Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China: A Case Study in the Madu River Basin

Evapotranspiration (ET) is the key to the water cycle process and an important factor for studying near-surface water and heat balance. Accurately estimating ET is significant for hydrology, meteorology, ecology, agriculture, etc. This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009-2018 based on the Soil and Water Assessment Tool (SWAT) model, which was calibrated and validated using the MODIS (Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid (MOD16A2) dataset and measured ET. Two calibration strategies (lumped calibration (LC) and spatially distributed calibration (SDC)) were used. The basin was divided into 34 sub-basins, and the coefficient of determination (R-2) and Nash-Sutcliffe efficiency coefficient (NSE) of each sub-basin were greater than 0.6 in both the calibration and validation periods. The R-2 and NSE were higher in the validation period than those in the calibration period. Compared with the measured ET, the accuracy of the model on the daily scale is: R-2 = 0.704 and NSE = 0.759 (SDC results). The model simulation accuracy of LC and SDC for the sub-basin scale was R-2 = 0.857, R-2 = 0.862 (monthly) and R-2 = 0.227, R-2 = 0.404 (annually), respectively; for the whole basin scale was R-2 = 0.902, R-2 = 0.900 (monthly) and R-2 = 0.507 and R-2 = 0.519 (annually), respectively. The model performed acceptably, and SDC performed the best, indicating that remote sensing data can be used for SWAT model calibration. During 2009-2018, ET generally increased in the Madu River Basin (SDC results, 7.21 mm/yr), with a multiyear average value of 734.37 mm/yr. The annual ET change rate for the sub-basin was relatively low upstream and downstream. The linear correlation analysis between ET and meteorological factors shows that on the monthly scale, precipitation, solar radiation and daily maximum and minimum temperature were significantly correlated with ET; annually, solar radiation and wind speed had a moderate correlation with ET. The correlation between maximum temperature and ET is best on the monthly scale (Pearson correlation coefficient R = 0.945), which may means that the increasing ET originating from increasing temperature (global warming). However, the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate, which means that ET decreases in these sub-basins, indicating that the 'Evaporation Paradox' exists in these sub-basins. This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.