attaining optimal sustainability for urban wastewater ... 119997106009...and imported in epanet...

ATTAINING OPTIMAL SUSTAINABILITY FOR

URBAN WASTEWATER MANAGEMENT-CASE

STUDY OF VADOARA URBAN DEVELOPMENT

ATUHTORITY AREA

A Synopsis submitted to Gujarat Technological University

for the Award of

Doctor of Philosophy

in

Civil Engineering

by

Devang Arvindbhai Shah

[119997106009]

under supervision of

Dr. Dilip Trimbak Shete

GUJARAT TECHNOLOGICAL UNIVERSITY

AHMEDABAD

[March – 2018]

Attaining Optimal Sustainability for Urban Wastewater Management-Case Study of Vadodara

Urban Development Authority Area 2018

GUJARAT TECHNOLOGICAL UNIVERSITY 1

Contents:

a. Abstract…………………………………………………………………………………….2

b. Brief description on the state of the art of the research topic……………………………...3

c. Definition of the Problem………………………………………………………………….7

d. Objective and Scope of work………………………………………………………………8

e. Original contribution by the thesis…………………………………………………………8

f. Methodology of Research, Results / Comparisons…………………………………………9

g. Achievements with respect to objectives…………………………………………………25

h. Conclusion………………………………………………………………………………...26

i. List of all publications arising from the thesis…………………………………………….28

j. Patents (if any)……………………………………………………………………………..NA

k. References…………………………………………………………………………………30




Title of the Thesis

Attaining Optimal Sustainability for Urban Wastewater Management-Case

Study of Vadodara Urban Development Authority Area

a. Abstract

India has become water stressed nation since 2011. In the sanitation sector treatment

capacities exist for not more than even half of wastewater generated from class I and class II

cities and untreated wastewater is being discharged to water bodies without treatment. If

properly treated sewage is considered for safe reuse in industry, residential area and

agriculture it can save precious fresh water resources but this reuse should be optimally

sustainable. Weragala (2010) used several criteria to compare forms of water allocation such

as: (i) Flexibility in the allocation of supplies; (ii) Security of tenure for established users;

(iii) Real opportunity cost of providing the resource is paid by the users; (iv) Predictability of

the outcome of the allocation process; (v) Equity of the allocation process; and (vi) Political

and public acceptability. Out of these six criteria in the present study the criterion of real

opportunity cost of providing the resource is paid by the users is considered. For developing

and implementing the most appropriate approach to water pricing, and subsequently to a

sustainable water management, Frone (2012) emphasized on efficient water pricing. He

analyzed the basic economics in some important theoretical insights of water pricing and

discussed four inter-correlated principles of sustainable water pricing (full-cost recovery,

economic efficiency, equity and administrative feasibility). Full-cost recovery and economic

efficiency are considered by determining optimal sustainability for urban wastewater

management in the present study.

The Vadodara Urban Development Authority Area was considered as case study to evaluate

feasibility of urban wastewater reuse. Based on requirement of different quality criteria two

main reuse options were identified. The first option was to reuse in industry & residential

area and the second option was to reuse for irrigation purpose.

In water reuse scheme the main cost is for distribution network. To reduce the cost of

distribution network actual and exact friction factors to be used in Darcy-Weisbach equation

were determined from direct surface roughness measurement (Shah & Shete, 2015). Using

QGIS software and Ghydrualics plugin reclaimed water distribution networks were prepared

and imported in EPANET software. After preparing files for successful run by updating all

parameters like demands, elevation, surface roughness, supply from each sewage treatment




plant etc. the files were imported in WaterNetGen for design of network. Various

combinations of sewage treatment plants distribution network like all plants connected

network, group of three and two plants connected networks and each plant separate networks

were studied for optimal cost of reclaimed water distribution. For solving this reclaimed

water allocation problem Vogel‘s approximation method was used and problems were solved

using AMPL software. After getting optimum solution the networks were formed again with

allocated distribution from various plants and for these networks piping costs were calculated

by WaterNetGen. The cost of reuse of treated sewage water for different five scenarios was

considered as follows:

Scenario 1 : Considering all costs

Scenario 2 : Considering only Elevated Service Reservoir, Pump and Piping cost

Scenario 3 : Considering only O.M & R cost

Scenario 4 : Considering selling prices as per Sardar Sarovar Narmada Nigam Limited prices

Scenario 5 : Considering saved fresh water cost as per selling prices

The Internal Rate of Return (IRR) was calculated considering with and without negative price

of water for different scenarios. The sensitivity analysis and risk & uncertainty analysis were

carried out. The IRR value greater than 11% (Asian Development Bank Criteria) was

obtained for scenarios 1 & 5. IRR for scenario 1, with and without considering negative price

of water are 27.47% and 21.01% respectively. IRR for scenario 5, with and without

considering negative price of water are 32.88% and 26.42% respectively.

Thus considering full-cost recovery and economic efficiency in real opportunity cost of

providing the treated wastewater paid by the users of Vadodara Urban Development

Authority Area, is optimally sustainable.

b. Brief description on the state of the art of the research topic

Continued population growth and increased standards of living increase resource demands

beyond the ability of the planet to meet these demands using currently available technology.

This brings in the concept of sustainable development as an operating principal upon which

to evaluate enhanced water supply and wastewater management approaches.

