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Radar rainfall estimation in the context of post-event analysis of flash-flood events
A method to estimate rainfall from radar data for post-event analysis of flash-flood events has been developed within the EC-funded HYDRATE project. It follows a pragmatic approach including careful analysis of the observation conditions for the radar system(s) available for the considered case. Clu...
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Published in: | Journal of hydrology (Amsterdam) 2010-11, Vol.394 (1-2), p.17-27 |
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creator | Bouilloud, Ludovic Delrieu, Guy Boudevillain, Brice Kirstetter, Pierre-Emmanuel |
description | A method to estimate rainfall from radar data for post-event analysis of flash-flood events has been developed within the EC-funded HYDRATE project. It follows a pragmatic approach including careful analysis of the observation conditions for the radar system(s) available for the considered case. Clutter and beam blockage are characterised by dry-weather observations and simulations based on a digital terrain model of the region of interest. The vertical profile of reflectivity (VPR) is either inferred from radar data if volume scanning data are available or simply defined using basic meteorological parameters (idealised VPR). Such information is then used to produce correction factor maps for each elevation angle to correct for range-dependent errors. In a second step, an effective Z–R relationship is optimised to remove the bias over the hit region. Due to limited data availability, the optimisation is carried out with reference to raingauge rain amounts measured at the event time scale. Sensitivity tests performed with two well-documented rain events show that a number of Z=aRb relationships, organised along hyperbolic curves in the (a and b) parameter space, lead to optimum assessment results in terms of the Nash coefficient between the radar and raingauge estimates. A refined analysis of these equifinality patterns shows that the “total additive conditional bias” can be used to discriminate between the Nash coefficient equifinal solutions. We observe that the optimisation results are sensitive to the VPR description and also that the Z–R optimisation procedure can largely compensate for range-dependent errors, although this shifts the optimal coefficients in the parameter space. The time-scale dependency of the equifinality patterns is significant, however near-optimal Z–R relationships can be obtained at all time scales from the event time step optimisation. |
doi_str_mv | 10.1016/j.jhydrol.2010.02.035 |
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Sensitivity tests performed with two well-documented rain events show that a number of Z=aRb relationships, organised along hyperbolic curves in the (a and b) parameter space, lead to optimum assessment results in terms of the Nash coefficient between the radar and raingauge estimates. A refined analysis of these equifinality patterns shows that the “total additive conditional bias” can be used to discriminate between the Nash coefficient equifinal solutions. We observe that the optimisation results are sensitive to the VPR description and also that the Z–R optimisation procedure can largely compensate for range-dependent errors, although this shifts the optimal coefficients in the parameter space. 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It follows a pragmatic approach including careful analysis of the observation conditions for the radar system(s) available for the considered case. Clutter and beam blockage are characterised by dry-weather observations and simulations based on a digital terrain model of the region of interest. The vertical profile of reflectivity (VPR) is either inferred from radar data if volume scanning data are available or simply defined using basic meteorological parameters (idealised VPR). Such information is then used to produce correction factor maps for each elevation angle to correct for range-dependent errors. In a second step, an effective Z–R relationship is optimised to remove the bias over the hit region. Due to limited data availability, the optimisation is carried out with reference to raingauge rain amounts measured at the event time scale. Sensitivity tests performed with two well-documented rain events show that a number of Z=aRb relationships, organised along hyperbolic curves in the (a and b) parameter space, lead to optimum assessment results in terms of the Nash coefficient between the radar and raingauge estimates. A refined analysis of these equifinality patterns shows that the “total additive conditional bias” can be used to discriminate between the Nash coefficient equifinal solutions. We observe that the optimisation results are sensitive to the VPR description and also that the Z–R optimisation procedure can largely compensate for range-dependent errors, although this shifts the optimal coefficients in the parameter space. The time-scale dependency of the equifinality patterns is significant, however near-optimal Z–R relationships can be obtained at all time scales from the event time step optimisation.