Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data

The application of hydrologic and hydrodynamic models in flash flood hazard assessment is mainly limited by the availability of robust monitoring systems and long-term hydro-meteorological observations. Nevertheless, several studies have demonstrated that coupled modeling approaches based on event s...

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Main Authors: Jorge Hurtado-Pidal, Juan S. Acero Triana, Edgar Espitia-Sarmiento, Fernando Jarrín-Pérez
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/12/10/2768
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author Jorge Hurtado-Pidal
Juan S. Acero Triana
Edgar Espitia-Sarmiento
Fernando Jarrín-Pérez
author_facet Jorge Hurtado-Pidal
Juan S. Acero Triana
Edgar Espitia-Sarmiento
Fernando Jarrín-Pérez
author_sort Jorge Hurtado-Pidal
collection DOAJ
description The application of hydrologic and hydrodynamic models in flash flood hazard assessment is mainly limited by the availability of robust monitoring systems and long-term hydro-meteorological observations. Nevertheless, several studies have demonstrated that coupled modeling approaches based on event sampling (short-term observations) may cope with the lack of observed input data. This study evaluated the use of storm events and flood-survey reports to develop and validate a modeling framework for flash flood hazard assessment in data-scarce watersheds. Specifically, we coupled the hydrologic modeling system (HEC-HMS) and the Nays2Dflood hydrodynamic solver to simulate the system response to several storm events including one, equivalent in magnitude to a 500-year event, that flooded the City of Tena (Ecuador) on 2 September, 2017. Results from the coupled approach showed satisfactory model performance in simulating streamflow and water depths (0.40 ≤ Nash-Sutcliffe coefficient ≤ 0.95; −3.67% ≤ Percent Bias ≤ 23.4%) in six of the eight evaluated events, and a good agreement between simulated and surveyed flooded areas (Fit Index = 0.8) after the 500-year storm. The proposed methodology can be used by modelers and decision-makers for flood impact assessment in data-scarce watersheds and as a starting point for the establishment of flood forecasting systems to lessen the impacts of flood events at the local scale.
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spelling doaj.art-d8a74de911324484b02d0e0ddd6c61802023-11-20T16:04:55ZengMDPI AGWater2073-44412020-10-011210276810.3390/w12102768Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey DataJorge Hurtado-Pidal0Juan S. Acero Triana1Edgar Espitia-Sarmiento2Fernando Jarrín-Pérez3Department of Territorial Planning, Faculty of Environmental Sciences and EULA-Centre, Universidad de Concepción, 4070386 Concepción, ChileDepartment of Agricultural and Biological Engineering, University of Illinois, 1304 West Pennsylvania Avenue, Urbana, IL 61801, USAWater and Aquatic Resources Research Group (GIRHA), Universidad Regional Amazónica Ikiam, 150101 Tena, EcuadorDepartment of Biological & Agricultural Engineering, Texas A&M University, TX 77843, USAThe application of hydrologic and hydrodynamic models in flash flood hazard assessment is mainly limited by the availability of robust monitoring systems and long-term hydro-meteorological observations. Nevertheless, several studies have demonstrated that coupled modeling approaches based on event sampling (short-term observations) may cope with the lack of observed input data. This study evaluated the use of storm events and flood-survey reports to develop and validate a modeling framework for flash flood hazard assessment in data-scarce watersheds. Specifically, we coupled the hydrologic modeling system (HEC-HMS) and the Nays2Dflood hydrodynamic solver to simulate the system response to several storm events including one, equivalent in magnitude to a 500-year event, that flooded the City of Tena (Ecuador) on 2 September, 2017. Results from the coupled approach showed satisfactory model performance in simulating streamflow and water depths (0.40 ≤ Nash-Sutcliffe coefficient ≤ 0.95; −3.67% ≤ Percent Bias ≤ 23.4%) in six of the eight evaluated events, and a good agreement between simulated and surveyed flooded areas (Fit Index = 0.8) after the 500-year storm. The proposed methodology can be used by modelers and decision-makers for flood impact assessment in data-scarce watersheds and as a starting point for the establishment of flood forecasting systems to lessen the impacts of flood events at the local scale.https://www.mdpi.com/2073-4441/12/10/2768flood hazard assessmentdata scarcitymodel couplingevent samplingsurvey data
spellingShingle Jorge Hurtado-Pidal
Juan S. Acero Triana
Edgar Espitia-Sarmiento
Fernando Jarrín-Pérez
Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
Water
flood hazard assessment
data scarcity
model coupling
event sampling
survey data
title Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
title_full Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
title_fullStr Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
title_full_unstemmed Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
title_short Flood Hazard Assessment in Data-Scarce Watersheds Using Model Coupling, Event Sampling, and Survey Data
title_sort flood hazard assessment in data scarce watersheds using model coupling event sampling and survey data
topic flood hazard assessment
data scarcity
model coupling
event sampling
survey data
url https://www.mdpi.com/2073-4441/12/10/2768
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AT edgarespitiasarmiento floodhazardassessmentindatascarcewatershedsusingmodelcouplingeventsamplingandsurveydata
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