The UN Report on ‗our common future‘ known as the Brundtland Report defined sustainable

development as ‗paths of progress which meet the needs and aspirations of the present

generation without compromising the ability of future generations to meet their

needs‘(Brundtland, 1987). Many definitions of sustainable development exist, but a useful




one is the balance between economic, environmental, and social considerations in the

selection and implementation of an approach to any issue—the so-called triple bottom line

(Daigger, 2007). Weragala (2010) used several criteria to compare forms of water allocation

such as: (i) Flexibility in the allocation of supplies; (ii) Security of tenure for established

users; (iii) Real opportunity cost of providing the resource is paid by the users; (iv)

Predictability of the outcome of the allocation process; (v) Equity of the allocation process;

and (vi) Political and public acceptability.

Flexibility in the allocation of supplies:

According to Chaturvedi et al. (2016) utilization of multiple water resources significantly

reduces the operating cost of a water network. Efficient use of water can reduce the water

usage cost and minimize the impact of waste water discharge on the environment. Process

integration techniques have been effectively utilized for optimizing water requirement in

batch as well as continuous processes (Klemeš, 2013). Dogaru and Lavric (2011) proposed a

procedure for optimization of the Water Network topology with an objective of fresh water

minimization.

Security of tenure for established users:

Hodgson (2016) pleaded that tenure arrangements determine how people, communities and

organizations gain access to the use of natural resources. Inadequate and insecure tenure

arrangements increase vulnerability, hunger and poverty and the risk of conflict while also

constraining economic growth. Water tenure is conceptualized as the relationship, whether

legally or customarily defined between people, as individuals or groups, w.r.t. water

resources.

Real opportunity cost of providing the resource is paid by the users:

Frone (2012) emphasized on efficient water pricing. He analyzed the basic economics in

some important theoretical insights of water pricing and discussed four inter-correlated

principles of sustainable water pricing (full-cost recovery, economic efficiency, equity and

administrative feasibility). Velazquez et al. (2013) presented a method for the simulation of

water pricing policies linked to water availability, and the design of efficient pricing policies

that incorporate the basin wise marginal value of water. Two approaches were applied:

priority-based simulation and economic optimization. Griffin (2006) pointed out that, better




pricing is probably the most underutilized tool to be used for solving water scarcity

problems.

In the absence of proper pricing of water, it is very difficult to arrive at the proper

opportunity cost of water resources. Therefore, it is proposed to use the shadow prices

reflecting the value of water (Young 2005; Velazquez et al. 2008).

Gilmont et al. (2012) suggested that blue water (irrigation water) can be used at a higher

opportunity cost in industrial and civic use so that it will fetch greater value per litre of

water.

The ‗‗negative pricing‘‘ in effect represents payment to high-volume consumers for taking

excess power off the grid, thus relieving overload. Occurrences of negative pricing have

been observed since the wholesale electricity markets have been operating, and occur during

periods of low demand, while generators are being kept in reserve for rapid engagement

when demand increases. In such situations power production may temporarily exceed

demand, potentially overloading the system. (Jones, 2014)

Equity of the allocation process:

In water resource management, the issue of the equity-efficiency trade-off has been explored

in a number of different contexts by Cochran and Ray (2009); Ward and Velázquez (2008);

and D‘Exelle et al. (2012).

Full-cost recovery and economic efficiency are considered by determining optimal

sustainability for urban wastewater management.

In light of increasing concerns about water supply availability, it is no longer appropriate to

consider treated municipal wastewater as a ―waste‖ that requires ―disposal‖, but rather as a

resource that can be put to beneficial use. This conviction in linking responsible engineering

and water sustainability has gained practical experience in many parts of the world(Levine,

Asano, & Leverenz, 2011). Water reuse is a growing practice in many regions of the world,

even in countries that are not typically considered to have problems with water

scarcity(Miller, 2006). Shah and Shete, (2013) presented the summary of the wastewater

recycling projects all over the world. The lessons learnt from centralized water reuse system

in urban areas were summarized in (Chen, et al. 2017). Various studies to find out costs and

benefits associated with water reuse are carried out worldwide (Herman, et al. 2017).




Varieties of feasibility study approaches and models for decision making regarding

implementation of reuse are available (Hernandez et al., 2006; Bixio, 2008,Urkiaga et al.,

2008; Sa-nguanduan and Nititvattananon, 2011)

The cost of reclaimed water distribution network depends on diameter of pipe which in turn

depends on friction factor of the pipe. The best method for friction factor determination is

Darcy-Weisbach equation followed by modified Hazen-Williams formula. Bombardelli &

Garci (2003) and Bennett & Glaser (2011) had shown that use of Hazen-Williams formula

have very limited range of applicability and may have very detrimental effect on pipe design.

So, obviously best alternative for all flow regime and all types of pipes is dimensionally

balanced Darcy-Weisbach equation. Many researchers had tried to evaluate validity of

Nikuradse work and find shortcomings; nevertheless Nikuradse sand-grain roughness

experiments have been the main reference on flow in rough pipes for over 60 years

(Sletfjerding & Gudmundsson 2003). At the time of inception itself the Colebrook-White

equation was in error by 3-5%, when compared with actual experimental data (Bhave 2006).

In recent years the use of the Colebrook–White equation for the computation of commercial

pipe friction factors, particularly for small-diameter pipes was discouraged by several

researchers (Yoo & Singh 2005). Instead they suggested using a power law with minor

modifications. But still usage of the formula is well prevalent as standard practice and

recently Mcgovern (2011) had updated the Moody‘s chart in vector graphics version.

