Multi-Objective Optimization for Evaluating the Benefits of Land Use Types in Urban Runoff Management

Land use types have emerged as a key focus in sustainable urban planning, offering a pathway to manage urban runoff and enhance ecological benefits. This study evaluates the performance and trade-offs of various land use types within a multi-objective optimization framework. The primary objectives are to minimize urban runoff, reduce construction and maintenance costs, and maximize ecological benefits such as carbon sequestration and vegetation cover.

The study employs a multi-objective optimization approach using a non-dominated sorting genetic algorithm II (NSGA-II) to determine the optimal land use types configuration under budget and spatial constraints. By balancing hydrological, ecological, and economic objectives, the optimization framework generates Pareto frontier solutions that can be used as a reference for decision-making.

This study is tailored to the urban context of South Korea, where rapid urbanization has increased flood risk and environmental stress. By adopting a multi-objective optimization approach, this study provides a decision support tool for urban planners and policymakers, highlighting the trade-offs between competing objectives and providing flexible solutions based on local conditions.

In conclusion, this study establishes a replicable sustainable urban runoff management framework that is applicable to Korea and other urban areas around the world. The combination of GIS-based analysis, land use types assessment, and optimization techniques ensures a powerful approach to address urban flooding while advancing ecological and economic objectives. The findings contribute to the development of resilient cities that can mitigate flood risks, improve ecological conditions, and support sustainable urbanization strategies.