Assessing Climate-Change-Induced Flood Risk in the Conasauga River
Total Page：16
File Type：pdf, Size：1020Kb
Nat. Hazards Earth Syst. Sci., 21, 1739–1757, 2021 https://doi.org/10.5194/nhess-21-1739-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Assessing climate-change-induced flood risk in the Conasauga River watershed: an application of ensemble hydrodynamic inundation modeling Tigstu T. Dullo1, George K. Darkwah1, Sudershan Gangrade2,3, Mario Morales-Hernández3,4, M. Bulbul Sharif5, Alfred J. Kalyanapu1, Shih-Chieh Kao2,3, Sheikh Ghafoor5, and Moetasim Ashfaq3,4 1Department of Civil and Environmental Engineering, Tennessee Technological University, Cookeville, TN 38505, USA 2Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA 3Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA 4Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA 5Department of Computer Science, Tennessee Technological University, Cookeville, TN 38505, USA Correspondence: Alfred J. Kalyanapu ([email protected]) Received: 13 October 2020 – Discussion started: 20 October 2020 Revised: 7 April 2021 – Accepted: 18 April 2021 – Published: 2 June 2021 Abstract. This study evaluates the impact of potential future Copyright statement. This paper has been authored by UT-Battelle, climate change on flood regimes, floodplain protection, and LLC, under contract DE-AC05-00OR22725 with the US Depart- electricity infrastructures across the Conasauga River wa- ment of Energy (DOE). The US government retains and the pub- tershed in the southeastern United States through ensemble lisher, by accepting the article for publication, acknowledges that hydrodynamic inundation modeling. The ensemble stream- the US government retains a nonexclusive, paid-up, irrevocable, flow scenarios were simulated by the Distributed Hydrol- worldwide license to publish or reproduce the published form of this paper, or allow others to do so, for US government purposes. ogy Soil Vegetation Model (DHSVM) driven by (1) 1981– DOE will provide public access to these results of federally spon- 2012 Daymet meteorological observations and (2) 11 sets sored research in accordance with the DOE Public Access Plan of downscaled global climate models (GCMs) during the (http://energy.gov/downloads/doe-public-access-plan). 1966–2005 historical and 2011–2050 future periods. Sur- face inundation was simulated using a GPU-accelerated Two-dimensional Runoff Inundation Toolkit for Operational 1 Introduction Needs (TRITON) hydrodynamic model. A total of 9 out of the 11 GCMs exhibit an increase in the mean ensemble flood Floods are costly disasters that affect more people than any inundation areas. Moreover, at the 1 % annual exceedance other natural hazard around the world (UNISDR, 2015). Ma- probability level, the flood inundation frequency curves indi- jor factors that can exacerbate flood damage include popu- cate a ∼ 16 km2 increase in floodplain area. The assessment lation growth, urbanization, and climate change (Birhanu et also shows that even after flood-proofing, four of the sub- al., 2016; Winsemius et al., 2016; Alfieri et al., 2017, 2018; stations could still be affected in the projected future period. Kefi et al., 2018). Recent observations exhibit an increase The increase in floodplain area and substation vulnerability in the frequency and the intensity of extreme precipitation highlights the need to account for climate change in flood- events (Pachauri and Meyer, 2014), which have strengthened plain management. Overall, this study provides a proof-of- the magnitude and frequency of flooding (Milly et al., 2002; concept demonstration of how the computationally intensive Langerwisch et al., 2013; Alfieri et al., 2015a, 2018; Mora et hydrodynamic inundation modeling can be used to enhance al., 2018). As a result, the damage and cost of flooding have flood frequency maps and vulnerability assessment under the substantially increased across the United States (US) (Pielke changing climatic conditions. and Downton, 2000; Pielke et al., 2002; Ntelekos et al., 2010; Wing et al., 2018) and the rest of the world (Hirabayashi Published by Copernicus Publications on behalf of the European Geosciences Union. 1740 T. T. 