However, significant breakthrough in finding shortcomings of these standard works had

been achieved by Bernuth & Wilson (1989) and Kandlikar (2005). Bernuth & Wilson

showed that Blasius equation and not Colebrook-White equation is an accurate predictor of

Darcy-Weisbach friction factor for small diameter plastic pipes for Reynolds numbers less

than 1,00,000. Kandlikar (2005) highlighted further need for research to establish perfect

understanding of the micro scale flow geometries. Taylor et al., (2006) has summarized

these developments in chronological order and predicted future path. A whole gamut of new

formulas had been proposed by Achanta et al. (2000), Yoo & Singh (2004), Yoo & Singh

(2005), Sonnad & Goudar, (2006), Winning & Coole (2009), Yang & Joseph (2009),

Ghanbari et al. (2011), Li et al. (2011), Dobrnjac (2012), Babajimopoulos & Terzidis

(2013) and so on. These formulas have resulted from regression analysis of results available

till date from published studies and minor modifications in patterns of equation without

major consideration to fundamental change in parameter definition or relationship. There are

several other approaches to solve pipe flow problems e.g. Ahsan (2014) had used




Computational Fluid Dynamics (CFD) modeling for numerical analysis of turbulent flow.

But significantly new approach has been proposed by Farshad et. al (2005) and (Afzal,

2007a & 2007b). Taylor et al. (2006) had also introduced six new terms to describe surface

roughness to be used for higher relative roughness in micro tubes and micro channels.

The work of Sletfjerding & Gudmundsson (2003) was pioneer to develop a method of

estimating the friction factor in pipes directly from measured values of the wall roughness.

They studied correlation between various measured surface roughness parameters and

measured friction factor. This was the research gap existing since times of Moody and

Colebrook. Farshad et al. (2005) used mean-peak-to-valley- height Rz in place of equivalent

surface roughness in Colebrook-White equation to calculate friction factor. Shah and Shete

(2015) determined friction factor for DI Pipes by Direct Surface Roughness Measurement.

Patel et al. (2017) used the same technique to determine friction factor for laterals of

sprinkler irrigation system.

c. Definition of the problem

About one third of the world‘s population currently lives in countries suffering from

moderate-to-high water stress. (UNEP, 2009) India has more than 17 % of the world‘s

population, but has only 4% of world‘s renewable water resources with 2.6% of world‘s land

area. There are further limits on utilizable quantities of water owing to uneven distribution

over time and space. (MoWR, 2012). If water reuse with reliable framework is implemented

in industrial and agricultural sectors, benefits of reducing stress on water resources and

utilization of nutrient value in treated wastewater without any adverse effect can be

achieved. To implement wastewater reuse, higher treatment capacity in terms of quality and

quantity is required.

As India do not have even primary sanitation facilities in all urban areas due to lack of funds,

the economic feasibility is most crucial factor in implementation of wastewater reuse. Water

allocation can be sustainable only when there is successful tradeoff amongst the priorities of

the stakeholders, social equity, economic returns & profitability, reliability of water supply

and sustenance of ecosystems.

Therefore it was decided to optimize sustainability for urban wastewater management

considering study of Frone (2012) regarding full-cost recovery & economic efficiency,

advice of Velazquez et al. (2013) on economic optimization, idea of ‗‗negative pricing‘‘




(Jones, 2014) and conclusion of Griffin (2006) that better pricing is probably the most

underutilized tool to be used for solving water scarcity problems.

d. Objective and Scope of work

Goal: To attain sustainable water reuse management by full-cost recovery, economic

efficiency & economic optimization considering an idea of ‗‗negative pricing‘‘.

Objective: To achieve optimal sustainability for urban wastewater management for

Vadodara Urban Development Authority Area

Criteria for evaluating this objective are:

Economic returns & profitability

Reliability of water supply

and

Specific (measurable) Indicators:

Amount of water being reused

Cost of distribution network

Selling price of reclaimed water

Internal Rate of Return

e. Original contribution by the thesis

Till date no study had been reportedly published to evaluate optimal sustainability of water

reuse project in India. The present research designed optimal reclaimed water distribution

network considering mean peak to valley height, Rz to determine friction factor which in turn

is used in EPANET and WaterNetGen softwares to design the distribution network and

ascertain the cost of the same. Considering Vadodara Development Authority Area as case

study, six present and proposed sewage treatment plants and one additional plant are used in

determining optimal allocation of reclaimed water by Vogel‘s approximation method using

AMPL software.




Real opportunity cost of providing the reclaimed water was calculated.

Following five scenarios were considered:

Scenario 1 : Considering all costs

Scenario 2 : Considering only Elevated Service Reservoir, Pump and Piping cost

Scenario 3 : Considering only O.M & R cost

Scenario 4 : Considering selling prices as per Sardar Sarovar Narmada Nigam Limited

Scenario 5 : Considering saved fresh water cost as per selling prices

For each scenario Internal Rate of Return (IRR) was calculated considering with and without

negative price of water. IRR more than 11% (as per Asian Development Bank‘s criteria)

supports the economic feasibility of the study.

f. Methodology of Research, Results

Study Area

The area around Vadodara city under jurisdiction of Vadodara Urban Development

Authority is considered in the present study.

Figure 1: Study Area

Data collection

From the VMSS data were collected for location, input and output parameters for different

sewage treatment plants, cost of treatment, present and future demands, population

forecasting etc. Population was projected using various established and latest techniques and




population to be served in VUDA area was considered as 13 lakhs as obtained by auto

regression method.

Specific (measurable) Indicator

a) Amount of water being reused

Mainly two type of uses were identified –

Agricultural reuse

Industrial and residential reuse.

The criteria for water reuse as given in various standards were studied and considered. The

amount of water being reused depends upon demands for industrial & residential reuse and

irrigational reuse. These demands had been worked out as explained on page 11 and amount

of water being reused was determined.

b) Cost of distribution network

The major part of the cost of distribution network depends on diameter of pipe. Diameter

depends on loss of head due to friction. Loss of head due to friction depends on friction

factor.

i) Friction factor

Since Moody published his world famous friction factor charts based on Colebrook-White

formula, engineering fraternity seems to be following it so religiously that the research gap

highlighted by Colebrook and Moody themselves way back in the last century, as an absence

of direct method for determination of roughness values for commercially available pipes, is

mostly forgotten with advent of time.

