A Comparison of SWAT Model Calibration Techniques for Hydrological Modeling in the Ganga River Watershed

作     者：Nikita Shivhare Prabhat Kumar Singh Dikshir Shyam Bihari Dwivedi 

作者机构：Indian Institute of Technology Banaras Hindu University Varanasi 221005 India 

出 版 物：《Engineering》 (工程（英文）)

年 卷 期：2018年第4卷第5期

页      面：643-652页

核心收录：

学科分类：082802[工学-农业水土工程] 08[工学] 0828[工学-农业工程] 0815[工学-水利工程] 

基　　金：Indian Meteorological Department National Bureau of Soil Survey and Land Utilization Planning in Nagpur India 

主　　题：Remote sensing Geographic information system Soil and Water Assessment Tool Hydrological modeling SUFI-2 GLUE ParaSol Sediment yield 

摘      要：The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool （SWAT） modeling in the Ganga catchment, over a region of 15 621.612 km2 in the southern part of Uttar Pradesh. The primary goals of this study are： ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting version 2 （SUFI-2）, the generalized likelihood uncertainty estimation （GLUE）, and par-allel solution （ParaSol）. The input data used in the SWAT were the Shuttle Radar Topography Mission （SRTM） digital elevation model （DEM）, Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover （LULC） map and soil map were used to create hydrological response units （HRUs）. Models utilizing SUFI- 2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five cat-egories： their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algo-rithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity （CH_K2）, the universal soil-loss equation （USLE） support parameter （USLE_P）, Manning＇s n value for the main channel （CH_N2）, the surface runof