Web-Based Dynamic Flood Susceptibility Mapping: Leveraging Fuzzy Logic for Interactive Analysis

Ibrahim Demir, S M Samiul Islam 

Flooding is one of the most frequent and devastating natural disasters, resulting in significant global social, environmental, and economic consequences. Performing comprehensive flood risk assessments is essential for comprehending community exposure and susceptibility to floods while facilitating the formulation of mitigation plans. This study presents a web-based framework for flood susceptibility mapping using fuzzy logic, providing dynamic, interactive, and accessible tools for flood risk analysis. Cedar Rapids, Iowa, was chosen as the research region because of its history of significant flooding, notably the catastrophic flood of 2008, and the accessibility of relevant records. The methodology combines physical and socio-economic data to assess flood vulnerability at community and property levels. The web application offers
functionalities enabling users to view the impact of specific indicators, adjust their weights in real time, and monitor immediate developments in flood susceptibility maps. The platform also offers advanced query capabilities, allowing users to retrieve and download comprehensive data for additional study. Additional salient features comprise customized flood scenarios, interactive
data displays, and accessibility for users without necessitating competence in Geographic Information Systems. The web-based approach markedly improves flood risk communication by providing an accessible interface for many stakeholders, including emergency managers, policymakers, and the general public. It facilitates educated decision-making for flood preparedness and mitigation, enhancing resilience in at-risk areas. The results highlight the potential to incorporate fuzzy logic into online tools to address conventional flood risk assessment issues, including computational intricacy and data constraints. The framework's scalable architecture enables adaptation to various natural hazards, enhancing overall catastrophe
risk reduction initiatives.