Spatiotemporal Variation of Evapotranspiration on Different Land Use/Cover in the Inner Mongolia Reach of the Yellow River Basin

Abstract

The accurate estimation of global evapotranspiration (ET) is essential to understanding the water cycle and land–atmosphere feedbacks in the Earth system. This study focused on the Inner Mongolia Reach of the Yellow River Basin, a typical arid and semi-arid region. Although there are many remote sensing ET datasets, many of the ET algorithms have not considered the impact of soil moisture, especially in water-limited areas. In this paper, the new PT-JPL model, which incorporates soil moisture into ET simulation, is used to improve the accuracy of ET simulation in water-limited areas. The simulation value is evaluated using two Hobq Desert eddy-covariance towers and the Penman–Monteith–Leuning version 2 (PML-V2) dataset. The new PT-JPL model shows the most significant improvements in water-limited regions; the coefficient of determination can reach 0.826, and the RMSE can reduce to 9.645 W/m2. Soil evaporation is central to the actual ET increase in the study area. Implementing ecological restoration projects reduced the exposed area of land in the study area and reduced the rate of total ET effectively. Furthermore, the most advanced machine learning local interpretation algorithm—the TreeExplainer-based Shapley additive explanation (SHAP) method—was used to identify the driving factors of ET capacity under different land use types. Temperature, NDVI, and root zone soil moisture were the main environmental factors causing ET changes in different plants. Meanwhile, temperature and root zone soil moisture had a noticeable coupling effect, except for grassland. Furthermore, a threshold effect of temperature to ET was found, and the value is 25, 30, and 30 °C in the forest, grassland, and cropland, respectively. This study provides an essential reference for accurately describing the ET characteristics of arid and semi-arid regions to achieve the efficient management of water resources.