</description><subject>Coefficients</subject><subject>Earth Sciences</subject><subject>Estimates</subject><subject>Extreme rainfall events</subject><subject>Flash-floods</subject><subject>Mathematical models</subject><subject>Meteorology</subject><subject>Optimization</subject><subject>Radar</subject><subject>Radar data</subject><subject>Radar quantitative precipitation estimation</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Sciences of the Universe</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNqFkF2LEzEUhoMoWKs_QcydIEz3ZDKZmVzJsqgrFAS11-FMPmxKdlKTtNh_b-os3m5uAifPeU_OQ8hbBhsGrL85bA77i0kxbFqoNWg3wMUzsmLjIJt2gOE5WQG0bcN62b0kr3I-QD2cdyuy-44GE03oZ4chUJuLf8Di40z9TMveUh3nYv8UGh09xlwae7ZzoThjuGSfr2UXMO8bF2I09N9rfk1e1LRs3zzea7L7_Onn3X2z_fbl693ttsGu5aVhZuJsQsRuElIyaY1kMA7txB06yUw3Sq1t52AQnFup-VhZYSzgJLRwwNfkw5K7x6COqf48XVREr-5vt8rP-aQARF8V9GdW4fcLfEzx96kuqh581jYEnG08ZTUyIbjkcqikWEidYs7Juv_ZDNRVuTqoR-XqqlxBq6ry2vdu6XMYFf5KPqvdjwpwYBL6vi6xJh8XwlYrZ2-TytrbWVvjk9VFmeifmPEXG-mW7g</recordid><startdate>20101117</startdate><enddate>20101117</enddate><creator>Bouilloud, Ludovic</creator><creator>Delrieu, Guy</creator><creator>Boudevillain, Brice</creator><creator>Kirstetter, Pierre-Emmanuel</creator><general>Elsevier B.V</general><general>[Amsterdam; New York]: Elsevier</general><general>Elsevier</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-1771-4953</orcidid></search><sort><creationdate>20101117</creationdate><title>Radar rainfall estimation in the context of post-event analysis of flash-flood events</title><author>Bouilloud, Ludovic ; Delrieu, Guy ; Boudevillain, Brice ; Kirstetter, Pierre-Emmanuel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a423t-1db31baaa4b59919ed910872b3faf91d489cce4f07533e9c38aaa5de0ab5c5f03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Coefficients</topic><topic>Earth Sciences</topic><topic>Estimates</topic><topic>Extreme rainfall events</topic><topic>Flash-floods</topic><topic>Mathematical models</topic><topic>Meteorology</topic><topic>Optimization</topic><topic>Radar</topic><topic>Radar data</topic><topic>Radar quantitative precipitation estimation</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Sciences of the Universe</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bouilloud, Ludovic</creatorcontrib><creatorcontrib>Delrieu, Guy</creatorcontrib><creatorcontrib>Boudevillain, Brice</creatorcontrib><creatorcontrib>Kirstetter, Pierre-Emmanuel</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bouilloud, Ludovic</au><au>Delrieu, Guy</au><au>Boudevillain, Brice</au><au>Kirstetter, Pierre-Emmanuel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Radar rainfall estimation in the context of post-event analysis of flash-flood events</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2010-11-17</date><risdate>2010</risdate><volume>394</volume><issue>1-2</issue><spage>17</spage><epage>27</epage><pages>17-27</pages><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>A method to estimate rainfall from radar data for post-event analysis of flash-flood events has been developed within the EC-funded HYDRATE project. 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Sensitivity tests performed with two well-documented rain events show that a number of Z=aRb relationships, organised along hyperbolic curves in the (a and b) parameter space, lead to optimum assessment results in terms of the Nash coefficient between the radar and raingauge estimates. A refined analysis of these equifinality patterns shows that the “total additive conditional bias” can be used to discriminate between the Nash coefficient equifinal solutions. We observe that the optimisation results are sensitive to the VPR description and also that the Z–R optimisation procedure can largely compensate for range-dependent errors, although this shifts the optimal coefficients in the parameter space. 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subjects | Coefficients Earth Sciences Estimates Extreme rainfall events Flash-floods Mathematical models Meteorology Optimization Radar Radar data Radar quantitative precipitation estimation Rain Rainfall Sciences of the Universe |
title | Radar rainfall estimation in the context of post-event analysis of flash-flood events |
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