This issue was addressed and the improved methodology for determining friction factor by

direct measurement of surface roughness for different diameter cement mortar lined DI pipes

was developed.

c) Selling price of reclaimed water

Assuming the profit over the cost of distribution of treated water should be 15%, selling

price of reclaimed water was determined.

d) Internal Rate of Return

IRR is the interest rate at which the net present value of all the cash flows both positive and

negative over the period from a project equals to zero.

Based on cost analysis Internal Rate of Return was calculated.

To achieve the goal as stated earlier reclaimed water distribution network model was

formulated using QGIS and EPANET.




The proposed landuse map for Vadodara is obtained and superimposed on Google Earth view

of VUDA area.

Identification of Residential, Industrial and Agricultural Areas

The proposed land use map obtained from Vadodara Urban Development Authority

(VUDA) was superimposed on Google earth exactly by adjusting scale and matching

landmark points. After superimposing proposed land use map various areas had been

identified for industrial, residential and agricultural use as per land use zones shown in the

VUDA map for developing outskirt areas of Vadodara City. These areas were then marked

with different layers in Quantum GIS (QGIS) software as shown in Fig. 2.

Figure 2: The industrial and residential areas marked in light majenta and light burgundy colour

respectively surrounding Vadodara city as per proposed land use map 2031 for VUDA area

The areas were divided into small compartments so as to create one node for laying out of

proposed reclaimed water pipelines. The network of proposed reclaimed water pipeline was

prepared in QGIS using GHydraulics plug-in as shown in Figure 3.




Figure 3: The industrial and residential areas and proposed reclaimed water distribution network

from various sewage treatment plants in VUDA area

The locations of sewage treatment plants, agricultural zones, industrial and residential zones

were identified and the reclaimed water distribution networks from various sewage treatment

plants to these areas were prepared.

With seven sources available, question of what should be the optimal proportion of reclaimed

water distribution from various sources to different destination arose.

To solve this problem VAM (Vogel Approximation Method) as a special case of linear

programming with optimality checks was utilized.

Before doing distribution by VAM, primary distribution by visual observation based on

vicinity was carried out and network was prepared.

From QGIS details of area for industrial & residential and agricultural zones were obtained

and centroid of each area was taken to allocate node of pipe network.

Elevation of all nodes and lengths of all pipes were obtained from QGIS for networks. Using

Ghydraulics plug in input file in the .inp format was prepared from QGIS and imported in

EPANET for further analysis.

Considering per capita supply of reclaimed water to be 100 lit/day the demand for each

residential zone was found out. For determination of industrial demand case study of

Makarpura GIDC was taken. From VCCI directory listing of industries in Makarpura GIDC

was obtained. For each type of industries demand was identified and ultimate demand for




conglomeration was worked out. Agricultural demand was worked out considering banana

crop and drip irrigation system (Shete, 2000).

After importing .inp file from QGIS Ghydrualics plug in the .net file was prepared to be run

in WaternetGen ( an EPANET extension for sizing pipes using simulated annealing algorithm

of optimization). First of all separate networks for each treatment plant considered and design

of optimum size of pipes was carried out. Then considering spatial distribution of industrial

and residential zones, the integrated model was prepared. The cost of networks was worked

out considering material cost, cost for excavation, cost of lowering, laying and joining,

refilling the trenches, accessories etc. complete using GWSSB schedule of rates. As there

were several destinations and demand locations with demand and supply constraints the

distribution of treated wastewater from different sewage treatment plant formed an excellent

transportation problem.

VAM is considered to be the best method for solution of transportation problem which is a

special case for linear programming. To form transportation problem, transportation tableau

was required to be prepared and for that from each individual source cost/unit of

transportation to each destination was required to be found out.

In order to do this first networks with individual sources were prepared and then optimized.

After designing each of these networks cost of transportation from source to each destination

for all sources to all destinations were required to be found out.

For this purpose Elevated Service Reservoirs were required to be designed.

Using mass curve method ESRs were designed and costs of pump and ESR were found out.

For calculating cost of piping from each source to each destination the links involved in each

route were calculated and accordingly piping cost was arrived for each route.

Similarly pumping cost was calculated for each route considering head loss in each pipe and

elevation difference between concerned nodes. Calculation of O, M & R cost was carried out

using Maximum Accelerated Cost Recovery System method for depreciation.

As this was annual cost the capital cost was also required to be brought in annual format so

total capital cost of sewage treatment plants, tertiary treatment plant, pipe, ESR and pump

was multiplied with capital recovery factor using interest rate at 7% and then O,M & R cost

and annual capital cost were added. Knowing total supply from each source, the final

demand for each node, and transportation cost for each node, the transportation model was

prepared.

Finally AMPL solver (Taha, 2011) was selected for the task of solving the tableau by VAM

method and optimal allocation was achieved.




Using this final allocation network was prepared and cost of all components was determined.

Results

Internal lining samples from cement mortar lined DI pipes of different diameters were

obtained and surface roughness was measured by profilometer. Surface roughness parameter

Rz was found to be varying between 0.0037 mm to 0.0378 mm. The Reynold‘s number, Re

was calculated using limiting flow obtained from limiting velocity considered for that

particular diameter. The range of Re was found to be 1900986 to 401998. The equivalent

surface roughness value ‗e‘ used in Churchill‘s equation to find out relative roughness e / D

was replaced with Rz (mean peak-to-valley height). Friction factors f were calculated using

these values of Re and Rz / D. Using these values of friction factors f and various values of

Re regression analysis was carried out to find out friction factors directly from different

specific values of Re.

