Runoff erosion capacity has significant effects on the spatial distribution of soil erosion and soil losses. But few studies have been conducted to evaluate these effects in the Loess Plateau. In this study, an adjusted SWAT model was used to simulate the hydrological process of the Xihe River basin from 1993 to 2012. The spatial variabilities between runoff erosion capacity and underlying surface factors were analyzed by combining spatial gradient analysis and GWR (Geographically Weighted Regression) analysis. The results show that the spatial distribution of runoff erosion capacity in the studying area has the following characteristics: strong in the north, weak in the south, strong in the west, and weak in the east. Topographic factors are the dominant factors of runoff erosion in the upper reaches of the basin. Runoff erosion capacity becomes stronger with the increase of altitude and gradient. In the middle reaches area, the land with low vegetation coverage, as well as arable land, show strong runoff erosion ability. In the downstream areas, the runoff erosion capacity is weak because of better underlying surface conditions. Compared with topographic and vegetation factors, soil factors have less impact on runoff erosion. The red clay and mountain soil in this region have stronger runoff erosion capacities compared with other types of soils, with average runoff modulus of 1.79 × 10−3 m3/s·km2 and 1.68 × 10−3 m3/s·km2, respectively, and runoff erosion power of 0.48 × 10−4 m4/s·km2 and 0.34 × 10−4 m4/s·km2, respectively. The runoff erosion capacity of the alluvial soil is weak, with an average runoff modulus of 0.96 × 10−3 m3/s·km2 and average erosion power of 0.198 × 10−4 m4/s·km2. This study illustrates the spatial distribution characteristics and influencing factors of hydraulic erosion in the Xihe River Basin from the perspective of energy. It contributes to the purposeful utilization of water and soil resources in the Xihe River Basin and provides a theoretical support for controlling the soil erosion in the Hilly-gully region of the Loess Plateau.

Floods and their subsequent socioeconomic exposures are increasing in most parts of the world due to global warming. However, less attention is given in the arid Central Asia (CA), in which floods usually occur in data-scarce high-mountainous regions with complex cryospheric hydrological processes (CHP). In this study, an improved hydrologic-hydrodynamic model coupled with a glacier mass balance module was developed to enhance flood simulations in CA. The effects of the CHP on future flood inundation and the subsequent socioeconomic exposures were also investigated. We found that the simulations of daily streamflow and flood magnitudes improved significantly over the selected hydrological stations after considering the glacier mass balance. Our estimations indicated that the flood inundation and its dynamic evolution generally agreed with satellite observations. Moreover, CHP-induced (rainfall-induced) flood inundation plays a significant role in China’s Xinjiang and Tajikistan (other regions of CA). The CHP would amplify the effects of future flood on socioeconomics in CA, with population (Gross Domestic Productivity, GDP) exposure up to 2.25 million persons/year (150 billion $ PPP/year) for 2071 – 2100. These findings could provide scientific evidence to improve the understanding of CHP effects on future floods and the subsequent exposures, informing the prioritization and design of flood mitigation strategies in CA.