A method for probabilistic flash flood forecasting
•A novel method for probabilistic flash flood forecasting is explained.•We input a stormscale NWP ensemble into a distributed hydrological model.•The method proved successful in forecasting flash flooding many hours in advance.•The method positively forecasted specific basin scales impacted by flash...
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Veröffentlicht in: | Journal of hydrology (Amsterdam) 2016-10, Vol.541, p.480-494 |
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creator | Hardy, Jill Gourley, Jonathan J. Kirstetter, Pierre-Emmanuel Hong, Yang Kong, Fanyou Flamig, Zachary L. |
description | •A novel method for probabilistic flash flood forecasting is explained.•We input a stormscale NWP ensemble into a distributed hydrological model.•The method proved successful in forecasting flash flooding many hours in advance.•The method positively forecasted specific basin scales impacted by flash flooding.•The method yielded probabilistic information about the hydrologic response.
Flash flooding is one of the most costly and deadly natural hazards in the United States and across the globe. This study advances the use of high-resolution quantitative precipitation forecasts (QPFs) for flash flood forecasting. The QPFs are derived from a stormscale ensemble prediction system, and used within a distributed hydrological model framework to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Before creating the PFFFs, it is important to characterize QPF uncertainty, particularly in terms of location which is the most problematic for hydrological use of QPFs. The SAL methodology (Wernli et al., 2008), which stands for structure, amplitude, and location, is used for this error quantification, with a focus on location. Finally, the PFFF methodology is proposed that produces probabilistic hydrological forecasts. The main advantages of this method are: (1) identifying specific basin scales that are forecast to be impacted by flash flooding; (2) yielding probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the QPFs; (3) improving lead time by using stormscale NWP ensemble forecasts; and (4) not requiring multiple simulations, which are computationally demanding. |
doi_str_mv | 10.1016/j.jhydrol.2016.04.007 |
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Flash flooding is one of the most costly and deadly natural hazards in the United States and across the globe. This study advances the use of high-resolution quantitative precipitation forecasts (QPFs) for flash flood forecasting. The QPFs are derived from a stormscale ensemble prediction system, and used within a distributed hydrological model framework to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Before creating the PFFFs, it is important to characterize QPF uncertainty, particularly in terms of location which is the most problematic for hydrological use of QPFs. The SAL methodology (Wernli et al., 2008), which stands for structure, amplitude, and location, is used for this error quantification, with a focus on location. Finally, the PFFF methodology is proposed that produces probabilistic hydrological forecasts. The main advantages of this method are: (1) identifying specific basin scales that are forecast to be impacted by flash flooding; (2) yielding probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the QPFs; (3) improving lead time by using stormscale NWP ensemble forecasts; and (4) not requiring multiple simulations, which are computationally demanding.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2016.04.007</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Distributed modeling ; Flash flood ; Flash flooding ; Forecasting ; Freshwater ; Hydrology ; Mathematical models ; Methodology ; NWP ; Probabilistic ; Probabilistic methods ; Probability theory ; Uncertainty</subject><ispartof>Journal of hydrology (Amsterdam), 2016-10, Vol.541, p.480-494</ispartof><rights>2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a445t-3417dddc6b6db4da98e801ef96559e317d48764907de7bbe6bf5e4745bd4ef363</citedby><cites>FETCH-LOGICAL-a445t-3417dddc6b6db4da98e801ef96559e317d48764907de7bbe6bf5e4745bd4ef363</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jhydrol.2016.04.007$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Hardy, Jill</creatorcontrib><creatorcontrib>Gourley, Jonathan J.</creatorcontrib><creatorcontrib>Kirstetter, Pierre-Emmanuel</creatorcontrib><creatorcontrib>Hong, Yang</creatorcontrib><creatorcontrib>Kong, Fanyou</creatorcontrib><creatorcontrib>Flamig, Zachary L.</creatorcontrib><title>A method for probabilistic flash flood forecasting</title><title>Journal of hydrology (Amsterdam)</title><description>•A novel method for probabilistic flash flood forecasting is explained.•We input a stormscale NWP ensemble into a distributed hydrological model.•The method proved successful in forecasting flash flooding many hours in advance.•The method positively forecasted specific basin scales impacted by flash flooding.•The method yielded probabilistic information about the hydrologic response.
