo 61 15,873 12,574

Blazhievski IC water itnake, Usoyski ICwater intake, Polski reservoir IC waterintake, Buranovo PS water intake,Mursalevo PS water intake

3.1 35,710 0 0 3 1,450 127 0 6 2 8 42,000 52,000 373,000 853,719 1,320,719 28,000 0 1,348,719 337,180 1,685,899

Dupnitsa Rila 62 27,330 23,614Gl. Rilski IC water intake, Drachka ditch ICwater intake, Glaven Porominovski ICwater intake

3.5 43,106 0 0 0 0 98 0 12 13 12 82,000 10,000 314,000 1,405,913 1,811,913 0 0 1,811,913 452,978 2,264,891

Dupnitsa Dupnitsa 60 26,526 16,807Arakchiyski IC water intake, GlavenGyurgevski IC water intake 1.2 35,226 0 0 0 0 71 1 8 17 4 76,000 2,500 216,000 759,748 1,054,248 0 0 1,054,248 263,562 1,317,810

Dupnitsa Dyakovo reservoir 59 18,234 18,234Bistritsa derivation water intake, Otovitsariver intake 3.4 36,955 1 35,400 0 0 4 4 5 8 6 0 20,000 515,000 250,636 785,636 69,000 0 854,636 213,659 1,068,295

Dupnitsa Blagoevgrad 63 16,029 15,129

Lyav Blagoevgrad MIC water intake,Tuhlarska ditch IC water intake, Tsentralnaditch IC water intake, Water intake to Belopole PS , Zelen dol PS water intake,

2.3 22,500 0 0 4 2,155 27 0 2 0 3 190,000 25,500 99,000 499,902 814,402 11,840 2,500 828,742 207,186 1,035,928

Gotse Delcev Razlog 58 28,692 18,428 N/A 4.6 24,290 1 110 0 0 92 0 4 0 0 0 0 202,000 629,365 831,365 2,000 0 833,365 208,341 1,041,706Sandanski Pirinska Bistritsa 150 38,721 38,721 MIC Pirinska Bistritsa water intake 0.0 73,433 0 0 1 700 174 0 15 4 23 0 14,600 914,380 2,978,351 3,907,331 62,000 0 3,969,331 992,333 4,961,664Sandanski Kozhuh 145 16,128 14,000 N/A 0.0 9,800 0 0 1 1,400 11 0 1 0 0 0 0 72,100 399,489 471,589 13,500 1,600 486,689 121,672 608,361Sandanski Valtata 148 4,738 4,738 N/A 0.0 0 1 900 0 0 0 0 0 0 0 0 0 14,000 0 14,000 14,000 0 28,000 7,000 35,000Sandanski Svoboda 144 10,100 10,100 N/A 0.0 9,460 0 0 1 2,000 0 0 2 1 10 0 0 81,600 227,678 309,278 17,300 0 326,578 81,645 408,223

Sub Total 202,371 172,345 Sub Total 18.0 290,480 3 36,410 10 7,705 604 5 55 45 66 390,000 124,600 2,801,080 8,004,801 11,320,481 217,640 4,100 11,542,221 2,885,555 14,427,776Dupnitsa Leshko 64 31,825 28,512 N/A 0.0 9,050 0 0 0 0 3 0 4 0 0 0 0 65,000 426,385 491,385 300 0 491,685 122,921 614,606Gotse Delcev Ablanitsa 57 2,500 1,950 N/A 0.4 0 0 0 1 350 0 0 0 0 0 0 0 30,000 0 30,000 0 30,000 60,000 15,000 75,000Pernik Begunovtsi IA 109 3,000 3,000 Begunovtsi reservoir water intake 0.4 1,658 2 1,554 0 0 0 0 2 0 0 0 19,500 14,500 37,307 71,307 0 0 71,307 17,827 89,134Pernik Dolna Dikanya 76 27,379 25,879 N/A 0.0 4,000 1 7 0 0 0 0 1 0 0 0 3,000 176,500 128,960 308,460 0 0 308,460 77,115 385,575Pernik Izvor 77 18,917 17,817 Izvor reservoir water intake 0.0 10,700 1 7 0 0 14 0 0 0 0 0 10,000 288,000 354,642 652,642 3,000 0 655,642 163,911 819,553Pernik Pchelina 79 18,167 18,167 N/A 0.0 24,761 2 55,325 1 4,125 0 0 11 2 2 0 1,000 385,000 1,631,556 2,028,806 0 0 2,028,806 507,202 2,536,008Pernik Yardzhilovtsi 78 8,003 8,003 Yardzhilovtsi water intake 0.8 0 1 1 1 786 0 0 0 0 0 0 3,000 19,000 0 22,000 0 0 22,000 5,500 27,500Sandanski Ograzhden 153 4,360 4,360 N/A 0.0 19,960 0 0 1 200 40 0 17 0 0 0 0 250,000 692,016 942,016 10,000 0 952,016 238,004 1,190,020Sandanski Asen Itov 152 13,555 13,555 N/A 0.0 29,540 0 0 2 1,700 35 0 10 3 4 0 11,020 214,000 899,907 1,124,927 61,000 0 1,185,927 296,482 1,482,409

Sub Total 127,706 121,243 Sub Total 1.5 99,669 7 56,895 6 7,161 92 0 45 5 6 0 47,520 1,442,000 4,170,773 5,671,543 74,300 30,000 5,775,843 1,443,961 7,219,804

