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  • 1. Process Automation forHydrological Data Mappingover GIS SoftwareBy Rohan Jain (08AG1016)

2. Introduction Weather data is available from variousorganisations like IMD, CWC through theirstations spanning all over the country,periodically. The data available from these places can beused for further processing. Processing is done via various GIS Softwareavailable. ArcGIS is one such popular software. It isused for this project 3. Introduction: Problem Data is not available in format ArcGIS support So it cannot be directly imported Manually importing 10s of thousands of datais not possible. Hence data needs to be automaticallyconverted into an ArcGIS format. But again data from all the sources is not in astandardised format. So each data source needs special attention 4. Objectives Automatic conversion of existinghydrological data of Mahanadi river basininto a universal time-series format Mapping of the data into ArcHydro model ofthe ArcGIS software 5. Study Area: Description Mahandi river basin, located betweenlongitudes 800 30 and 870 E, and latitudes190 21 and 230 35 N 4.3% of the total geographical area of India Mahanadi was notorious for its devastatingfloods. Hirakud Dam, one of the longest damsimproved the situation greatly. 6. Mahanadi riverbasin 7. Study Area: Data Available Data from India Meteorological Departmentand Central Water Commission (CWC) Rainfall data Escape Discharge data Water Level Data Data from remote sensing 8. Methodology: Requirements ArcGIS (Version 9.3) ArcHydro tools (Version 1.4) and ArcHydrodata model Python Programming Language (Version >2.6) External Python Libraries xlrd (for reading spreadsheets) dbfpy (for writing dBase files) 9. Methodology: Study Material Book: ArcHydro - GIS for Water Resourcesby David R. Maidment[7] Book: Arc Hydro Tools - Tutorials GIS Course Content - University of Texas Web Resources, Lectures made available byESRI[8] (ArcGIS Developer organisation) 10. Methodology For interfacing with ArcGIS dBase (*.dbf)database file format used dBase is a popular database and ArcGISrelies on it itself for storing data, so a goodchoice for using it for our task Python libraries available (dbfpy) For data model to store the time series, usedthe TimeSeries model from ArcHydro datamodels. 11. Methodology: Data Model FeatureID: ID of the feature for which thistime series data exists. IMD Stations, CWCGauges etc. TSTypeID: ID of the time series type. Wehave Precipitaion, Discharge, Water Leveletc defined TSDateTime: The date and time of individualdata TSValue: Individual data value 12. Methodology: Automation1. The data obtained from various organisations is converted into a format which follows python data structures.2. Separate (dBase) files contain information about HydroIDs (which will help find FeatureID). The information is extracted and used to find FeatureIDs for station names3. Time Series is generated and then further published as dBase files for use with ArcGIS software. 13. The Data ConversionProcess 14. Methodology: Code Written Modules These are for generic tasks which are applicable toall data sources Takes care of timeseries related internal tasks Also generates the dBase files Process the HydroIDs (FeatureIDs in Time Series database) Fetches ID - Name info about the stations 15. Methodology: Code Written Individual Data Source Scripts Since each data source provides information in adifferent format, they all need a separate script. These scripts process the raw data to pythonicformat and then generate time series database Written in Python Programming Language Total roughly 450 lines of python code A C/Java equivalent will easily measure 2-3times 16. Results Set up an initial project with correct directoryhierarchy and install python + the requiredlibraries Then, on execution of the scripts the timeseries files are generated automatically The time series files can then be importedinto ArcGIS table 17. Results: Loading DataLoading datainto a TimeSeries table inArcCatalog 18. Result: Loading DataArcCatalog data loading dialogs 19. Result: Loading Data Displaying data after being imported. 20. Result: Processing Data Processing the data in ArcMap using ArcHydro tools 21. Result: Processing DataArcMap Processing the Discharge Time Series 22. Future Work Rewrite the modules using Object OrientedApproach to improve the code quality andfuture additions of code easier Apart from this Rainfall, Discharge, WaterLevel series more data can be obtained andadded 23. Thank You