Xianliang Liu

This study takes the Danjiangkou reservoir basin, which is the water source area of the South-to-North Water Diversion Project, one of the largest water diversion projects in the world, as the research area. Three different types of evapotranspiration (ET) datasets are adopted, including the Global Land Evaporation Amsterdam Model (GLEAM), European Centre for Medium-Range Weather Forecasts ERA5—Land Component (ERA5Land), and Complementary Relationship (CR) datasets. These datasets are analyzed for spatiotemporal evolution and data fusion using Mann–Kendall analysis, Sen’s Slope analysis, and Extended Triple Collocation (ETC). The aim is to improve the accuracy of evapotranspiration estimation in the watershed of the water source area. The results show the following: (1) All three sets of evapotranspiration data indicate an increasing trend in the watershed, with rates of 0.78 mm/year, 0.14 mm/year, and 2.56 mm/year, respectively. Additionally, the seasonal variation in evapotranspiration is significant, with the rate of change being summer > spring > autumn > winter. (2) The data fusion results indicate that ERA5Land performs best in the water source area watershed, with the smallest root mean square error (RMSE) value. In the fused data, ERA5Land’s evapotranspiration data account for the largest proportion at 59.93%, GLEAM ET data account for 39.96%, and CR’s evapotranspiration data account for the smallest proportion at only 0.11%. (3) The spatial distribution shows that the fused data fully exploits the advantages of different evapotranspiration data, inherits the advantages of ERA5Land and GLEAM ET products, and achieves effective fusion of multi-source data, thereby forming a more accurate dataset. These research findings provide scientific references for the construction of digital twin watersheds, intelligent water resource allocation, and effective responses to climate change in the water source area of the South-to-North Water Diversion Project.

The construction of water-saving renovation projects can bring substantial benefits to the development of agriculture, but it may also be accompanied by negative impacts, especially in a large-scale irrigation district. Hence, there is always controversy, and it is vital and necessary to investigate the effectiveness of water-saving renovation. In this study, the Yahekou irrigation district, one of the largest districts in China, is selected as the case to explore the beneficial influence and adverse impact. Kriging interpolation, Pearson correlation analysis, and linear regression analysis are employed to study the temporal evolution, spatial distribution, and domain influencing factors. The results show that the water-saving renovation project in the Yahekou irrigation district had significant water-saving benefits during the period of 1998–2021, and the average annual water use of the irrigation district decreased by 61%. Canal lining is an important influencing factor for the decrease in irrigation water use, with a correlation coefficient of −0.538, B of −18.669, and R² of 0.290. Furthermore, the water-saving renovation of irrigation districts is not the dominant reason for changes in groundwater depth. Meanwhile, the groundwater depth below ground level (the level DBGL) in the irrigation district increased by 82%. The combined effects of atmospheric precipitation, canal lining, river sand mining, and groundwater exploitation have led to a sustained increase in groundwater depth in the study area. The results obtained from this study can provide valuable and scientific reference for agricultural water resource management over the large-scale irrigation district. This article focuses on the impact of water-saving renovation on ecological and technical indicators such as water use and the groundwater DBGL. However, the impact of water-saving renovation in irrigation districts is multifaceted; subsequent research can explore the impact of water-saving renovation projects on society and the economy.