The maximum and minimum values of Rz / D were adopted for plotting graphs considering

extreme combinations of Rz and pipe diameter D, i.e. maximum Rz (0.0378 mm) was

considered with minimum diameter (200 mm) and to get minimum value of Rz / D,

minimum value of Rz (0.0037 mm) was considered with maximum diameter (600 mm). The

maximum and minimum values of Rz / D obtained were 0.0001890 and 0.0000062

respectively, which covers all possible values for present study. The rounded off minimum

and maximum Rz / D values were 0.000005 and 0.00025. Fig. 4 depicts the variations in the

friction factors for cement mortar lined Ductile Iron pipe calculated by Churchill‘s equation

and by Regression analysis for different Rz / D values with Reynolds number. The values of

friction factors obtained for each Rz / D values starting from 0.000005 up to 0.00025 were

plotted against Reynolds number from 4000 to 1.901 x 106. The initial two increments were

kept of 0.000015 and all remaining increments were 0.000025 till Rz / D of 0.00025 was

reached.




Figure 4 Variations in friction factor f obtained by Churchill‘s equation for different values of Rz / D

for cement mortar lined DI pipes and Reynolds No.

As the friction factor obtained by both Churchill equation and regression analysis have perfect

coefficient of correlation the Rz values were used in EPANET and WaterNetGen to determine

diameter of the pipe network.

Optimal cost of transportation of reclaimed water from each source to different demand

nodes using AMPL solver were presented here.

There was slight difference in cost calculations in scenarios 1and 5. In scenario 1 selling

price of saved water for irrigation purpose was considered as charged by Sardar Sarovar

Narmada Nigam Limited, whereas in scenario 5 selling price of saved water was based on

cost of treated water plus 15% profit for irrigation purpose.

TABLE 1: Tableau of transportation cost as per scenarios 1 and 5

Source/

Destination

T1 Rs.

T2 Rs.

T3 Rs.

T4 Rs.

. D(Dummy)

Rs. Supply in

LPS

Atladara 1103972 1119644 1122277 1136761 . 0 995.370

Chani 1195688 1211360 1211373 1227765 . 0 243.056

Gajarawadi 1062067 1077740 1057585 1054502 . 0 763.889

Kapurai 1073886 1089558 1088000 1110326 . 0 1192.130

Rajivnagar 1126683 1142356 1140798 1155282 . 0 902.778

Tarsali 1050545 1066217 1068850 1091176 . 0 601.852

Demands in

LPS

21.77 19.82 14.12 12.68 .

2639.51

Similarly tableaus for all scenarios were prepared. AMPL solver (Taha, 2011) was used

to solve the tableau by VAM method and optimal allocation of reclaimed water from each

source to different destinations and the optimal costs of transportation of reclaimed water

from various sources to all destinations for various options are given in Table 2.

TABLE 2: Summary statement of AMPL optimal output

Sr.

No. Description

Cost, Rs.

Total Cost,

Rs.

Demand

Satisfied,

MLD

Cost per

MLD,

Rs.

Sewage treatment plants(STPs)

Tarsali Gajarawadi Kapurai Rajivnagar Chani Atladara

1 All plants connected

network 2,26,37,61,593 2,26,37,61,593 177.946 1,27,21,622

2 All plants separate

network 24,85,58,812 11,57,09,554 15,58,71,238 38,77,55,102 30,42,05,325 92,74,99,872 2,13,95,99,904 152.879 1,39,95,360

3 TKG plus others 50,17,10,040 38,77,55,102 30,42,05,325 92,74,99,872 2,12,11,70,340 152.879 1,38,74,810

4 KGR plus others 24,85,58,812 2,34,38,47,667 30,42,05,325 9,27,499,872 3,82,41,11,676 152.879 2,50,13,938

5 KG plus others 24,85,58,812 26,00,14,299 38,77,55,102 30,42,05,325 92,74,99,872 2,12,80,33,411 152.879 1,39,19,703

6 AC plus others 24,85,58,812 11,57,09,554 15,58,71,238 38,77,55,102 1,08,47,96,486 1,99,26,91,192 177.669 1,12,15,741

Abbreviations: TKG- Tarsali, Kapurai and Gajarawadi STP, KGR- Kapurai, Garjarawadi and Rajivnagar STP, KG- Kapurai and Gajarawadi

STP and AC – Atladara and Chani STP

Though per MLD cost was the lowest for Ataladara Channi combined network (Sr. No. 6)

the second lowest option of all the plants connected network ( Sr. No. 1) was considered

as optimal solution due to better reliability of supply. As all the plants were connected in

first option whenever there would be breakdown or maintenance would be going on in

any one plant the supply could be maintained by diverting treated water from other plants

to the demand nodes.

After selecting all the plants connected network as optimal solution, based on VAM

output from AMPL software, the reclaimed water distribution network was prepared.

For this final optimal network all the costs like pipe network cost, pumping cost, ESR and

pump cost, O,M & R cost etc. were calculated.

