The imbalance between water supply and demand is intensified by population growth and economic development. While water diversion projects are capable of mitigating water shortages, multiple ecological and environmental risks, such as accidental pollution and impairment of ecosystem structure, are introduced by their long-distance water transport and complex corridor environments. The reduction in potential losses hinges on the accurate assessment of these risks. This study integrates the Driving Force–Pressure–State–Impact–Response (DPSIR) model with a projection pursuit model optimized by an improved Sparrow Search Algorithm (SSA) based on seagull optimization and whale optimization operators. A comprehensive risk assessment model was constructed and validated using data from the Chuhe Main Canal for the period 2015 to 2024 as a case study. The results indicate that “water resource utilization rate”, “biodiversity index”, and “public satisfaction” are key factors; project risks have gradually escalated from “relatively low risk” to “relatively high risk”. By this model, the key risk factors and evolutionary patterns of ecological and environmental risks in water diversion projects are able to be scientifically identified, thereby providing a quantitative basis for risk early warning and differentiated management strategies, as well as serving as a reference for the ecological risk assessment of similar inter-basin water diversion projects.
Li et al. (2026) studied this question.