Impact of hurricane Harvey on the results of regional flood frequency analysis

McDonald, Walter; Naughton, Joseph B.

doi:10.1111/jfr3.12500

Cited by 4 publications

(5 citation statements)

References 23 publications

(31 reference statements)

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“…From this figure there were no clear clusters, and large and small changes in the 100-year peak flows were generally distributed throughout the entire study area. These changes in return period floods are similar to those that occurred where Harvey actually made landfall, which resulted in an average increase in the 100-year flood of 30% (McDonald & Naughton, 2018). This outcome demonstrates that the impact of simulating Harvey on flood frequency statistics is similar, and in some cases greater, in other areas along the Texas coast.…”

Section: Flood Frequency Statisticssupporting

confidence: 62%

“…It is estimated that approximately 8%–19% of Hurricane Harvey's intensity was attributed to climate change (Risser & Wehner, 2017; van Oldenborgh et al, 2017). This intensity had a significant impact on the computation of design floods, as the flooding from Harvey increased the 100‐year peak flow in the region by an average of 28% using flood frequency statistics (McDonald & Naughton, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

Regier

Naughton

McDonald

2021

J Flood Risk Management

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Hurricane Harvey produced unprecedented flooding that altered flood frequency statistics near Houston, Texas. While Harvey could have made landfall elsewhere along the Gulf coast, traditional flood frequency methodologies only consider the risk of Harvey in the region that it hit. This may be a shortcoming of flood frequency methodologies as the intensity of Harvey was greater due to climate change; therefore, Harvey may be more indicative of future hurricanes than other historical observations. To that end, this study investigates what effect Harvey would have had on flood frequency statistics if it had made landfall elsewhere. To do so, a Monte Carlo simulation was used to shift Harvey's rainfall within alternative landfall locations. This rainfall was then applied to synthetic unit hydrographs to estimate peak flows that were applied in Log Pearson III and Regional Flood Frequency Analyses. Log Pearson III analyses with simulated Harvey streamflows produced median 100‐year peak flows that were 17%–66% higher than analyses that only used historical records. A regional flood frequency analysis in the central coastal geomorphologic region of Texas showed that predictive equations, based upon basin area and shape factor, had an average increase of 30.2% in the 100‐year peak discharge.

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Section: Flood Frequency Statisticssupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

Regier

Naughton

McDonald

2021

J Flood Risk Management

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“…The Multi-Radar Multi-Sensor system (MRMS), which utilizes data from over 180 NEXRAD radars and covers the conterminous United States at 1-km spatial resolution with a 2-min update frequency (Zhang et al 2016), has shown more accuracy during Hurricane Harvey event than did NASA's Integrated Multisatellite Retrievals for GPM (IMERG) v6 product and National Centers for Environmental Prediction (NCEP) gridded gauge only precipitation production; and has good agreement with the Harris County Flood Control District (HCFCD) rain gauge data (Chen et al 2020;Li et al 2020). This study, again, uses Hurricane Harvey as the study case, since it was considered a 100-500-yr flood event, which caused the local streams' return period reduced 20%-35% after the event (Vu and Mishra 2019;McDonald and Naughton 2019).…”

Section: Introductionmentioning

confidence: 99%

A comprehensive flood inundation mapping for Hurricane Harvey using an integrated hydrological and hydraulic model

Chen

Gao

et al. 2021

Journal of Hydrometeorology

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As climate change will increase the frequency and intensity of precipitation extremes and coastal flooding, there is a clear need for an integrated hydrology and hydraulic system that has the ability to model the hydrologic conditions over a long period and the flow dynamic representations of when and where the extreme hydrometeorological events occur. This system coupling provides comprehensive information (flood wave, inundation extents and depths) about coastal flood events for emergency management and risk minimization. This study provides an integrated hydrologic and hydraulic coupled modeling system that is based on the Coupled Routing and Excessive Storage (CREST) model and the Australia National University- Geophysics Australia (ANUGA) model to simulate flood. Forced by the near-real-time Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimates (QPEs), this integrated modeling system was applied during the 2017 Hurricane Harvey event to simulate the streamflow, the flood extent, and the inundation depth. The results were compared with post-event Water High Mark (WHM) survey data and its interpolated flood extent by the United States Geological Survey (USGS) and the Federal Emergency Management Agency (FEMA) flood insurance claims, as well as a satellite-based flood map, the National Water Model (NWM) and the Fathom (LISFLOOD-FP) model simulated flood map. The proposing hydrologic and hydraulic model simulation indicated that it could capture 87% of all flood insurance claims within the study area, and the overall error of water depth was 0.91 meters, which is comparable to the mainstream operational flood models (NWM and Fathom).

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Section: Introductionmentioning

confidence: 99%

“…Peak discharge has also been considered as a major variable in univariate analyses. For Hurricane Harvey's flood return period estimations, McDonald and Naughton (2019) applied the Log Pearson III distribution and Nyaupane et al (2018) applied the GEV to discharge data. However, these univariate assessments miss potentially important dependencies between hazards and misrepresent the likelihood of high-impact conditions (Harr et al, 2022).…”

mentioning

confidence: 99%

A Multivariate Frequency Analysis Framework to Estimate the Return Period of Hurricane Events Using Event‐Based Copula

Cho,

Ahmadisharaf,

Done

et al. 2023

Water Resources Research

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This study proposed a framework to evaluate multivariate return periods of hurricanes using event‐based frequency analysis techniques. The applicability of the proposed framework was demonstrated using point‐based and spatial analyses on a recent catastrophic event, Hurricane Ian. Univariate, bivariate, and trivariate frequency analyses were performed by applying generalized extreme value distribution and copula on annual maximum series of flood volume, peak discharge, total rainfall depth, maximum wind speed, wave height and storm surge. As a result of point‐based analyses, return periods of Hurricane Ian was investigated by using our framework; univariate return periods were estimated from 39.2 to 60.2 years, bivariate from 824.1 to 1,592.6 years, and trivariate from 332.1 to 1,722.9 years for the Daytona‐St. Augustine Basin. In the Florida Bay‐Florida Keys Basin, univariate return periods were calculated from 7.5 to 32.9 years, bivariate from 36.5 to 114.9 years, and trivariate from 25.0 to 214.8 years. Using the spatial analyses, we were able to generate the return period map of Hurricane Ian across Florida. Based on bivariate frequency analyses, 18% of hydrologic unit code 8 (HUC8) basins had an average return period of more than 30 years. Sources of uncertainty, due to the scarcity of analysis data, stationarity assumption and impact of other weather systems such as strong frontal passages, were also discussed. Despite these limitations, our framework and results will be valuable in disaster response and recovery.

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Impact of hurricane Harvey on the results of regional flood frequency analysis

Cited by 4 publications

References 23 publications

Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

Transposing flood risk from extreme rainfall events: A case study of Hurricane Harvey

A comprehensive flood inundation mapping for Hurricane Harvey using an integrated hydrological and hydraulic model

A Multivariate Frequency Analysis Framework to Estimate the Return Period of Hurricane Events Using Event‐Based Copula

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