Total 507,383 434,767 Total 53.2 753,506 17 104,919 26 20,921 1,321 5 147 70 91 510,000 353,395 7,416,980 23,929,844 32,221,469 961,190 466,600 33,649,259 8,412,315 42,061,574

3

Totalcapacity(liter/sec)

1

2

Number ofDam

Volume(103 m3)

Cost for rehabilitation Distribution points:

DP

10 % design,5 % for control

acuities,10 % physicalcontingency

Reservoir Other structures on the canal (number)

Distribution

structures:DS

Siphon:S

Tunnel:T

Aqueduct:A

Number ofPump

TOTALcost

Priority Regional Branch Irrigation System:IS IS_ID

Potentialareadka

Suitableareadka

Required cost for improvement (EURO)

Type of rehabilitation

Pump stationIntake structure:ITS

Name of intake( RI : River Intake , WI : Water Intake)

Capacity(m3/s)

Length(m)

6.4

6.5

6.6

6.7

6.8




Table 6.8.1 Summary of the Proposed Programme of Measures for Water Quality and Water Quantity Improvement and Management

Cat

egor

y St

ruct

ural

Mea

sure

s N

on-s

truct

ural

Mea

sure

s 1. W

ater

Qua

lity

Impr

ovem

ent

and

Man

agem

ent

1)

EABD

hig

h pr

iorit

y to

wns

•

New

WW

TPs:

17 to

wns

•

Ren

ovat

ion

of th

e ex

istin

g W

WTP

s: 4

tow

ns

• Im

prov

e. /

expa

nsio

n / n

ew s

ewer

net

wor

ks:

22 to

wns

•

Con

stru

ctio

n co

st

WW

TPs (

new

& re

nova

tion)

: EU

R 2

06 m

il.

Sew

er n

etw

orks

: EU

R. 1

628

mil.

Su

b-to

tal:

EUR

. 183

4 m

il.

2)

WA

BD

hig

h pr

iorit

y to

wns

•

New

WW

TPs:

6 to

wns

•

Ren

ovat

ion

of th

e ex

istin

g W

WTP

s: 3

tow

ns

• Im

prov

e. /

Expa

nsio

n / N

ew S

ewer

Net

wor

ks:

9 to

wns

•

Con

stru

ctio

n C

ost

WW

TPs (

New

& R

enov

atio

n):

EUR

72

mil.

Se

wer

Net

wor

ks:

EUR

. 537

mil.

Su

b-to

tal:

EUR

. 609

mil.

3)

Impl

emen

tatio

n sc

hedu

le:

Ye

ar 2

011

to 2

018

1)

Coo

pera

tion

with

mun

icip

ality

for w

ater

qua

lity

man

agem

ent.

• R

ecom

men

dabl

e to

star

t fro

m s

ome

pilo

t m

unic

ipal

ities

for m

onito

ring

wor

ks.

2)

Stre

ngth

enin

g of

regu

latio

n fo

r was

tew

ater

disc

harg

e.

• Fr

om In

dust

ries

and

Big

Ani

mal

Bre

edin

g Fi

rms.

3)

Impr

ovem

ent o

f sur

face

mon

itorin

g sy

stem

for w

ater

qu

ality

. •

To e

nsur

e st

able

mon

itorin

g, se

lect

ion

of K

ey

and

Impo

rtant

Mon

itorin

g Zo

nes /

Sta

tions

and

m

easu

re w

ith m

unic

ipal

ities

. •

Cap

acity

bui

ldin

g an

d st

age-

wis

eim

plem

enta

tion

of th

e ne

w m

onito

ring

prog

ram

. •

Qua

lity

cont

rol p

rogr

am to

be

form

ulat

ed a

nd

impl

emen

ted.

2. W

ater

Qua

ntity

Im

prov

emen

t an

d M

anag

emen

t

2.1

Impr

ovem

ent o

f Wat

er S

uppl

y Sy

stem

s 1)

R

epla

cem

ent o

f wat

er su

pply

pip

es

• W

hole

Bul

garia

: ab

out 6

2,28

8, 0

00 m

•

Tota

l cos

t: ab

out E

UR

11,

809

mill

ion

2)

Long

-term

and

to b

e st

arte

d as

soon

as p

ossib

le.

2.2

Impr

ovem

ent o

f Irr

igat

ion

Syst

ems

Impr

ovem

ent o

f int

ake,

wat

er tr

ansf

er a

nd d

istri

butio

n fa

cilit

ies:

1)

EABD

•

5 Irr

igat

ion

Syst

ems i

n 3

Irrig

atio

n Br

anch

es.

• C

onst

ruct

ion

Cos

t: EU

R. 8

4 m

il.

2)

WA

BD

• 5

Irrig

atio

n Sy

stem

s in

3 Irr

igat

ion

Bran

ches

. •

Con

stru

ctio

n C

ost:

EUR

. 20

mil.

3)

Impl

emen

tatio

n sc

hedu

le:

Year

201

1 to

201

8

1)

Rev

iew

and

impr

ovem

ent o

f wat

er u

se p

erm

issio

n fo

r opt

imum

wat

er u

se.

2)

Mon

itorin

g/m

easu

rem

ent o

f wat

er in

take

vol

ume.

3)

Im

prov

emen

t of q

ualit

y of

dat

a re

quire

d fo

r wat

er

man

agem

ent.

Tabl

e 6.

8.1

Sum

mar

y of

the

Prop

osed

Pro

gram

me

of M

easu

res f

or W

ater

Qua

lity

and

Wat

er

Qua

ntity

Impr

ovem

ent a

nd M

anag

emen

t

chapter 3 gis database 3.1 introduction

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