Risk Assessment of Yellow Muddy Water in High-Construction-Intensity Cities Based on the GIS Analytic Hierarchy Process Method: A Case Study of Guangzhou City

During urbanisation, extensive production and construction activities encroach on ecological spaces, leading to changes in environmental structures and soil erosion. The issue of yellow muddy water caused by rainfall in cities with high construction intensity has garnered significant attention. Taking Guangzhou City as the research area, this study is the first to propose a risk assessment model for yellow muddy water in cities with high construction intensity, and the influence of construction sites on yellow muddy water was fully considered. Rainfall and construction sites were used as indicators to assess the hazards of yellow muddy water. Elevation, slope, normalised difference vegetation index ( NDVI ), soil erosion modulus, stream power index ( SPI ), surface permeability, and roads represent the exposure evaluation indicators. Population number and GDP (Gross Domestic Product) were used as vulnerability evaluation indicators. Based on the analytic hierarchy process (AHP) method, the weights of each evaluation indicator were determined, and a risk assessment system for yellow muddy water was established. By overlaying the weighted layers of different evaluation indicators on the geographic information system (GIS) platform, a risk degree distribution map of yellow muddy water disasters was generated. The evaluation results demonstrated that the disaster risk levels within the study area exhibited spatial differentiation, with areas of higher risk accounting for 14.76% of the total. The evaluation results were compared with historical yellow muddy water event information from Guangzhou, and the effectiveness of the model was verified by the receiver operating characteristic (ROC) curve. The validation results indicate that this model provides high accuracy in assessing the degree of risk of yellow muddy water in high-construction-intensity cities, offering effective technical support for precise disaster prevention and mitigation.