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The Effect of Storm Direction on Flood Frequency Analysis
Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Ca...
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Published in: | Geophysical research letters 2021-05, Vol.48 (9), p.n/a |
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description | Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Carlo approach where stochastically transposed storms drive hydrologic simulations over medium and mesoscale watersheds in the Midwestern United States. Systematic rotations of these watersheds are used to emulate changes in the preferential storm direction. We found that the peak flow distribution impacts are scale‐dependent, with larger changes observed in the mesoscale watershed than in the medium‐scale watershed. We attribute this to the high diversity of storm patterns and the storms' scale relative to watershed size. This study highlights the potential of the proposed stochastic framework to address fundamental questions about hydrologic extremes when our ability to observe these events in nature is hindered by technical constraints and short time records.
Plain Language Summary
Estimating the likelihood of extreme events such as floods is becoming more challenging because climate change affects storm patterns worldwide. This study focuses on understanding how storm direction affects the probability distribution of peak flows, which is essential for floodplain mapping and engineering design of resilient infrastructure under future climate. Our results suggest that storm direction has minor implications for these probability distributions in medium‐sized watersheds or smaller (order of 4,000 km2) but can significantly affect larger watersheds, particularly for the largest flood events. Our findings point to avenues for future interdisciplinary analyses of the complex, dynamic role of rainfall structure in flooding.
Key Points
The importance of storm direction in peak flow distribution is mainly driven by the relative difference of storm and watershed size
Expected changes in predominant storm trajectories can significantly modify peak flow distributions
Regionalization of peak flow distributions should account for the effects of the relative orientation of storms and watersheds |
doi_str_mv | 10.1029/2020GL091918 |
format | article |
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Plain Language Summary
Estimating the likelihood of extreme events such as floods is becoming more challenging because climate change affects storm patterns worldwide. This study focuses on understanding how storm direction affects the probability distribution of peak flows, which is essential for floodplain mapping and engineering design of resilient infrastructure under future climate. Our results suggest that storm direction has minor implications for these probability distributions in medium‐sized watersheds or smaller (order of 4,000 km2) but can significantly affect larger watersheds, particularly for the largest flood events. Our findings point to avenues for future interdisciplinary analyses of the complex, dynamic role of rainfall structure in flooding.
Key Points
The importance of storm direction in peak flow distribution is mainly driven by the relative difference of storm and watershed size
Expected changes in predominant storm trajectories can significantly modify peak flow distributions
Regionalization of peak flow distributions should account for the effects of the relative orientation of storms and watersheds</description><identifier>ISSN: 0094-8276</identifier><identifier>EISSN: 1944-8007</identifier><identifier>DOI: 10.1029/2020GL091918</identifier><language>eng</language><publisher>United States: American Geophysical Union (AGU)</publisher><subject>Hydrologic modeling ; peak flow distribution ; storm direction ; storm transposition</subject><ispartof>Geophysical research letters, 2021-05, Vol.48 (9), p.n/a</ispartof><rights>2021. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3436-c943aba65bea47108a9c1b18dc883ad36704cc66728bea4b2754d64e3e2ac5823</citedby><cites>FETCH-LOGICAL-c3436-c943aba65bea47108a9c1b18dc883ad36704cc66728bea4b2754d64e3e2ac5823</cites><orcidid>0000-0003-3880-0874 ; 0000-0002-2957-6252 ; 0000-0002-9050-4266 ; 0000-0001-8045-5926 ; 0000000290504266 ; 0000000180455926 ; 0000000229576252 ; 0000000338800874</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2020GL091918$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2020GL091918$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,780,784,885,11514,27924,27925,46468,46892</link.rule.ids><backlink>$$Uhttps://www.osti.gov/biblio/1786631$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Perez, G.</creatorcontrib><creatorcontrib>Gomez‐Velez, J. D.</creatorcontrib><creatorcontrib>Mantilla, R.</creatorcontrib><creatorcontrib>Wright, D. B.</creatorcontrib><creatorcontrib>Li, Z.</creatorcontrib><title>The Effect of Storm Direction on Flood Frequency Analysis</title><title>Geophysical research letters</title><description>Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Carlo approach where stochastically transposed storms drive hydrologic simulations over medium and mesoscale watersheds in the Midwestern United States. Systematic rotations of these watersheds are used to emulate changes in the preferential storm direction. We found that the peak flow distribution impacts are scale‐dependent, with larger changes observed in the mesoscale watershed than in the medium‐scale watershed. We attribute this to the high diversity of storm patterns and the storms' scale relative to watershed size. This study highlights the potential of the proposed stochastic framework to address fundamental questions about hydrologic extremes when our ability to observe these events in nature is hindered by technical constraints and short time records.
Plain Language Summary
Estimating the likelihood of extreme events such as floods is becoming more challenging because climate change affects storm patterns worldwide. This study focuses on understanding how storm direction affects the probability distribution of peak flows, which is essential for floodplain mapping and engineering design of resilient infrastructure under future climate. Our results suggest that storm direction has minor implications for these probability distributions in medium‐sized watersheds or smaller (order of 4,000 km2) but can significantly affect larger watersheds, particularly for the largest flood events. Our findings point to avenues for future interdisciplinary analyses of the complex, dynamic role of rainfall structure in flooding.
