Assessing climate-change-induced flood risk in the Conasauga River watershed: an application of ensemble hydrodynamic inundation modeling

Tigstu T Dullo,Shih-Chieh Kao,George K Darkwah,Sudershan Gangrade,Mario Morales-Hernández,M Bulbul Sharif,Sheikh Ghafoor,Moetasim Ashfaq,Alfred J Kalyanapu

doi:10.5194/nhess-21-1739-2021

Abstract

Abstract. This study evaluates the impact of potential future climate change on flood regimes, floodplain protection, and electricity infrastructures across the Conasauga River watershed in the southeastern United States through ensemble hydrodynamic inundation modeling. The ensemble streamflow scenarios were simulated by the Distributed Hydrology Soil Vegetation Model (DHSVM) driven by (1) 1981–2012 Daymet meteorological observations and (2) 11 sets of downscaled global climate models (GCMs) during the 1966–2005 historical and 2011–2050 future periods. Surface inundation was simulated using a GPU-accelerated Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON) hydrodynamic model. A total of 9 out of the 11 GCMs exhibit an increase in the mean ensemble flood inundation areas. Moreover, at the 1 % annual exceedance probability level, the flood inundation frequency curves indicate a ∼ 16 km2 increase in floodplain area. The assessment also shows that even after flood-proofing, four of the substations could still be affected in the projected future period. The increase in floodplain area and substation vulnerability highlights the need to account for climate change in floodplain management. Overall, this study provides a proof-of-concept demonstration of how the computationally intensive hydrodynamic inundation modeling can be used to enhance flood frequency maps and vulnerability assessment under the changing climatic conditions.

Highlights

Floods are costly disasters that affect more people than any other natural hazard around the world (UNISDR, 2015)
Extending from the framework developed by Gangrade et al (2019) for PMFscale events (AEP < 10−4 %) based on one selected climate model (CCSM4), we focus on more frequent extreme streamflow events (i.e., annual exceedance probability (AEP) around 1 %–0.2 %), which requires different modeling strategies based on multiple downscaled climate models
Similar to results presented in the previous sections, these results demonstrate the need for improving existing flood mitigation measures by incorporating the trends and uncertainties that originate from climate change

Summary

Introduction

Floods are costly disasters that affect more people than any other natural hazard around the world (UNISDR, 2015). Major factors that can exacerbate flood damage include population growth, urbanization, and climate change (Birhanu et al, 2016; Winsemius et al, 2016; Alfieri et al, 2017, 2018; Kefi et al, 2018). The damage and cost of flooding have substantially increased across the United States (US) (Pielke and Downton, 2000; Pielke et al, 2002; Ntelekos et al, 2010; Wing et al, 2018) and the rest of the world Dullo et al.: Assessing climate-change-induced flood risk in the Conasauga River watershed et al, 2013; Arnell and Gosling, 2014; Alfieri et al, 2015b, 2017; Kefi et al, 2018)

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Results

Conclusion