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Open AccessArticle

Spatial Variation Pattern Analysis of Hydrologic Processes and Water Quality in Three Gorges Reservoir Area

1
School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
2
Bureau of Hydrology, Changjiang Water Resources Commission, Wuhan 430010, China
3
School of Water Resources and Hydropower Engineering, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
4
China Institute of Development Strategy and Planning, Wuhan University, Wuhan 430072, China
5
Section of Hydraulic Structure and Flood Risk, Department of Hydraulic Engineering, Faculty of Civil Engineering and Geoscience, Delft University of Technology, Delft 2628 CN, The Netherlands
*
Author to whom correspondence should be addressed.
Water 2019, 11(12), 2608; https://doi.org/10.3390/w11122608
Received: 16 October 2019 / Revised: 3 December 2019 / Accepted: 7 December 2019 / Published: 11 December 2019
(This article belongs to the Section Hydrology and Hydrogeology)
The Three Gorges Project (TGP) has greatly enhanced the heterogeneity of the underlying surface in the Three Gorges Reservoir Area (TGRA), thereby affecting the hydrologic processes and water quality. However, the influence of the differences of underlying surfaces on the hydrologic processes and water quality in the TGRA has not been studied thoroughly. In this research, the influence of the heterogeneity of landscape pattern and geographical characteristics on the spatial distribution difference of hydrologic processes and water quality in the different tributary basins of the TGRA was identified. The TGRA was divided into 23 tributary basins with 1840 sub-basins. The spatial differentiation of the hydrologic processes and water quality of the 23 tributary basins was examined by the Soil and Water Assessment Tool (SWAT). The observed data between 1 January 2010 and 31 December 2013 were used to calibrate and validate the model, after which the SWAT model was applied to further predict the runoff and water quality in the TGRA. There are 25 main model parameters, including CN2, CH_K2 and SOL_AWC, which were calibrated and validated with SWAT-Calibration and Uncertainty Procedures (SWAT-CUP). The landscape patterns and geomorphologic characteristics in 23 tributary basins were investigated and spatially visualized to correlate with surface runoff and nutrient losses. Due to geographical difference, the average total runoff depth (2010–2013) in the left bank area (538.6 mm) was 1.4 times higher than that in the right bank area (384.5 mm), total nitrogen (TN) loads in the left bank area (6.23 kg/ha) were 1.9 times higher than in the right bank area (3.27 kg/ha), and total phosphorus (TP) loads in the left bank area (1.27 kg/ha) were 2.2 times higher than in the right bank area (0.58 kg/ha). The total runoff depth decreased from the head region (553.3 mm) to the tail region (383.2 mm), while the loads of TN and TP were the highest in the middle region (5.51 kg/ha for TN, 1.15 kg/ha for TP), followed by the tail region (5.15 kg/ha for TN, 1.12 kg/ha for TP) and head region (3.92 kg/ha for TN, 0.56 kg/ha for TP). Owing to the different spatial distributions of land use, soil and geographical features in the TGRA, correlations between elevation, slope gradient, slope length and total runoff depth, TN and TP, were not clear and no consistency was observed in each tributary basin. Therefore, the management and control schemes of the water security of the TGRA should be adapted to local conditions. View Full-Text
Keywords: spatial variation; hydrologic processes and water quality; landscape pattern; geomorphologic characteristics; Three Gorges Reservoir Area; SWAT model spatial variation; hydrologic processes and water quality; landscape pattern; geomorphologic characteristics; Three Gorges Reservoir Area; SWAT model
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MDPI and ACS Style

Chen, X.; Xu, G.; Zhang, W.; Peng, H.; Xia, H.; Zhang, X.; Ke, Q.; Wan, J. Spatial Variation Pattern Analysis of Hydrologic Processes and Water Quality in Three Gorges Reservoir Area. Water 2019, 11, 2608.

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