Key Points
The importance of storm direction in peak flow distribution is mainly driven by the relative difference of storm and watershed size
Expected changes in predominant storm trajectories can significantly modify peak flow distributions
Regionalization of peak flow distributions should account for the effects of the relative orientation of storms and watersheds</description><subject>Hydrologic modeling</subject><subject>peak flow distribution</subject><subject>storm direction</subject><subject>storm transposition</subject><issn>0094-8276</issn><issn>1944-8007</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp90E1LAzEQBuAgCtbqzR8QPLs6-dh8HEttq7AgaD2HbDZLI9uNJiuy_94t9eBJGJgZeBiGF6FrAncEqL6nQGFTgSaaqBM0I5rzQgHIUzQD0NNMpThHFzm_AwADRmZIb3cer9rWuwHHFr8OMe3xQ0jTHmKPp1p3MTZ4nfznl-_diBe97cYc8iU6a22X_dVvn6O39Wq7fCyq583TclEVjnEmCqc5s7UVZe0tlwSU1Y7URDVOKWYbJiRw54SQVB1ETWXJG8E989S6UlE2RzfHuzEPwWQXBu92Lvb99KIhUgnByIRuj8ilmHPyrflIYW_TaAiYQzbmbzYTp0f-HTo__mvN5qUSlJWC_QBhnWNQ</recordid><startdate>20210516</startdate><enddate>20210516</enddate><creator>Perez, G.</creator><creator>Gomez‐Velez, J. D.</creator><creator>Mantilla, R.</creator><creator>Wright, D. B.</creator><creator>Li, Z.</creator><general>American Geophysical Union (AGU)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000-0003-3880-0874</orcidid><orcidid>https://orcid.org/0000-0002-2957-6252</orcidid><orcidid>https://orcid.org/0000-0002-9050-4266</orcidid><orcidid>https://orcid.org/0000-0001-8045-5926</orcidid><orcidid>https://orcid.org/0000000290504266</orcidid><orcidid>https://orcid.org/0000000180455926</orcidid><orcidid>https://orcid.org/0000000229576252</orcidid><orcidid>https://orcid.org/0000000338800874</orcidid></search><sort><creationdate>20210516</creationdate><title>The Effect of Storm Direction on Flood Frequency Analysis</title><author>Perez, G. ; Gomez‐Velez, J. D. ; Mantilla, R. ; Wright, D. B. ; Li, Z.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3436-c943aba65bea47108a9c1b18dc883ad36704cc66728bea4b2754d64e3e2ac5823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Hydrologic modeling</topic><topic>peak flow distribution</topic><topic>storm direction</topic><topic>storm transposition</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Perez, G.</creatorcontrib><creatorcontrib>Gomez‐Velez, J. D.</creatorcontrib><creatorcontrib>Mantilla, R.</creatorcontrib><creatorcontrib>Wright, D. B.</creatorcontrib><creatorcontrib>Li, Z.</creatorcontrib><collection>CrossRef</collection><collection>OSTI.GOV</collection><jtitle>Geophysical research letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Perez, G.</au><au>Gomez‐Velez, J. D.</au><au>Mantilla, R.</au><au>Wright, D. B.</au><au>Li, Z.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Effect of Storm Direction on Flood Frequency Analysis</atitle><jtitle>Geophysical research letters</jtitle><date>2021-05-16</date><risdate>2021</risdate><volume>48</volume><issue>9</issue><epage>n/a</epage><issn>0094-8276</issn><eissn>1944-8007</eissn><abstract>Storm direction modulates a hydrograph's magnitude and duration, thus having a potentially large effect on local flood risk. However, how changes in the preferential storm direction affect the probability distribution of peak flows remains unknown. We address this question with a novel Monte Carlo approach where stochastically transposed storms drive hydrologic simulations over medium and mesoscale watersheds in the Midwestern United States. Systematic rotations of these watersheds are used to emulate changes in the preferential storm direction. We found that the peak flow distribution impacts are scale‐dependent, with larger changes observed in the mesoscale watershed than in the medium‐scale watershed. We attribute this to the high diversity of storm patterns and the storms' scale relative to watershed size. This study highlights the potential of the proposed stochastic framework to address fundamental questions about hydrologic extremes when our ability to observe these events in nature is hindered by technical constraints and short time records.
Plain Language Summary
Estimating the likelihood of extreme events such as floods is becoming more challenging because climate change affects storm patterns worldwide. This study focuses on understanding how storm direction affects the probability distribution of peak flows, which is essential for floodplain mapping and engineering design of resilient infrastructure under future climate. Our results suggest that storm direction has minor implications for these probability distributions in medium‐sized watersheds or smaller (order of 4,000 km2) but can significantly affect larger watersheds, particularly for the largest flood events. Our findings point to avenues for future interdisciplinary analyses of the complex, dynamic role of rainfall structure in flooding.
Key Points
The importance of storm direction in peak flow distribution is mainly driven by the relative difference of storm and watershed size
Expected changes in predominant storm trajectories can significantly modify peak flow distributions
Regionalization of peak flow distributions should account for the effects of the relative orientation of storms and watersheds</abstract><cop>United States</cop><pub>American Geophysical Union (AGU)</pub><doi>10.1029/2020GL091918</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-3880-0874</orcidid><orcidid>https://orcid.org/0000-0002-2957-6252</orcidid><orcidid>https://orcid.org/0000-0002-9050-4266</orcidid><orcidid>https://orcid.org/0000-0001-8045-5926</orcidid><orcidid>https://orcid.org/0000000290504266</orcidid><orcidid>https://orcid.org/0000000180455926</orcidid><orcidid>https://orcid.org/0000000229576252</orcidid><orcidid>https://orcid.org/0000000338800874</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Hydrologic modeling peak flow distribution storm direction storm transposition |
title | The Effect of Storm Direction on Flood Frequency Analysis |
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