Quantifying Nuisance Flood Risks by aggregating Hazard and Vulnerability Dimensions over a Severely Flood-Prone Urban Catchment in India

Abstract

Global urban centers are pressurized from elevated flood risks contributing to mammoth economic and financial losses. Nuisance flooding (NF), is an unusual case of urban flooding characterised by lower water depths (between 3 to 10 cm) and velocity (not exceeding 3 m/s) that does not significantly affect public safety or economic assets but can disrupt daily public routines and put additional strain on buildings and infrastructure. Such low-level flooding has been frequently drawing acute attention of the policymakers and stakeholders. However, only a handful of research have understood their inherent risks, i.e., considering both hazard and vulnerability dimensions. The present study quantifies nuisance flood risk over Mithi River catchment, the most severely flood-affected urban centre in Mumbai, the economic capital of India. Appropriate hydro-meteorological variables, such as design rainfall, discharge, and storm tide, are forced into the MIKE+ Hydro River (1D) and MIKE+ Overland Flow (2D) modules in order to simulate inundation. A 1D-2D coupled model setup is created by linking the two modules together. The maps of flood hazards are expressed as the product of depth and velocity (dv). On the other hand, a method based on indicators is taken into account to determine the vulnerability of crucial infrastructure (such as hospitals, fire stations, petrol pumps, etc.). and infrastructure facilities (such as slums, subways, roads etc.) to nuisance flooding. The Shannon entropy assigns appropriate weights to the indicators, which is later used to derive performance scores or degree of vulnerability through TOPSIS multi-criteria decision-making process. To determine the impact of a few indicators on the overall susceptibility, a series of sensitivity analyses are also conducted. To represent the marginal and compound contributions of risk and vulnerability to the overall nuisance flood risk, a unique method called a bivariate choropleth (a 4 ×4 matrix of different colour codes) has been created. The study inspires the adoption of solutions, both structural and non-structural, to reduce the danger of nuisance flooding in a densely populated urban area. Given the influence of climate change on multiple flood drivers over coastal regions, the study recommends the adoption of proposed framework to global coastal cities, for minimising flood risks and developing resilience for the future.