Impact of climate change on flood risk with urban resilience perspective using fuzzy logic model

Abstract Risk is the probability of a hazard and its consequence that can make humans vulnerable and exposed. The flood-related risk assessment and vulnerability of a locality in advance can help to be better prepared for any future hazard situation. Using a fuzzy logic approach, this study examines the climate change-related risk related to floods in Gyor City in Hungary, which floods have historically impacted. The urban resilience aspect was identified using the urban flood resilience model (UFResi-M) to identify flood-related hazards and the relevant coping capacity in the study area. Five hydrometeorological components, i.e., precipitation, river discharge, temperature, snow accumulation, and river level were selected as the most appropriate indicators for the flood caused by climate change. Mann–Kendall test (MKT) and Sen’s slope estimator (SSE) were applied to perform the trend analysis of hydrometeorological components. A fuzzy logic model based on pre-assigned rules was developed to identify climatic change variability and trend prediction in uncertain situations using MATrix LABoratory (MATLAB). The model investigates how hydrometeorological inputs impact the flood situation in the study area. The model was correlated with real-world data showing a significant correlation between precipitation, river discharge, temperature, snow accumulation, and river level. The model values were processed through the resilience index to identify the relation of flood risk with resilience, which shows an inverse relationship between river level and the resilience of the study area.