Uncertainty analysis of 100-year flood maps under climate change scenarios
Saba Mirza Alipour, Kolbjørn Engeland, J. B. Leal
Abstract
This study presents an assessment of the uncertainty associated with 100-year flood maps under three scenarios: present, RCP4.5, and RCP8.5. Through intensive Monte Carlo simulations, the study focuses on evaluating the uncertainty introduced by key model input parameter, namely the roughness coefficient, runoff coefficient, and precipitation intensity. Notably, the precipitation intensity incorporates multiple sources of uncertainty, including RCP scenario, climate model, and probability distribution function. To analyze the uncertainties, a surrogate hydrodynamic/hydrologic model based on a physical 2D model is employed. The findings of this study challenge the traditional use of deterministic flood maps and climate factors, highlighting the necessity of employing probabilistic approaches for the development of accurate and secure flood maps. Moreover, the research findings indicate that the primary source of uncertainty in precipitation is the selection of the probability distribution, followed by the choice of climate model, and to a lesser extent, the specific RCP scenario.