This paper took the Foziling Reservoir in the Pi River Basin as an example, used an improved genetic algorithm to optimize the flood control dispatching during the flood process, and compared the results with the traditional genetic algorithm and the dispatching plan in the 2020 large-scale reservoir flood control operation plan. The results showed that, compared with the traditional genetic algorithm, the improved genetic algorithm saved the time for the model to determine the penalty coefficients and made the model application more convenient. At the same time, the design of the original scheduling scheme also has certain limitations. The scheduling results obtained by improving the genetic algorithm could occupy a small flood control capacity as much as possible under the premise of ensuring the safety of the reservoir itself and the downstream area.

Based on the regional disaster system theory, this study constructed a comprehensive flood risk indicator system for small reservoirs, covering the entire flood disaster process from three dimensions: hazard, vulnerability, and exposure. The analytic hierarchy process (AHP) and entropy weight method (EW) were used to determine indicator weights, and a risk assessment was conducted for small reservoirs in Huangshan City, Anhui Province, China. The results indicate that most reservoirs exhibit medium–low overall risk, yet distinct localized high-risk zones exist. High-economic-density areas such as Tunxi District, the central–eastern parts of Huangshan District, and the central and eastern parts of Qimen County have become high-risk clusters due to prominent exposure indicators (numbers of villages and medical facilities). Reservoirs in western and northern regions exhibit higher hazard levels, primarily driven by rainfall and catchment areas. Dam height and reservoir capacity are the main factors affecting vulnerability, with no significant spatial clustering for high-vulnerability reservoirs. Through the decoupling of three-dimensional indicators, this study reveals the differentiated driving mechanisms of “hazard–vulnerability–exposure,” providing a scientific basis for optimizing flood control engineering (e.g., reservoir capacity expansion, dam reinforcement) and risk zoning management (e.g., emergency evacuation planning in high-exposure areas) for small reservoirs.