Modeling Runoff and Sediment Yield in Highly Gullied Regions of Kashmir using SWAT Model: A Case Study of Lolab Watershed

https://doi.org/10.22146/jcef.55298

Dar Sarvat Gull(1*), Ayaz Mehmood Dar(2)

(1) Department of Civil Engineering, National Institute of Technology Srinagar, INDIA
(2) Department of Civil Engineering, National Institute of Technology Srinagar, INDIA
(*) Corresponding Author

Abstract


Soil erosion in highly gullied regions of Kashmir valley is a serious global issue due to its impacts on economic productivity and environmental consequences such as land disintegration and one of the most affected areas is Lolab which is flood-prone and has witnessed several disastrous floods in the past. This means assessment of hydrological behavior should be highly prioritized and the most problematic sub-basins contributing to the erosion and excessive runoff identified to formulate and apply proper management strategies. This study integrated the Soil and Water Assessment Tool (SWAT) with Arc software to simulate the runoff and sediment yield of Lolab Watershed. The method was applied due to its flexibility in inputting data requirements and the capability to model larger catchments and mountainous areas. Meanwhile, sensitivity analysis showed the most sensitive four parameters for runoff estimation with the initial soil conservation service curve number II rated to be the highest and two others were found for sediment estimation with channel erodibility factor rated highest. The calibration of the values of these sensitive parameters led to the provision of reliable NashSutcliffe (NSE) and Coefficient of determination(R2) efficiencies which makes SWAT a good analyzing tool to assess the hydrological behavior of highly gullied region and un-gauged basins of Kashmir. These factors were found to be above 0.90 for both runoff and sediment yield and the sediment yield rates were estimated using SWAT at individual sub-basin levels after which a prioritization map was prepared to determine the most problematic sub-basins in the watershed. 


Keywords


Runoff; Sediment Yield; Un-gauged Basins; SWAT; Sensitivity Analysis

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References

Ahmed, P., & Mir, A. A., 2014. Sediment Yield Estimation for Watershed Management in Lolab Watershed of Jammu & Kashmir State using Geospatial Tools. International Journal of Advanced Remote Sensing and GIS, 3,pp. 616-626.

Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., & Kannan, N., 2012. SWAT: Model Use, Calibration, and Validation.Transactions of the ASABE,55(4), pp.1491-1508.

Arnold, J. G., Srinivasan, R., Muttiah, R. S., & Williams, J. R., 1998. Large Area Hydrologic Modeling and Assessment Part I: Model Development 1. JAWRA Journal of the American Water Resources Association, 34(1), pp. 73-89.

Bisantino, T., Bingner, R., Chouaib, W., Gentile, F., & Trisorio L. G., 2015. Estimation of Runoff, Peak Discharge and Sediment Load at The Event Scale in a Medium‐Size Mediterranean Watershed Using The AnnAGNPS model. Land Degradation & Development, 26(4), pp. 340-355.

Calder, I. R., 1998. Water-Resource and LandUse Issues. Swim Paper 3.

Chow, V.T., Maidment, D.R., & Mays, L.W., 1988. Applied Hydrology. New York: McGraw-Hill.

Eckhardt, K., & Arnold, J. G., 2001. Automatic Calibration of a Distributed Catchment Model. Journal of Hydrology, 251(1-2), pp. 103109.

Gull, S., & Shah, S. R., 2020. Watershed Models for Assessment of Hydrological Behavior of The Catchments: A Comparative Study. Water Practice and Technology, 15 (2), pp. 261-281.

Gull, S., Ahangar, M. A., & Dar, A. M., 2017. Prediction of Stream Flow and Sediment Yield of Lolab Watershed Using Swat Model. HydrolCurr. Res, 8, pp. 265.

Himanshu, S. K., Pandey, A., & Shrestha, P., 2017. Application of SWAT in an Indian River Basin for Modeling Runoff, Sediment and Water Balance. Environmental Earth Sciences, 76(1), pp. 3.

Kim, J., Johnson, L. E., Cifelli, R., Choi, J., & Chandrasekar, V., 2018. Derivation of Soil Moisture Recovery Relation using Soil Conservation Service (SCS) Curve Number Method. Water, 10(7), pp. 833.

Neitsch, S. L., Arnold, J. G., Kiniry, J. R., & Williams, J. R., 2011. Soil and Water Assessment Tool Theoretical Documentation Version 2009. Texas: Texas Water Resources Institute.

Nikolaidis, N. P., Bouraoui, F., & Bidoglio, G., 2013. Hydrologic and Geochemical Modeling of a Karstic Mediterranean Watershed. Journal of Hydrology, 477, pp. 129-138.

Pradhan, P., Tingsanchali, T., & Shrestha, S., 2020. Evaluation of Soil and Water Assessment Tool and Artificial Neural Network Models for Hydrologic Simulation in Different Climatic Regions of Asia. Science of the Total Environment, 701, pp. 134308.

SCS, U., 1985. National Engineering Handbook, section 4: Hydrology. Washington DC: US Soil Conservation Service, USDA.

Setegn, S. G., Srinivasan, R., & Dargahi, B., 2008. Hydrological Modelling in the Lake Tana Basin, Ethiopia using SWAT Model. The Open Hydrology Journal, 2(1).

Shen, Z. Y., Gong, Y. W., Li, Y. H., Hong, Q., Xu, L., & Liu, R. M., 2009. A Comparison of WEPP and SWAT for Modeling Soil Erosion of the Zhangjiachong Watershed in the Three Gorges Reservoir Area. Agricultural Water Management, 96(10), pp. 1435-1442.

Sorooshian, S., 1991. Parameter estimation, model identification, and model validation: conceptual-type models. In Recent Advances in the Modeling of Hydrologic Systems (pp. 443-467). Dordrecht: Springer.

Thakur, V. C., & Rawat, B. S., 1992. Geological Map of the Western Himalaya. Scale 1: 1,111,111.

Tuppad, P., Mankin, D., K. R., Lee, T., Srinivasan, R., & Arnold, J. G., 2011. Soil and Water Assessment Tool (SWAT) Hydrologic/Water Quality Model: Extended Capability and Wider Adoption. Transactions of the ASABE, 54(5), pp. 1677-1684.

Van Andel, T., 2010. African Rice (Oryza glaberrima Steud.): Lost Crop of the Enslaved Africans Discovered in Suriname. Economic botany, 64(1), pp. 1-10.

Wheater, H. S., Jakeman, A. J., & Beven, K. J., 1993. Progress and directions in rainfall-runoff modeling. In: Jakeman, A.K., Beck, M.B., McAleer, M.J. (Eds.), Modeling change in environmental systems. John Wiley & Sons, Chichester, UK, pp. 101–132.

Wischmeier, W. H., & Smith, D. D., 1978. Predicting rainfall erosion losses-a guide to conservation planning. Predicting rainfall erosion losses-a guide to conservation planning.

Zhang, S., Liu, Y., & Wang, T., 2014. How Land Use Change Contributes to Reducing Soil Erosion in the Jialing River Basin, China. Agricultural Water Management, 133, pp. 65-73



DOI: https://doi.org/10.22146/jcef.55298

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