Soil erosion is an important ecological and environmental problem in the Yellow River Basin (YRB), which restricts the sustainable development of the YRB. Based on the Revised Universal Soil Loss Equation (RUSLE) and Optimal Parameters-based Geographical Detector (OPGD), this study discusses the multiscale spatiotemporal characteristics of soil erosion and its influencing factors in the YRB. The results show that: (1) The average values of soil-erosion modulus of the YRB in 2000, 2005, 2010, 2015, and 2020 was 1877.69, 1641.59, 1485.25, 844.84, and 832.07 t·km⁻²·a⁻¹, respectively, and the areas with severe soil erosion are mainly concentrated in the three provinces of Gansu, Shanxi and Shaanxi, showing a belt-like trend in the northeast-southwest as a whole. (2) From 2000 to 2020, the q value of soil erosion influencing factors in the YRB showed a downward trend. From the YRB scale to the county scale, the q value of the influencing factors showed an increasing trend. Among them, fractional vegetation cover (FVC), landform type, and LU/LC have strong explanatory power for soil erosion in the YRB. FVC explains about 15% of soil erosion, and the interaction between FVC and landform explains up to 35% of soil erosion. (3) The ability of human activities (LU/LC, FVC) to influence soil erosion is increasing, and this feature is more pronounced at small scales. The conclusion of this study can be summarized as managers should pay attention to the role of human activities in the YRB for soil erosion, especially at small scales, in order to formulate lower-cost and targeted soil and water conservation measures.

Urban multi-disaster integrated risk assessment is an important part of urban sustainable development and territorial spatial planning. Based on the results of integrated risk assessment, the scientific and effective performance of disaster prevention and reduction can be effectively improved. This study determines a multi-disaster integrated risk assessment system. The system evaluates the hazard level of disasters, the exposure level of disaster bearing bodies, the vulnerability level of disaster bearing bodies, and the urban resilience level, and determines the city’s integrated risk level on this basis. Taking Jinan as an example, the risk, exposure, vulnerability, resilience, and integrated risk level of Jinan City were analyzed. The results show that the system reasonably analyzes the multi-disaster integrated risk level, and according to the assessment results, countermeasures for disaster prevention and suggestions for territorial spatial planning were put forward.

In recent years, large-scale afforestation in the Yellow River Basin (YRB) has attracted widespread attention due to its significant impact on surface water, playing a crucial role in the ecological sustainability and high-quality development of the basin. In this study, we used a combination of Theil–Sen and Mann–Kendall trend analysis to detect the spatiotemporal dynamic changes of NDVI, surface water storage (SWS), and its components in the YRB from 2001 to 2020, and explored the time lag and instantaneous effects between them using methods such as cross-correlation. The results show that from 2001 to 2020, NDVI and SWS in the YRB increased at rates of 0.41%/year and 1.95 mm/year, respectively, with fluctuations. Spatially, NDVI exhibited a significant upward trend in most areas of the YRB, while regions with significant increases in SWS, canopy surface water (CSW), snow water equivalent (SWE), and soil moisture (SM) were primarily located in the upper reaches. There was a time lag effect of about 2 months between NDVI and SWS in the YRB, and the time lags between SWE, SM, and NDVI were 5 months and 2 months, respectively. Except for CSW, the lag between NDVI and SWE was longer than that between NDVI and SWS or SM across all land cover types. Regarding the instantaneous effect, we found that the effect of vegetation on SWS in the upstream area is mainly the water storage function. In some areas of the middle and lower reaches, vegetation intensifies the consumption of SWS. Our study provides valuable insights into the response mechanism between vegetation restoration and SWS changes, facilitating better coordination between water resource management and ecological conservation in the YRB, thereby achieving sustainable regional economic and ecological development.

The Yellow River Basin (YRB) is an important grain production base, and exploring the spatiotemporal heterogeneity and driving factors of soil erosion in the YRB is of great significance to the ecological environment and sustainable agricultural development. In this study, we employed the Revised Universal Soil Loss Equation (RUSLE) in conjunction with Transport-Limited Sediment Delivery (TLSD) to explore a modified RUSLE-TLSD for use assessing net water erosion. This modification was performed using sediment data, and the explanatory power of driving factors was assessed utilizing an optimal parameters-based geographical detector (OPGD). The results demonstrated that the modified RUSLE-TLSD can accurately simulate the spatiotemporal distribution of net water erosion (NSE = 0.5766; R² = 0.6708). From 2000 to 2020, the net water erosion modulus in the YRB ranged between 1.62 and 5.33 t/(ha·a). Specifically, the net water erosion modulus decreased in the YRB and the middle reaches of the YRB (MYRB), but it increased in the upper reaches of the YRB (UYRB). The erosion occurred mainly in the Loess Plateau region, while the deposition occurred mainly in the Hetao Plain and Guanzhong Plain. The Normalized Difference Vegetation Index (NDVI) and slope emerged as significant driving factors, and their interaction explained 31.36% of YRB net water erosion. In addition, the redistribution of precipitation by vegetation and the slope weakened the impact of precipitation on the spatial pattern of net water erosion. This study provides a reference, offering insights to aid in the development of soil erosion control strategies within the YRB.