Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Gabriel Perez; Ethan T. Coon; Saubhagya S. Rathore; Phong V.V. Le

doi:10.1016/j.jhydrol.2024.131620

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Gabriel Perez, Ethan T. Coon, Saubhagya S. Rathore, Phong V.V. Le

Watershed Systems Modeling

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of a spatially-resolved Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST. This allows us to extend the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Amanzi–ATS, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5000 annual synthetic storm events in a ∼2000km² Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

Original language	English
Article number	131620
Journal	Journal of Hydrology
Volume	639
DOIs	https://doi.org/10.1016/j.jhydrol.2024.131620
State	Published - Aug 2024

Funding

This study was funded by the U.S. Department of Energy, Office of Science, Biological and Environmental Research program and is a product of the Southeast Texas Urban Integrated Field Laboratory project. Computing resources for this work were provided through the U.S. Department of Energy’s ASCR Leadership Computing Challenge award, “Advancing Watershed System Science using ML and Process-based Simulation” provided at the DOE Office of Science’s user facility, National Energy Research Scientific Computing Center ( ALCC-ERCAP0025400 ). We thank Mark Wang and Professor Paola Passalacqua at the University of Texas at Austin for their feedback on the flood map produced by GeoFlood.

Keywords

Basin inundation fraction
Flood frequency analysis
Flood hazard
Integrated Surface-Subsurface Hydrological Model
Peak flows
Population flood exposure
Process-based hydrological simulations
Stochastic Storm Transposition

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10.1016/j.jhydrol.2024.131620

Cite this

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title = "Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure",

abstract = "Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of a spatially-resolved Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST. This allows us to extend the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Amanzi–ATS, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5000 annual synthetic storm events in a ∼2000km2 Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.",

keywords = "Basin inundation fraction, Flood frequency analysis, Flood hazard, Integrated Surface-Subsurface Hydrological Model, Peak flows, Population flood exposure, Process-based hydrological simulations, Stochastic Storm Transposition",

author = "Gabriel Perez and Coon, \{Ethan T.\} and Rathore, \{Saubhagya S.\} and Le, \{Phong V.V.\}",

note = "Publisher Copyright: {\textcopyright} 2024",

year = "2024",

month = aug,

doi = "10.1016/j.jhydrol.2024.131620",

language = "English",

volume = "639",

journal = "Journal of Hydrology",

issn = "0022-1694",

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TY - JOUR

T1 - Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

AU - Perez, Gabriel

AU - Coon, Ethan T.

AU - Rathore, Saubhagya S.

AU - Le, Phong V.V.

PY - 2024/8

Y1 - 2024/8

N2 - Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of a spatially-resolved Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST. This allows us to extend the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Amanzi–ATS, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5000 annual synthetic storm events in a ∼2000km2 Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

AB - Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of a spatially-resolved Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST. This allows us to extend the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Amanzi–ATS, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5000 annual synthetic storm events in a ∼2000km2 Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

KW - Basin inundation fraction

KW - Flood frequency analysis

KW - Flood hazard

KW - Integrated Surface-Subsurface Hydrological Model

KW - Peak flows

KW - Population flood exposure

KW - Process-based hydrological simulations

KW - Stochastic Storm Transposition

UR - https://www.scopus.com/pages/publications/85198142341

U2 - 10.1016/j.jhydrol.2024.131620

DO - 10.1016/j.jhydrol.2024.131620

M3 - Article

AN - SCOPUS:85198142341

SN - 0022-1694

VL - 639

JO - Journal of Hydrology

JF - Journal of Hydrology

M1 - 131620

ER -

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

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