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The impact of socioeconomic development on land-use and land-cover change (LUCC) in river basins varies spatially and temporally. Exploring the spatiotemporal evolutionary trends and drivers of LUCC under regional disparities is the basis for the sustainable development and management of basins. In this study, the Weihe River Basin (WRB) in China was selected as a typical basin, and the WRB was divided into the upstream of the Weihe River Basin (UWRB), the midstream of the Weihe River Basin (MWRB), the downstream of the Weihe River Basin (DWRB), the Jinghe River Basin (JRB), and the Luohe River Basin (LRB). Based on land-use data (cultivated land, forestland, grassland, built-up land, bare land, and water body) from 1985 to 2020, we analyzed the spatiotemporal heterogeneity of LUCC in the WRB using a land-use transfer matrix and a dynamic change model. The driving forces of LUCC in the WRB in different periods were detected using the GeoDetector, and the selected influencing factors included meteorological factors (precipitation and temperature), natural factors (elevation, slope, soil, and distance to rivers), social factors (distance to national highway, distance to railway, distance to provincial highway, and distance to expressway), and human activity factors (population density and gross domestic product (GDP)). The results indicated that the types and intensities of LUCC conversions showed considerable disparities across different sub-basins, where complex conversions among cultivated land, forestland, and grassland occurred in the LRB, JRB, and UWRB, with higher dynamic change before 2000. The conversion of other land-use types to built-up land was concentrated in the UWRB, MWRB, and DWRB, with substantial increases after 2000. Additionally, the driving effects of the influencing factors on LUCC in each sub-basin also exhibited distinct diversity, with the LRB and JRB being influenced by the meteorological and social factors, and the UWRB, MWRB, and DWRB being driven by human activity factors. Moreover, the interaction of these influencing factors indicated an enhanced effect on LUCC. This study confirmed the spatiotemporal heterogeneity effects of socioeconomic status on LUCC in the WRB under regional differences, contributing to the sustainable development of the whole basin by managing sub-basins according to local conditions.

Flash floods show strong regional differentiation in spatial–temporal distribution and driving forces, thereby hindering their effective prevention and control. This study analyzed the spatiotemporal characteristics of flash floods in Shaanxi Province, China, differentiated among the northern Shaanxi (NS), Guanzhong (GZ), and southern Shaanxi (SS) regions based on the Mann–Kendall, Theil–Sen Median, and standard deviation ellipse methods. The main factors driving disasters and their interactions in each region were then identified within the three categories of precipitation factor (PPF), surface environment factor, and human activity factor (HAF) based on a geographical detector. Finally, the differences in flash flood characteristics among the NS, GZ, and SS regions were analyzed. The results showed that flash floods in Shaanxi Province are greatly affected by the PPF and the HAF, although the spatial–temporal characteristics and disaster-causing factors were significantly different in each region. The regions were ranked according to the number and growth trends of flash floods as follows: SS > GZ > NS. Furthermore, flash floods were affected by multiple factors, with the interaction between factors acting as a driving force of flash floods. The results of this study can provide a reference for the management of flash floods under regional differentiation.

Understanding the environmental impacts of road networks and the success of policy initiatives is crucial to a country’s socioeconomic development. In this study, we propose a comprehensive approach to quantitatively assessing whether a given response is effective in mitigating the impacts of environmental shocks on roads. Our approach includes factor analysis, direct and indirect loss quantification, and cost-benefit analysis. Using nationwide data on road malfunctions and weather service performance in China, we found that the macro-level indirect economic losses from road malfunctions were more than the direct losses in multiples ranging from 11 to 21, and that information provided by the weather service could reduce losses, with benefits exceeding costs by a ratio of 51. The results of our study provide a quantitative tool as well as evidence of the effectiveness of sustainability investment, which should provide guidance for future disaster mitigation, infrastructure system resilience, and sustainability-building policy-making.