For calculation of Internal Rate of Return total capital costs were calculated as follows:

Rs.

a) Capital cost treatment plants for

primary and secondary treatment- 4,29,40,49,105

b) Capital cost treatment plants for

tertiary treatment- 45,78,46,259

c) For industrial and residential purposes-

Total ESR cost 30,96,00,000

Total piping cost 87,18,76,597

Total pump cost 63,70,000

Capital Cost of Piping, ESR &

Pump 1,18,78,46,597

d) For irrigation purpose-

Total ESR cost 40,77,20,000

Total piping cost 1,01,53,88,449

Total pump cost 1,00,15,543

Capital Cost of Piping, ESR &

Pump 1,43,31,23,992

Total Capital Cost……………………7,37,28,65,953

(a+b+c+d) Say 7.37x109




Selling price for industrial and residential reuse for scenario 1 was calculated as follows:

Total demand in MLD 177.946

Annual Cost of treatment plant

including O & M, ……………Rs. 27,81,61,627

Annual Cost of additional

treatment, ……………………..Rs. 45,78,46,259

Cost of additional treatment

O & M, ……………………….Rs. 1,33,56,05,508

Annual cost of ESR, Pump and

Piping, ……………...…………Rs. 9,57,24,285

Total O,M & R cost for Piping,

ESR & Pump, ……………..….Rs. 6,69,45,285

Total pumping cost, …………Rs. 2,57,29,757

TOTAL COST,

…………………..Rs. 2,26,00,12,721

i.e. COST / MLD, ……………Rs. 1,27,00,554

i.e. COST/Kilo Liter, ……..…Rs. 34.80

Adding 15% profit

5.22

Selling price /KL, ……………Rs.

40.02

Say, ………………………………

..Rs./KL

40.00

This selling price is similar to selling price of Sardar Sarovar Narmada Nigam Limited

selling price of Rs. 40.17 Rs./KL in 2020.

Similarly the selling price for irrigation purpose reuse was also determined and it came to

be Rs. 9 / KL.

Analysis

Figure 5 shows how the friction factors obtained by both Churchil equation and by

regression analysis have perfect correlation. The coefficient of correlation obtained R2

was 1.00.




Figure 5 Variation of friction factors for cement mortar lined DI pipes obtained by

Churchill‘s equation fc and regression Analysis fr

Internal rate of return was calculated using selling price of reclaimed water and all the

costs to treat the urban wastewater for each of the five scenarios to ascertain the economic

sustainability of the project.

Table 3: IRR for Scenario 1 considering all costs

Sr.

No. PARTICULARS

0TH

YEAR

1ST

YEAR

2ND

YEAR

3RD

YEAR

. 28th

YEAR

29th

YEAR

30th

YEAR

1 CAPITAL COST, Rs. 7.37x109 .

1.1 LOAN RECEIVED FROM

BANK, Rs. 6.06x109

.

2 FIXED COST .

2.1 Rate of depreciation for first

half year as per MACRS, % 3.75 7.219

. 0 0 0

2.2

Rate of depreciation for

second half year as per

MACRS, %

3.75 7.219 6.677 .

0 0 0

2.3 Depreciation for 1st half

year, Rs. 0 1.38x108 2.66x108

. 0 0 0

2.4 Depreciation for 2nd half

year, Rs. 1.38x108 2.66x108 2.46x108

. 0 0 0

2.5 Total Depreciation, Rs. 1.38x108 4.04x108 5.12x108 . 0 0 0

2.6 Cumulative depreciation, Rs. 1.38x108 5.43x108 1.05x109 . 7.37

x109

7.37

x109 7.37 x109

2.7 Amount of Repayment of

Loan, Rs. 4.46x108 4.46x108 4.46x108

. 4.46x108 4.46x108 4.46x108

2.8 Interest obtainable in 1st half

year, Rs. 0 2.76x106 1.10x107

. 1.54x108 1.54x108 1.54x108

2.9 Interest obtainable in 2nd

half year, Rs. 0 5.58x106 1.66x107

. 1.57x108 1.57x108 1.57x108

2.10 Total Interest to be received

on depreciation money, Rs. 0 8.35x106 2.76x107

. 3.10x108 3.10x108 3.10x108




Sr.

No. PARTICULARS

0TH

YEAR

1ST

YEAR

2ND

YEAR

3RD

YEAR

. 28th

YEAR

29th

YEAR

30th

YEAR

2.11 Interest lost on 25% capital

cost as seed money, Rs. 7.37x107 7.37x107 7.37x107

. 7.37x107 7.37x107 7.37x107

3 Insurance, Rs. 5.53x107 5.53x107 5.53x107 . 5.53x107 5.53x107 5.53x107

4 Cost of O & M for Primary

and secondary plant, Rs. 1.73x108 1.73x108 1.73x108

. 1.73x108 1.73x108 1.73x108

5 Cost of O & M for tertiary

plant, Rs. 1.34x109 1.34x109 1.34x109

. 1.34x109 1.34x109 1.34x109

6 Maintenance & Repairs of

ESR, Pump and Piping, Rs. 1.54x108 1.54x108 1.54x108

. 1.54x108 1.54x108 1.54x108

7 Pumping cost, Rs. 6.10x107 6.10x107 6.10x107 . 6.10x107 6.10x107 6.10x107

8 Operator's salary, Rs. 1.44x106 1.44x106 1.44x106 . 1.44x106 1.44x106 1.44x106

9 Other charges, Rs. 3.69x107 3.69x107 3.69x107 . 3.69x107 3.69x107 3.69x107

10 CASH OUTFLOW, Rs. 2.34x109 2.34x109 2.34x109 . 2.34x109 2.34x109 2.34x109

11 NET CASH OUTFLOW,

Rs. 2.34x109 2.33x109 2.31x109

. 2.03x109 2.03x109 2.03x109

12 INCOME .

12.1

Selling price of treated water

for industrial and residential

purpose Rs./KL

40.00 40.00 40.00

.

40.00 40.00 40.00

12.2

Total treated water to be sold


purpose, KL

6.50x107 6.50x107 6.50x107

.

