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Development of a GIS Interface for Estimation of Runoff from Watersheds

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  • J. Patil
  • A. Sarangi
  • O. Singh
  • A. Singh
  • T. Ahmad

Abstract

Development of accurate surface runoff estimation techniques from ungauged watersheds is relevant in Indian condition due to the non-availability of hydrologic gauging stations in majority of watersheds. Besides this, the high budgetary requirements for installation of gauging stations are another limiting factor in India, which leads to the use of surface runoff estimation techniques for ungauged watersheds. Natural Resources Conservation Services Curve Number (NRCS-CN) method is one of the most widely used methods for quick and accurate estimation of surface runoff from ungauged watershed. Also, the coupling of NRCS-CN techniques with the advanced Geographic Information System (GIS) capabilities automates the process of runoff prediction in timely and efficient manner. Keeping view of this, a GIS interface was developed using the in-built macro programming language, Visual Basic for Applications (VBA) of ArcGIS® tool to estimate the surface runoff by adopting NRCS-CN technique and its three modifications. The developed interface named as Interface for Surface Runoff Estimation using Curve Number techniques (ISRE-CN), was validated using the recorded data for the periods from 1993 to 2001 of a gauged watershed, Banha in the Upper Damodar Valley in Jharkhand, India. The observed runoff depths for different rainfall events in this study watershed was compared with the predicted values of NRCS-CN methods and its three modifications using statistical significance tests. It was revealed that using all the rainfall data for different AMC conditions, the modified CN I performed the best [R 2 (coefficient of determination) = 0.92; E (model efficiency) = 0.89) followed by modified CN III method (R 2 = 0.88; E = 0.87), while the modified CN II (R 2 = 0.42; E = 0.36) failed to predict accurately the surface runoff from Banha watershed. Moreover, under AMC based estimations, the modified CN I method also performed best ( R 2 = 0.95; E = 0.95) for AMC II condition, while the modified CN II performed the worst in all the AMC conditions. However, the developed Interface in ArcGIS® needs to be tested in other watershed systems for wider applicability of the modified CN methods. Copyright Springer Science+Business Media B.V. 2008

Suggested Citation

  • J. Patil & A. Sarangi & O. Singh & A. Singh & T. Ahmad, 2008. "Development of a GIS Interface for Estimation of Runoff from Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(9), pages 1221-1239, September.
  • Handle: RePEc:spr:waterr:v:22:y:2008:i:9:p:1221-1239
    DOI: 10.1007/s11269-007-9222-8
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    References listed on IDEAS

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    1. S. Mishra & Vijay Singh & J. Sansalone & V. Aravamuthan, 2003. "A Modified SCS-CN Method: Characterization and Testing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 17(1), pages 37-68, February.
    2. Sarangi, A. & Bhattacharya, A.K., 2005. "Comparison of Artificial Neural Network and regression models for sediment loss prediction from Banha watershed in India," Agricultural Water Management, Elsevier, vol. 78(3), pages 195-208, December.
    3. S. Mishra & M. Jain & P. Bhunya & V. Singh, 2005. "Field Applicability of the SCS-CN-Based Mishra–Singh General Model and its Variants," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 19(1), pages 37-62, February.
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    2. Muhammad Ajmal & Jae-Hyun Ahn & Tae-Woong Kim, 2016. "Excess Stormwater Quantification in Ungauged Watersheds Using an Event-Based Modified NRCS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1433-1448, March.
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    4. Shirisha Pulukuri & Venkata Reddy Keesara & Pratap Deva, 2018. "Flow Forecasting in a Watershed using Autoregressive Updating Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(8), pages 2701-2716, June.
    5. Chunlin Li & Miao Liu & Yuanman Hu & Tuo Shi & Min Zong & M. Todd Walter, 2018. "Assessing the Impact of Urbanization on Direct Runoff Using Improved Composite CN Method in a Large Urban Area," IJERPH, MDPI, vol. 15(4), pages 1-14, April.
    6. Vojtek Matej & Vojteková Jana, 2016. "GIS-based Approach to Estimate Surface Runoff in Small Catchments: A Case Study," Quaestiones Geographicae, Sciendo, vol. 35(3), pages 97-116, September.
    7. Ismail Chenini & Abdallah Mammou & Moufida El May, 2010. "Groundwater Recharge Zone Mapping Using GIS-Based Multi-criteria Analysis: A Case Study in Central Tunisia (Maknassy Basin)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(5), pages 921-939, March.
    8. Muhammad Ajmal & Jae-Hyun Ahn & Tae-Woong Kim, 2016. "Excess Stormwater Quantification in Ungauged Watersheds Using an Event-Based Modified NRCS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(4), pages 1433-1448, March.
    9. Rejani Raghavan & Kondru Venkateswara Rao & Maheshwar Shivashankar Shirahatti & Duvvala Kalyana Srinivas & Kotha Sammi Reddy & Gajjala Ravindra Chary & Kodigal A. Gopinath & Mohammed Osman & Mathyam P, 2022. "Assessment of Spatial and Temporal Variations in Runoff Potential under Changing Climatic Scenarios in Northern Part of Karnataka in India Using Geospatial Techniques," Sustainability, MDPI, vol. 14(7), pages 1-21, March.
    10. Chang-Shian Chen & Frederick Chou & Boris Chen, 2010. "Spatial Information-Based Back-Propagation Neural Network Modeling for Outflow Estimation of Ungauged Catchment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(14), pages 4175-4197, November.
    11. R. Bhalla & Neil Pelkey & K. Devi Prasad, 2011. "Application of GIS for Evaluation and Design of Watershed Guidelines," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(1), pages 113-140, January.
    12. Rajat Agarwal & P. Garg & R. Garg, 2013. "Remote Sensing and GIS Based Approach for Identification of Artificial Recharge Sites," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2671-2689, May.
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