Hurricane Harvey highlights: Need to assess the adequacy of probable maximum precipitation estimation methods

Shih Chieh Kao; Scott T. DeNeale; David B. Watson

doi:10.1061/(asce)he.1943-5584.0001768

Hurricane Harvey highlights: Need to assess the adequacy of probable maximum precipitation estimation methods

Shih Chieh Kao, Scott T. DeNeale, David B. Watson

Water Resources Science & Engineering

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

18 Scopus citations

Abstract

Probable maximum precipitation (PMP) is the primary criterion used to design flood protection measures for critical infrastructures such as dams and nuclear power plants. Based on our analysis using the Stage IV (ST4) quantitative precipitation estimates, precipitation associated with Hurricane Harvey near Houston, Texas, represents a PMP-scale storm and partially exceeds the Hydrometeorological Report No. 51 (HMR51) 72-h PMP estimates at 5,000 mi² (ST4 = 805 mm; HMR51 = 780 mm) and 10,000 mi² (ST4 = 686 mm; HMR51 = 673 mm). We also find statistically significant increasing trends since 1949 in the annual maximum total precipitable water and dew point temperature observations along the US Gulf Coast region, suggesting that, if the trend continues, the theoretical upper bound of PMP could be even larger. Our analysis of Hurricane Harvey rainfall data demonstrates that an extremely large PMP-scale storm is physically possible and that PMP estimates should not be considered overly conservative. This case study highlights the need for improved PMP estimation methodologies to account for long-term trends and to ensure the safety of our critical infrastructures.

Original language	English
Article number	05019005
Journal	Journal of Hydrologic Engineering
Volume	24
Issue number	4
DOIs	https://doi.org/10.1061/(asce)he.1943-5584.0001768
State	Published - Apr 1 2019

Funding

This study was supported by the Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development Program. The research used resources of the Oak Ridge Leadership Computing Facility at ORNL. The authors are employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy. Accordingly, the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes.

Keywords

Hurricane Harvey
Infrastructure safety
Probable maximum precipitation
Stage IV quantitative precipitation estimate (QPE)

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10.1061/(asce)he.1943-5584.0001768

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title = "Hurricane Harvey highlights: Need to assess the adequacy of probable maximum precipitation estimation methods",

abstract = "Probable maximum precipitation (PMP) is the primary criterion used to design flood protection measures for critical infrastructures such as dams and nuclear power plants. Based on our analysis using the Stage IV (ST4) quantitative precipitation estimates, precipitation associated with Hurricane Harvey near Houston, Texas, represents a PMP-scale storm and partially exceeds the Hydrometeorological Report No. 51 (HMR51) 72-h PMP estimates at 5,000 mi2 (ST4 = 805 mm; HMR51 = 780 mm) and 10,000 mi2 (ST4 = 686 mm; HMR51 = 673 mm). We also find statistically significant increasing trends since 1949 in the annual maximum total precipitable water and dew point temperature observations along the US Gulf Coast region, suggesting that, if the trend continues, the theoretical upper bound of PMP could be even larger. Our analysis of Hurricane Harvey rainfall data demonstrates that an extremely large PMP-scale storm is physically possible and that PMP estimates should not be considered overly conservative. This case study highlights the need for improved PMP estimation methodologies to account for long-term trends and to ensure the safety of our critical infrastructures.",

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doi = "10.1061/(asce)he.1943-5584.0001768",

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AU - DeNeale, Scott T.

AU - Watson, David B.

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Y1 - 2019/4/1

N2 - Probable maximum precipitation (PMP) is the primary criterion used to design flood protection measures for critical infrastructures such as dams and nuclear power plants. Based on our analysis using the Stage IV (ST4) quantitative precipitation estimates, precipitation associated with Hurricane Harvey near Houston, Texas, represents a PMP-scale storm and partially exceeds the Hydrometeorological Report No. 51 (HMR51) 72-h PMP estimates at 5,000 mi2 (ST4 = 805 mm; HMR51 = 780 mm) and 10,000 mi2 (ST4 = 686 mm; HMR51 = 673 mm). We also find statistically significant increasing trends since 1949 in the annual maximum total precipitable water and dew point temperature observations along the US Gulf Coast region, suggesting that, if the trend continues, the theoretical upper bound of PMP could be even larger. Our analysis of Hurricane Harvey rainfall data demonstrates that an extremely large PMP-scale storm is physically possible and that PMP estimates should not be considered overly conservative. This case study highlights the need for improved PMP estimation methodologies to account for long-term trends and to ensure the safety of our critical infrastructures.

AB - Probable maximum precipitation (PMP) is the primary criterion used to design flood protection measures for critical infrastructures such as dams and nuclear power plants. Based on our analysis using the Stage IV (ST4) quantitative precipitation estimates, precipitation associated with Hurricane Harvey near Houston, Texas, represents a PMP-scale storm and partially exceeds the Hydrometeorological Report No. 51 (HMR51) 72-h PMP estimates at 5,000 mi2 (ST4 = 805 mm; HMR51 = 780 mm) and 10,000 mi2 (ST4 = 686 mm; HMR51 = 673 mm). We also find statistically significant increasing trends since 1949 in the annual maximum total precipitable water and dew point temperature observations along the US Gulf Coast region, suggesting that, if the trend continues, the theoretical upper bound of PMP could be even larger. Our analysis of Hurricane Harvey rainfall data demonstrates that an extremely large PMP-scale storm is physically possible and that PMP estimates should not be considered overly conservative. This case study highlights the need for improved PMP estimation methodologies to account for long-term trends and to ensure the safety of our critical infrastructures.

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Hurricane Harvey highlights: Need to assess the adequacy of probable maximum precipitation estimation methods

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