RUNOFF AND SEDIMENT YIELD ESTIMATION USING DISTRIBUTED GEOSPATIAL MODELS FOR AGRICUL- TURAL WATERSHED IN THAILAND

Sunya  Sarapirome; Tharapong  Phetprayoon; Charlie  Navanugraha; Sodchol  Wonprasaid

Authors

Sunya Sarapirome School of Remote Sensing, Institute of Science, Suranaree University of Technology, Thailand.
Tharapong Phetprayoon School of Remote Sensing, Institute of Science, Suranaree University of Technology, Thailand.
Charlie Navanugraha Faculty of Environment and Resources Studies, Mahasarakham University.
Sodchol Wonprasaid School of Crop Production, Institute of Agricultural Technology, Suranaree University of Technology.

Keywords:

Runoff model, Sediment yield model, Distributed geospatial model, GIS

Abstract

This study aims at developing distributed geospatial models to simulate runoff and sediment yieldfor Upper Lam Phra Phloeng, an agricultural watershed in Thailand. The soil conservation service curve number method, the modified universal soil loss equation, and the sediment deliverydistributed model integrated with a geospatial model were used to simulate the event-based runoff and sediment yield. Calibration and validation were performed by comparing observed and simulated results at the M.171 and M.145 stations during the rainy season of the year 2008. The runoff model calibration shows that the coefficient of efficiency (E) is 0.94 and coefficient of determination (R2) is 0.95 at the M.171 station while E is 0.87 and R2 is 0.91 at the M.145 station. The results of the runoff model validation show that E is 0.87 and 0.68 and R2 is 0.89 and 0.75 at M.171 and M.145 stations, respectively. The sediment yield model calibration results show that E is 0.85 and R2 is 0.89 while its validation shows that E and R2 are 0.79 and 0.92, respectively. Thisindicates that the calibrated model working under the geographic information system (GIS) can be applied with satisfactory accuracy to the runoff and sediment yield estimation. Not only are the quantitative results provided satisfactory, but the model is also able to estimate varying runoff and sediment yield over the watershed spatially.

References

Amutha, R. and Porchelvan, P. (2009). Estimation of surface runoff in Mallattar sub-watershed using SCS-CN method. Journal of the Indian Society of Remote Sensing, 37(2): 291-304.

Anbazhagan, S., Ramasamy, S.M., and Das Gupta, S. (2005). Remote sensing and GIS for artificial recharge study, runoff estimation and planning in Ayyar basin, Tamil Nadu, India. Environ. Geol., 48: 158-170.

Charuppat, T. (2002). Land use change detection, land evaluation and land use planning in Lam Phra Phloeng watershed, [Ph.D. Thesis]. Faculty of Agriculture, Khon Kaen University. Khon Kaen, Thailand, 313p.

Cho, J., Park, S., and Im, S. (2008). Evaluation of agricultural nonpoint source (AGNPS) model for small watersheds in Korea applying irregular cell delineation. Agr. Water Manage., 95: 400-408.

Ferro, V. and Porto, P. (2000). Sediment delivery distributed (SEDD) model. J. Hydrol. Eng., 5(4): 411-422.

Grunwald, S. and Norton, L.D. (2000). Calibration and validation of nonpoint source pollution model. Agr. Water Manage., 45: 17-39.

He, C. (2003). Integration of geographic information systems and simulation model for watershed management. Environ. Modell. Softw., 18: 809-813.

Huang, J., Hong, H., and Zhang, L. (2008). Control division of agricultural non-point source pollution at medium-sized watershed scale in Sountheast China. Frontiers of Environmental Science and Engineering in China, 2(3): 333-339.

Kinnell, P.I.A. (2005). Why the universal soil loss equation and the revised version of it do not predict event erosion well. Hydrol. Process., 19: 851-854.

Krause, P., Boyle, D.P., and Bäse, F. (2005). Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 5: 83-87.

Melesse, A.M. and Shih, S.F. (2002). Spatially distributed storm runoff depth estimation using Landsat images and GIS. Comput. Electron. Agr., 37: 173-183.

