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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-339
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-339
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Oct 2020

20 Oct 2020

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This preprint is currently under review for the journal NHESS.

Assessing Climate Change-Induced Flood Risk in the Conasauga River Watershed: An Application of Ensemble Hydrodynamic Inundation Modeling

Tigstu T. Dullo1, Sudershan Gangrade2,3, Mario Morales-Hernández3,4, Md Bulbul Sharif5, Alfred J. Kalyanapu1, Shih-Chieh Kao2,3, Sheikh Ghafoor5, and Moetasim Ashfaq3,4 Tigstu T. Dullo et al.
  • 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

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) eleven 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. Nine out of the eleven 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.

Tigstu T. Dullo et al.

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