A Stochastic Optimization Algorithm for Optimizing Flood Risk Management Measures Including Rainfall Uncertainties and Nonphysical Flood Damages

AbstractOne of the basic assumptions usually made by researchers for obtaining optimal designs of flood mitigation measures that take into account the associated uncertainties is consideration of flood damage probability directly correlated with flood event probability. The present work demonstrates that this assumption leads to 42% underestimation of expected damages for the case study of the Kan River basin near the capital city of Iran, Tehran. To eliminate this limitation, in this paper, inherent rainfall uncertainties are included through random sampling techniques and simulation-based optimization approaches. A Monte Carlo simulation method is employed to generate multivariate synthetic rainfalls, which are then imported in a rainfall-runoff model. This model gives the flood hydrographs of subbasins for hydraulic routing in waterways of the watershed by a hydraulic model, considering different flood mitigation measures. These models are then coupled with the NSGA-II optimization algorithm to provide...