Modelling hydrology and water quality processes in the Pengxi River basin of the Three Gorges Reservoir using the soil and water assessment tool

Author

Yingyuan Shi, Gaohong Xu, Yonggui Wang, Bernard A. Engel, Hong Peng, Wanshun Zhang, Meiling Cheng and Minglong Dai

Agricultural Water Management, 2017, vol. 182, issue C, pages 24-38

Abstract: The Pengxi River is one of the main tributaries on the north shore of the Three Gorges Reservoir (TGR) and currently faces water quality deterioration and algal bloom problems. The Soil and Water Assessment Tool (SWAT) with a TGR specific database was utilized to evaluate the hydrology and water quality processes of the Pengxi River Basin. The flow and its nutrient content were assessed by the model, and the largest pollutant load generation areas of this basin were identified. The Generalized Likelihood Uncertainty Estimation (GLUE) method was used to conduct sensitivity analysis, model calibration and validation. Results of sensitivity analysis showed that CN2 (initial SCS runoff curve number for moisture condition II) was most sensitive for runoff, while RCN (concentration of nitrogen in rainfall) and FILTERW (width of edge of field filter strip) were most sensitive for nitrogen and phosphorus loadings respectively. Determination of the most sensitive parameters on the rate of change of SWAT outputs was identified. The coefficient of determination (R2) in the validation ranged from 0.66–0.85 for daily stream flow and 0.70–0.86 for nutrient yield. Average annual water yield for the entire basin was found to be 3.93 billion m3 from 2010 to 2013, while average annual total nitrogen yield was 9406t, and average annual total phosphorus yield was 984t. The simulation results indicate that runoff appeared to vary significantly throughout the year and from year to year, and was correlated with precipitation. Higher pollutant load generation areas were mainly concentrated in the central and southern part of the Pengxi River basin. This study is expected to have major implications for identifying non-point source (NPS) and water quality management policies and approaches.

Keywords: SWAT; Hydrology and water quality processes; Non-point source pollutants; Sensitivity analysis; GLUE (search for similar items in EconPapers)
Date: 2017
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