6.50x107 6.50x107 6.50x107

12.3

Income from selling treated

water for industrial and

residential purpose, Rs.

2.60x109 2.60x109 2.60x109

.

2.60x109 2.60x109 2.60x109

12.4

Total saved fresh water

income as per SSNNL rates


purpose, Rs.

2.60x109 1.69x109 1.69x109

.

1.69x109 1.69x109 1.69x109

12.5

Selling price of treated water

for irrigation purpose,

Rs./KL

9 9 9 .

9 9 9

12.6 Total treated water to be sold

for irrigation purpose, KL 8.15x107 8.15x107 8.15x107

. 8.15x107 8.15x107 8.15x107

12.7 Income from Selling water

for irrigation purpose, Rs. 7.34x108 7.34x108 7.34x108

. 7.34x108 7.34x108 7.34x108

12.8

Total saved fresh water

income as per SSNNL rate

for irrigation purpose

4.32x107 4.32x107 4.32x107

.

4.32x107 4.32x107 4.32x107

13 CASH INFLOW 5.06x109 5.06x109 5.06x109 . 5.06x109 5.06x109 5.06x109

14 NET CASH FLOW, Rs. -

1.34x1010 2.73x109

2.73

x109

2.75

x109 . 3.04

x109 3.04x109 3.04x109

15 INTERNAL RATE OF

RETURN 27.47%

.

1ST

YEAR

2ND

YEAR

3RD

YEAR

. 28th

YEAR

29th

YEAR

30th

YEAR




The optimal solution for scenario 1 was subjected to sensitivity analysis by increasing and

decreasing demand by 5, 10 and 15% and % variations in AMPL optimal output were

found out.

TABLE 4: Sensitivity analysis of the optimum solution considering 5%, 10% and 15%

increase and decrease in demands

Case % Variation in

demand

% Variation in AMPL

optimal output

1 5 0.51

2 10 0.88

3 15 1.23

4 -5 -0.02

5 -10 -0.28

6 -15 -0.49

As % variation in AMPL optimal output varies from -0.02 % to 1.23% , it is considered

as negligible for practical considerations. Therefore internal rate of return was not

calculated for increase and decrease in demand by 5,10 and 15%.

The next alternative for sensitivity analysis is variation in selling price. Considering

increase and decrease in selling price by 5, 10 and 15% internal rate of return was

calculated for all the five scenarios.

TABLE 5: Sensitivity analysis of optimal solution for different scenarios

Description

Internal Rate of Return

Original

selling price

% Increase and decrease in selling price

5% 10% 15% -5% -10% -15%

Scenario 1 27.47% 29.99% 31.97% 32.92% 25.56% 22.99% 22.03%

Scenario 2 NA

Scenario 3 17.76% 19.20% 21.19% 23.22% 16.31% 14.29% 12.18%

Scenario 4 22.37% NA

Scenario 5 32.88% 36.04% 37.95% 38.91% 30.97% 27.82% 26.86%




Internal rate of return was also calculated considering negative pricing.

At present there are five existing STPs and one proposed STP at Rajivnagar. Looking to

the future need of VUDA area it is assumed that a new additional STP at Chhani is

required. Table 6 represents IRR with and without negative pricing consideration for

with and without 35 MLD Chhani new plant.

Scenario 1

Scenario 50.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

1 2 3 4 5 6 7

Sensitivity analysis of optimal solution for different scenarios

Scenario 1

Scenario 3

Scenario 5




TABLE 6: IRR with and without considering Chhani new plant for different scenarios

and considering negative pricing

N1 N2 N3 N4

Description

Considering 35 MLD Chhani

New Plant

Without Considering 35 MLD

Chhani New Plant

Original

With

Negative

Pricing

Original With Negative

Pricing

S1 Scenario 1 26.33% 20.10% 27.47% 21.01%

S2 Scenario 2 NA NA

S3 Scenario 3 16.52% 12.77% 17.76% 13.83%

S4 Scenario 4 20.91% 16.78% 22.37% 18.03%

S5 Scenario 5 32.35% 26.13% 32.88% 26.42%

IRR with and without considering Chhani new plant for different scenarios were

calculated and used in uncertainty analysis given in Tables 7 and 8.

TABLE 7: Solving uncertainty problem with pessimistic, optimistic and equal probability

considerations

Pessimistic

(maxmin)

value

Optimistic (maximax)

value

Equal probability value

=1/n(P1+P2+….+Pn)

S1 20.10% 27.47% 23.73

S2 NA NA NA

S3 12.77% 17.76% 15.22

S4 16.78% 22.37% 19.52

S5 26.13% 32.88% 29.45

TABLE 8: Solving uncertainty problem with maximum regret consideration

N1 N2 N3 N4

Regret Regret Regret Regret Maximum

Regret

S1 6.02% 6.03% 5.41% 5.41% 6.03%

S2 NA NA NA NA NA

S3 15.83% 13.36% 15.12% 12.59% 15.83%

S4 11.44% 9.35% 10.51% 8.39% 11.44%

S5 0.00% 0.00% 0.00% 0.00% 0.00%




Considering the uncertainty over the new Chhani STP plant of 35 MLD, uncertainty was

tested for equal probability, maximum regret, optimistic and pessimistic criteria.

As shown in Table 7 and 8 scenario 5 is the best choice under uncertainty conditions.

g. Achievements with respect to objectives

Specific (measurable) Indicator

a) Amount of water being reused

MLD

For industrial and residential purposes = 177.946

For irrigation, gardening and tree

plantation purposes = 248.584

Total water to be reused = 426.530

b) Cost of combined distribution network

Industrial & residential purposes = Rs. 87,18,76,597

(New Chhani plant was not considered for industrial and residential purposes network

because all the reclaimed water from Channi new plant was given for irrigation purpose.)