Merritt, W.S., Letcher, R.A., and Jakeman, A.J. (2003). A review of erosion and sediment transport models. Environ. Modell. Softw., 18(8-9): 761-799.

Mishra, S.K. and Singh, V.P. (2003). Soil Conser-vation Service Curve Number (SCS-CN) Methodology. Kluwer Academic Publishers, Dordrecht, Netherlands, 505p.

Mohammed, H., Yohannes, F., and Zeleke, G. (2004). Validation of agricultural nonpoint source (AGNPS) pollution model in Kari water, South Wollo, Ethiopia. Int. Appl. Earth Obs., 6: 97-109.

Najim, M.M.M., Babel, M.S., and Loof, R. (2006). AGNPS model assessment for a mixed forested watershed in Thailand. Science Asia, 32: 53-61.

Nash, J.E. and Sutcliffe, J.V. (1970). River flow forecasting through conceptual models. Part I: A discussion of principles. J. Hydrol., 10(3): 282-290.

National Resources Conservation Service [NRCS]. (2004). Estimation of direct runoff from storm rainfall: Part 630 hydrology national engineering handbook. United States Department of Agriculture, Washington, DC, USA, 79p.

National Resources Conservation Service [NRCS]. (2007). Hydrologic soil groups: Part 630 hydrology engineering handbook. United States Department of Agriculture, Washington, DC, USA, 14p.

O’Callaghan, J.F. and Mark, D.M. (1984). The extraction of drainage networks from digital elevation data. Lect. Notes Comput. Sc., 28: 323-344.

Olivera, F. and Maidment, D. (1999). Geographic information systems (GIS)-based spatially distributed model for runoff routing. Water Resour. Res., 35(4): 1155-1164.

Pandey, A., Chowdary, V.M., Mal, B.C., and Billib, M. (2008). Runoff and sediment yield modeling from a small agricultural watershed in India using the WEPP model. J. Hydrol., 348: 305-319.

Patil, J.P., Sarangi, A., Singh, O.P., Singh, A.K., and Ahman, T. (2008). Development of a GIS interface for estimation of runoff from watersheds. Water Resour. Manag., 22(9): 1221-1239.

Pullar, D. and Springer, D. (2000). Towards inte-grating GIS and catchment models. Environ. Modell. Softw., 15(5): 451-459.

Rao, K.N., Narendra, K., and Latha, P.S. (2010). An integrated study of geospatial information technologies for surface runoff estimation in an agricultural watershed, India. Journal of the Indian Society of Remote Sensing, 38: 255-267.

Stefano, C.D., Ferro, V., Palazzolo, E., and Panno, M. (2000). Sediment delivery processes and agricultural non-point pollution in a Sicilian basin. J. Agr. Eng. Res., 77(1): 103-112.

Strager, M.P., Fletcher, J.J., Strager, J.M., Yuill, C.B., Eli, R.N., Petty, J.T., and Lamont, S.J. (2010). Watershed analysis with GIS: The watershed characterization and modeling system software application. Comput. Geosci., 36: 970-976.

Tangtham, N. and Lorsirirat, K. (1993). Prediction models of the effect of the basin characteristics and forest cover on reservoir sedimentation in Northeastern Thailand. Kasetsart Journal of Natural Science, 27: 230-235.

Williams, J.R. (1975). Sediment-yield prediction with universal equation using runoff energy factor. In: Present and perspective technology for predicting sediment yield and sources. Pro-ceedings of the Sediment Yield Workshop; 28-30 Nov, 1972. ARS-S-40, US Department of Agriculture Sedimentation Laboratory, Oxford, MS, USA: U.S. Government Printing Office, Washington, DC, USA, p. 244-252.

Xinxiao, Y., Xiaoming, Z., and Lili, N. (2009). Simulated multi-scale watershed runoff and sediment production based on GeoWEPP model. Int. J. Sediment Res., 24: 465-478.

Zhan, X. and Huang, M.L. (2004). ArcCN-Runoff: an ArcGIS tool for generating curve number and runoff maps. Environ. Modell. Softw., 19: 875-879.