An Urban density-based runoff simulation framework to envisage flood resilience of cities

Abstract

Urban form densities play a decisive role in complex urban form scenarios. Therefore, learning to ‘live with the floods’; has become a challenging issue to practice in most urban planning approaches. Several simulation studies have been conducted to examine the influence of urbanization scenarios on urban flood risk management. Yet, there is a gap remaining to optimize every component of flood hydrodynamics across a distinct urban form density. As a result, the economic loss to the urban system is hard to minimize. But planning an intervention with a proper quantification approach for a long-term flood management strategy is useful for making cities resilience to floods. The primary aim of this research is to create a spatial simulation framework that can evaluate how urban density(UD) affects surface runoff (SR) in urban watersheds in various urban form scenarios. First, examine the potential quantification indicators of urban form density. Second, develop a framework to quantify urban form density at the urban watershed scale, which applies to spatial structure. The third step involves creating an SR simulation model that utilizes the 13 selected UD indicators to verify and validate the previously developed framework with real-world data, with the main three categories (3Ds') as per the developed framework. The model evaluates itself with AI-based Decision Tree Analysis incorporated with correlation and experts’ opinions. The model results indicate that the UD indicators including impervious coverage (accuracy level 98.7%), OSR (accuracy level 94.8%), and road density ( accuracy level 93.5%) are the key indicators combined with the population density, accessibility, and built_up coverage to regulate SR in urban catchments. The ground verification of model results indicates an R2 value greater than 0.88. The ultimate goal of this study is to create a method of quantitatively evaluating the effects of physical UD as an independent variable, allowing for a more location specific manner. This study contributes a novel framework incorporating 3Ds (density, diversity, design) to quantify UD, which will aid subsequent processes of decision-making in the realm of urban flood mitigation and planning techniques.