Irrigation purposes:

Without New Chhani STP =Rs. 101,53,88,448

With New Chhani STP = Rs. 106,27,99,022

c) Selling price of reclaimed water

Industrial and residential purposes = Rs. 40 / KL

Irrigation purpose:

Without New Chhani STP =Rs. 9 / KL

With New Chhani STP = Rs. 10 /KL

d) Internal Rate of Return




Table 9: Internal Rate of Return with and without negative pricing consideration for with

and without 35 MLD Chhani New Plant

Description

Considering 35 MLD Chhani

New Plant

Without Considering 35 MLD Chhani New

Plant

Original With Negative

Pricing Original

With Negative

Pricing

Scenario 1 26.33% 20.10% 27.47% 21.01%

Scenario 2 NA NA

Scenario 3 16.52% 12.77% 17.76% 13.83%

Scenario 4 20.91% 16.78% 22.37% 18.03%

Scenario 5 32.35% 26.13% 32.88% 26.42%

Criteria

a) Economic returns & profitability

IRR for scenario 1 considering option with and without Chhani new STP plant were

26.33% and 27.47% respectively.

IRR for scenario 5 considering option with and without Chhani new STP plant were

32.35% and 32.88% respectively.

As the IRR is above 11% (criteria of Asian Development Bank) the distribution of

reclaimed water is economically sustainable.

b) Reliability of water supply

As the IRR is above 11% (criteria of Asian Development Bank) the distribution of

reclaimed water is sustainable.Therefore the prospect of sustainability will make the

reclaimed water distribution reliable.

As all plants are connected during failure of any plant, water can be diverted from other

plant and thus reliability of supply can be achieved.

h. Conclusions

As Specific (measurable) Indicators fullfill the criteria, the objective can be achieved.

Thus, it can be stated that reuse of reclaimed water to VUDA area is sustainable.




After calculating IRR sensitivity analysis was carried out by increasing and decreasing

the selling price by 5, 10 and 15% for scenario 1 and scenario 5. In all cases IRR

remained well above 11%. So, even if there is decrease of 15% in selling price the reuse

option is profitable.

The sensitivity analysis reveals that scenario 2, 3 and 4 are not profitable. Scenario 5 is

the most profitable option therefore selling price of reclaimed water for industrial &

residential purposes should be Rs. 40 /KL and for irrigation purpose Rs. 10/ KL.

Considering the uncertainty over the new Chhani STP plant of 35 MLD, uncertainty was

tested for equal probability, maximum regret, optimistic and pessimistic criteria.

Accordingly it is concluded that scenario 5 should be considered for determining the

selling price.

From these conclusions, it is no longer appropriate to consider treated municipal

wastewater as a ―waste‖ that requires ―disposal‖, but rather it should be used as a

resource that can be put to beneficial use.




i. List of all publications arising from the thesis

Technical Papers Published in Reputed Journals:

Sr. No. Name of the

Authors

Name of the Journal Year of

Publication

Title of the paper

1

D.A. Shah &

Dr. D. T.

Shete

Abhinav Journal of Research In

Science & Tech.

Aug-13 Feasibility of Water Reuse

Technical Papers Published at International Level:

Sr. No. Name of the

Authors

Name of the Conference Year of

Publication

Title of the paper

1

D.A. Shah &

Dr. D. T.

Shete

Hydro- 2015 International, 17-19th

December, 2015

20th International Conference on

Hydraulics,

Water Resources and River

Engineering, IIT Roorkee,

Roorkee, India

Dec-15

Determining Friction Factor for DI

Pipes by Direct Surface Roughness

Measurements

2

D.A. Shah &

Dr. D. T.

Shete

Hydro-2017 International, 21-23rd

Decemeber,2017, 22nd

International Conference on

Hydraulics, Water Resources and

Coastal Engineering, L.D. College

of Engineering,

Ahmedabad, India

Dec-17

Attaining Optimal Allocation for

Urban Wastewater Management-

Case Study of VUDA Area

3.

D.A. Shah &

Dr. D. T.

Shete

PiCET, 16- 17 February, 2018

Parul University International

Conference on Engineering &

Technology: Smart Construction,

Parul Institute of Engineering and

Technology,

Limda, Vadodara, India

Feb-18

Sensitivity analysis for optimum

urban water reuse for Vadodara

Urban Development Authority Area-

Variation in cost of reclaimed water

Technical Papers Published at National Level:

1

D.A. Shah &

Dr. D. T.

Shete

Proceedings of National

Conference on Emerging Vistas of

Technology in 21st Century-

―Green City‖

(ISBN-978-93-82880-32-5)


Technology,


May-13 Green City : Wastewater Reuse

Perspective and Challenges Ahead




Sr. No. Name of the

Authors

Name of the Conference Year of

Publication

Title of the paper

2

D.A. Shah &

Dr. D. T.

Shete

Proceedings of 5th National

Conference on Emerging Vistas of

Technology in 21st Century-―Smart

Eco Friendly Structures‖


Technology,


Apr-14

Feasibility Study of Reclaimed

Water Reuse Considering

Conveyance Cost

3

D.A. Shah &

Dr. D. T.

Shete

Indian Water Works Association

50th Annual Convention 2018,

Feb. 19-21 at Kala Acadamy,

Panji, Goa

Feb-18

Sensitivity Analysis for Optimum

Urban Water Reuse for Vadodara

Urban Development Authority

(VUDA)Area- Variation in Demand




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