Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed

Li, Xudong; Rankin, Cheryl; Gangrade, Sudershan; Zhao, Gang; Lander, Kris; Voisin, Nathalie; Shao, Manqing; Morales-Hernandez, Mario; Kao, Shih-Chieh; Gao, Huilin

doi:10.1016/j.jhydrol.2021.127126

Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed

Journal Article · Sun Oct 31 00:00:00 EDT 2021 · Journal of Hydrology

DOI:https://doi.org/10.1016/j.jhydrol.2021.127126· OSTI ID:1837856

Li, Xudong ^[1]; Rankin, Cheryl ^[1]; ^[2]; Zhao, Gang ^[1]; Lander, Kris ^[3]; Voisin, Nathalie ^[4]; ^[1]; ^[2]; ^[2]; Gao, Huilin ^[1]

Texas A & M Univ., College Station, TX (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
National Oceanic and Atmospheric Administration (NOAA), Fort Walton, TX (United States)
Pacific Northwest National Lab. (PNNL), Seattle, WA (United States)

Integrated forecasting systems for precipitation, streamflow, and floodplain inundation are of critical importance in mitigating the impacts of destructive floods caused by extreme weather events. However, the skills of streamflow and floodplain inundation forecasts derived from various Quantitative Precipitation Forecasts (QPF) require a greater level of understanding. In this paper, a set of QPF developed by the National Weather Service (NWS) were used to drive a flood modeling system obtained utilizing offline coupling of a physics-based distributed hydrological model, the Distributed Hydrology Soil and Vegetation Model (DHSVM), and a hydrodynamic model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). This flood modeling system was used to produce forecasts of streamflow and floodplain inundation maps during three major flood events in the Brays Bayou Watershed (Houston, Texas, USA) for a range of QPF durations (6–72 h). Then, to investigate the effects of increasing QPF durations on the forecasts, the forecasting skills of precipitation, streamflow, and floodplain inundation were quantified. The results show that: 1) QPF skills for more intense and sustained events such as hurricanes and tropical storms are higher than for shorter, less intense events; 2) while QPF and streamflow forecasting skills decrease as QPF durations increase, inundation forecasts under longer QPF durations (24 or 72 h) show higher skills; 3) extending the maximum QPF duration in operational hydrologic modeling from 24 h (under normal circumstances) to 72 h (for extreme events) may increase the skills of long lead time forecasts for large-scale events like Hurricane Harvey.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1837856

Journal Information:: Journal of Hydrology, Journal Name: Journal of Hydrology Journal Issue: D Vol. 603; ISSN 0022-1694

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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54 ENVIRONMENTAL SCIENCES
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Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed

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