Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed
Abstract
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 forecastsmore »
- Authors:
-
[2];
[1];
[2];
[2];
- 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)
- Publication Date:
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1837856
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Hydrology
- Additional Journal Information:
- Journal Volume: 603; Journal Issue: D; Journal ID: ISSN 0022-1694
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; Flood forecasting skill; Extreme weather events; Quantitative precipitation forecast (QPF); QPF duration; Inundation mapping
Citation Formats
Li, Xudong, Rankin, Cheryl, Gangrade, Sudershan, Zhao, Gang, Lander, Kris, Voisin, Nathalie, Shao, Manqing, Morales-Hernandez, Mario, Kao, Shih-Chieh, and Gao, Huilin. Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed. United States: N. p., 2021.
Web. doi:10.1016/j.jhydrol.2021.127126.
Li, Xudong, Rankin, Cheryl, Gangrade, Sudershan, Zhao, Gang, Lander, Kris, Voisin, Nathalie, Shao, Manqing, Morales-Hernandez, Mario, Kao, Shih-Chieh, & Gao, Huilin. Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed. United States. https://doi.org/10.1016/j.jhydrol.2021.127126
Li, Xudong, Rankin, Cheryl, Gangrade, Sudershan, Zhao, Gang, Lander, Kris, Voisin, Nathalie, Shao, Manqing, Morales-Hernandez, Mario, Kao, Shih-Chieh, and Gao, Huilin. Sun .
"Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed". United States. https://doi.org/10.1016/j.jhydrol.2021.127126. https://www.osti.gov/servlets/purl/1837856.
@article{osti_1837856,
title = {Evaluating precipitation, streamflow, and inundation forecasting skills during extreme weather events: A case study for an urban watershed},
author = {Li, Xudong and Rankin, Cheryl and Gangrade, Sudershan and Zhao, Gang and Lander, Kris and Voisin, Nathalie and Shao, Manqing and Morales-Hernandez, Mario and Kao, Shih-Chieh and Gao, Huilin},
abstractNote = {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.},
doi = {10.1016/j.jhydrol.2021.127126},
journal = {Journal of Hydrology},
number = D,
volume = 603,
place = {United States},
year = {Sun Oct 31 00:00:00 EDT 2021},
month = {Sun Oct 31 00:00:00 EDT 2021}
}
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