Flash flooding is one of the most costly and deadly natural hazards in the United States and across the globe. This study advances the use of high-resolution quantitative precipitation forecasts (QPFs) for flash flood forecasting. The QPFs are derived from a stormscale ensemble prediction system, and used within a distributed hydrological model framework to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Before creating the PFFFs, it is important to characterize QPF uncertainty, particularly in terms of location which is the most problematic for hydrological use of QPFs. The SAL methodology (Wernli et al., 2008), which stands for structure, amplitude, and location, is used for this error quantification, with a focus on location. Finally, the PFFF methodology is proposed that produces probabilistic hydrological forecasts. The main advantages of this method are: (1) identifying specific basin scales that are forecast to be impacted by flash flooding; (2) yielding probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the QPFs; (3) improving lead time by using stormscale NWP ensemble forecasts; and (4) not requiring multiple simulations, which are computationally demanding.</description><subject>Distributed modeling</subject><subject>Flash flood</subject><subject>Flash flooding</subject><subject>Forecasting</subject><subject>Freshwater</subject><subject>Hydrology</subject><subject>Mathematical models</subject><subject>Methodology</subject><subject>NWP</subject><subject>Probabilistic</subject><subject>Probabilistic methods</subject><subject>Probability theory</subject><subject>Uncertainty</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqNkEtLAzEQx4MoWKsfQdijl10nm9fuSUrxBQUveg7JZtZm2TY12Qr99qbUu85hhnn9mfkRckuhokDl_VAN64OLYazqnFbAKwB1Rma0UW1ZK1DnZAZQ1yWVLb8kVykNkI0xPiP1otjgtA6u6EMsdjFYY_3o0-S7oh9NWmcfTl3sTC5vP6_JRW_GhDe_cU4-nh7fly_l6u35dblYlYZzMZWMU-Wc66SVznJn2gYboNi3UogWWW7yRknegnKorEVpe4FccWEdx55JNid3J9181dce06Q3PnU4jmaLYZ80bbhoQCmh_jHKFANKxVFVnEa7GFKK2Otd9BsTD5qCPuLUg_7FqY84NXCdcea9h9Me5pe_PUadOo_bDp3PZCbtgv9D4Qft6oA1</recordid><startdate>201610</startdate><enddate>201610</enddate><creator>Hardy, Jill</creator><creator>Gourley, Jonathan J.</creator><creator>Kirstetter, Pierre-Emmanuel</creator><creator>Hong, Yang</creator><creator>Kong, Fanyou</creator><creator>Flamig, Zachary L.</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201610</creationdate><title>A method for probabilistic flash flood forecasting</title><author>Hardy, Jill ; 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Flash flooding is one of the most costly and deadly natural hazards in the United States and across the globe. This study advances the use of high-resolution quantitative precipitation forecasts (QPFs) for flash flood forecasting. The QPFs are derived from a stormscale ensemble prediction system, and used within a distributed hydrological model framework to yield basin-specific, probabilistic flash flood forecasts (PFFFs). Before creating the PFFFs, it is important to characterize QPF uncertainty, particularly in terms of location which is the most problematic for hydrological use of QPFs. The SAL methodology (Wernli et al., 2008), which stands for structure, amplitude, and location, is used for this error quantification, with a focus on location. Finally, the PFFF methodology is proposed that produces probabilistic hydrological forecasts. The main advantages of this method are: (1) identifying specific basin scales that are forecast to be impacted by flash flooding; (2) yielding probabilistic information about the forecast hydrologic response that accounts for the locational uncertainties of the QPFs; (3) improving lead time by using stormscale NWP ensemble forecasts; and (4) not requiring multiple simulations, which are computationally demanding.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2016.04.007</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Distributed modeling Flash flood Flash flooding Forecasting Freshwater Hydrology Mathematical models Methodology NWP Probabilistic Probabilistic methods Probability theory Uncertainty |
title | A method for probabilistic flash flood forecasting |
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