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, magnitude of PMF (AEP < 10−4 %), the findings cannot be 2017; Kefi et al., 2018). directly associated with more frequent and moderate flood Since 1968, the National Flood Insurance Program events (i.e., AEP around 1 %–0.2 %) that are the main focus (NFIP), administered by the Federal Emergency Manage- of many engineering applications. Although some of these ment Agency (FEMA), has implemented floodplain regu- studies focused on evaluating the resilience of electricity lation standards in the US to mitigate the escalating flood infrastructures against flood hazard and/or climate change, losses (Bedient et al., 2013). For communities participating only a few of them evaluated site-specific inundation risk in the NFIP, flood insurance is required for structures located and quantified impacts of climate-change-induced flooding within the 1 % annual exceedance probability (AEP) flood on electricity infrastructures under different future climate zone (i.e., areas with probability of flooding ≥ 1 % in any scenarios. Again, one main challenge is associated with the given year; FEMA, 2002). However, existing floodplain pro- high computational costs to effectively transform ensemble tection standards have proven to be inadequate (Galloway et streamflow projections into ensemble surface inundation pro- al., 2006; Ntelekos et al., 2010; Tan, 2013; Blessing et al., jections through hydrodynamic models. With the enhanced 2017; HCFCD, 2018), and climate change can likely exacer- inundation models and high-performance computing (HPC) bate these issues (Olsen, 2006; Ntelekos et al., 2010; Kollat capabilities (Morales-Hernández et al., 2020), this challenge et al., 2012; AECOM, 2013; Wobus et al., 2017; Nyaupane can be gradually overcome for more spatially explicit flood et al., 2018; Pralle, 2019). For instance, the streamflow AEP vulnerability assessment. thresholds and synthetic hydrographs used to simulate the The objective of this study is to demonstrate the applicabil- flood zones were derived purely based on historic observa- ity of a computationally intensive ensemble inundation mod- tions that may underestimate the intensified hydrologic ex- eling approach to better understand how climate change may tremes in the projected future climatic conditions. Although affect flood regimes, floodplain regulation standards, and the the possible change of future streamflow AEP thresholds vulnerability of existing infrastructures. Extending from the may be evaluated by an ensemble of hydrologic model out- framework developed by Gangrade et al. (2019) for PMF- puts driven by multiple downscaled and bias-corrected cli- scale events (AEP < 10−4 %) based on one selected climate mate models (e.g., Wobus et al., 2017), the extension from model (CCSM4), we focus on more frequent extreme stream- maximum streamflow to maximum flood zone is not trivial flow events (i.e., AEP around 1 %–0.2 %), which requires and cannot be explicitly addressed through the conventional different modeling strategies based on multiple downscaled deterministic inundation modeling approach. climate models. The unique aspects of this study are the The increases in the magnitude and frequency of flood- application of an integrated climate–hydrologic–hydraulic ing, in addition to the inadequacy of floodplain measures and modeling framework for the following. the high costs of hardening (Wilbanks et al., 2008; Farber- 1. The framework will evaluate the changes in flood DeAnda et al., 2010; Gilstrap et al., 2015), have put elec- regime using high-resolution ensemble flood inundation tricity infrastructures at risk (Zamuda et al., 2015; Zamuda maps. The ensemble-based approach is able to incor- and Lippert, 2016; Cronin et al., 2018; Forzieri et al., 2018; porate the large hydrologic interannual variability and Mikellidou et al., 2018; Allen-Dumas et al., 2019). In par- model uncertainty that cannot be captured through the ticular, electricity infrastructures which lie in areas vulnera- conventional deterministic flood map. ble to flooding can experience floodwater damages that may lead to changes in their energy production and consumption 2. The framework will enable direct frequency analysis (Chandramowli and Felder, 2014; Ciscar and Dowling, 2014; of ensemble flood inundation maps that correspond to Bollinger and Dijkema, 2016; Gangrade et al., 2019). For in- historic and projected future climate conditions. This stance, flooding can rust metals, destroy insulation, and dam- approach provides an alternative floodplain delineation age interruption capacity (Farber-DeAnda et al., 2010; Vale, technique to the conventional approach, in which a sin- 2014; NERC, 2018; Bragatto et al., 2019). It is estimated that gle deterministic design flood value is used to develop a nearly 300 energy facilities are located on low-lying lands flood map with a given exceedance probability. vulnerable to sea-level rise and flooding in the lower 48 US 3. The framework will evaluate the vulnerability of elec- states (Strauss and Ziemlinski, 2012). tricity infrastructures to climate-change-induced flood- Several studies have assessed the vulnerability of elec- ing and assess the adequacy of existing flood protec-