Spatiotemporal Analysis of Driving Factors and Comprehensive Risk Assessment of Water-Induced Hazards in the Guanzhong Plain, Northwest China

Water-induced natural disaster risks are one of the major challenges faced globally. With the intensification of climate change and human activities, water scarcity, frequent extreme precipitation events, and the increasing occurrence of drought and flood disasters have become significant risk factors threatening the sustainable development of regional economies and societies. The occurrence of water-related disasters is not only influenced by natural hazards but also closely linked to the exposure and vulnerability of socio-economic systems, demonstrating a high degree of complexity and multifactorial nature. The Guanzhong Plain, as an important economic zone and densely populated area in northwest China, faces severe water risk challenges, posing significant pressure on both regional economic development and ecological sustainability. Therefore, a systematic assessment of the spatiotemporal characteristics and driving factors of water risk in the Guanzhong Plain is not only crucial for addressing regional water security issues but also provides an important practical basis for developing scientific water resource management strategies. This study analyzes the spatiotemporal variations in precipitation and temperature in the Guanzhong Plain using long-term observational data from 14 meteorological stations. Subsequently, the spatiotemporal characteristics of extreme precipitation were examined using the RClimDex model, and the Standardized Precipitation Index (SPI) was calculated. In addition, the Remote Sensing Ecological Index (RSEI) was employed to assess the ecological environment status, revealing the spatiotemporal patterns of drought and flood hazards and their driving factors. Building on these analyses, a comprehensive water disaster risk assessment framework was developed, incorporating factors such as the hazard posed by disaster-inducing elements, the vulnerability of disaster-prone environments, the exposure of disaster-bearing entities, and the capacity for disaster prevention and mitigation. Sixteen representative indicators were selected, and a combined weighting approach using the Analytic Hierarchy Process and Entropy Weight Method was applied to assign weights to these indicators. Finally, a quantitative assessment and spatial zoning of water risk safety in the Guanzhong Plain were conducted using weighted composite analysis. Based on the identified levels of water risk safety, corresponding policy recommendations were proposed. This study systematically reveals the spatiotemporal evolution patterns and underlying driving mechanisms of water risk in the Guanzhong Plain, and develops a comprehensive water risk assessment framework, providing scientific basis and theoretical support for regional water resource management and sustainable development.