Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium
The k-day extreme precipitation depths ( k=1, 2, 3, 4, 5, 7, 10, 15, 20, 25 and 30) at the climatological network of Belgium (165 stations) are analysed to assess the regional general extreme value (GEV) growth curves and to determine the at-site fractiles. The calendar year and the hydrological sum...
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Veröffentlicht in: | Journal of hydrology (Amsterdam) 2002-11, Vol.268 (1), p.113-126 |
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description | The
k-day extreme precipitation depths (
k=1, 2, 3, 4, 5, 7, 10, 15, 20, 25 and 30) at the climatological network of Belgium (165 stations) are analysed to assess the regional general extreme value (GEV) growth curves and to determine the at-site fractiles. The calendar year and the hydrological summer and winter are considered separately. The method proposed combines regional L-moment estimates of the GEV parameters and tends to take advantage of a few long-term well-documented series. Therefore, a data extension procedure based on the fractiles method has been used to extend the 1951–1995 observation period to the 1910–1995 reference period. This ensures the temporal homogeneity of the series by assessing the possible missing extremes and it places all the series in a reference period, where the stationarity of the extreme precipitation has been verified. Using the nine historical series and generating randomly located missing values the efficiency of three data extension methods has been evaluated. This comparison indicates that a procedure using the regional growth curve satisfies this task. It shows that the residual mean square error of the at-site means is reduced when the mean correlation between the reference station and the series presenting gaps exceeds 0.52 but that the corresponding error on high order fractiles is reduced for all the observed correlation and for large numbers (40–50) of missing values. A practical estimation of the confidence intervals is proposed. |
doi_str_mv | 10.1016/S0022-1694(02)00160-9 |
format | Article |
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k-day extreme precipitation depths (
k=1, 2, 3, 4, 5, 7, 10, 15, 20, 25 and 30) at the climatological network of Belgium (165 stations) are analysed to assess the regional general extreme value (GEV) growth curves and to determine the at-site fractiles. The calendar year and the hydrological summer and winter are considered separately. The method proposed combines regional L-moment estimates of the GEV parameters and tends to take advantage of a few long-term well-documented series. Therefore, a data extension procedure based on the fractiles method has been used to extend the 1951–1995 observation period to the 1910–1995 reference period. This ensures the temporal homogeneity of the series by assessing the possible missing extremes and it places all the series in a reference period, where the stationarity of the extreme precipitation has been verified. Using the nine historical series and generating randomly located missing values the efficiency of three data extension methods has been evaluated. This comparison indicates that a procedure using the regional growth curve satisfies this task. It shows that the residual mean square error of the at-site means is reduced when the mean correlation between the reference station and the series presenting gaps exceeds 0.52 but that the corresponding error on high order fractiles is reduced for all the observed correlation and for large numbers (40–50) of missing values. A practical estimation of the confidence intervals is proposed.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/S0022-1694(02)00160-9</identifier><identifier>CODEN: JHYDA7</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Areal geology. Maps ; Belgium ; Data extension ; Earth sciences ; Earth, ocean, space ; Exact sciences and technology ; Extreme precipitation ; General extreme value distribution ; Geologic maps, cartography ; Hydrology ; Hydrology. Hydrogeology ; L-moments ; Regionalisation</subject><ispartof>Journal of hydrology (Amsterdam), 2002-11, Vol.268 (1), p.113-126</ispartof><rights>2002 Elsevier Science B.V.</rights><rights>2003 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a422t-73d94cfd1b09615912d674c0b69ecbf69c58a800957dd1207f4a341121d62cf33</citedby><cites>FETCH-LOGICAL-a422t-73d94cfd1b09615912d674c0b69ecbf69c58a800957dd1207f4a341121d62cf33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S0022-1694(02)00160-9$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,778,782,3539,27907,27908,45978</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14352727$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Gellens, Daniel</creatorcontrib><title>Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium</title><title>Journal of hydrology (Amsterdam)</title><description>The
k-day extreme precipitation depths (
k=1, 2, 3, 4, 5, 7, 10, 15, 20, 25 and 30) at the climatological network of Belgium (165 stations) are analysed to assess the regional general extreme value (GEV) growth curves and to determine the at-site fractiles. The calendar year and the hydrological summer and winter are considered separately. The method proposed combines regional L-moment estimates of the GEV parameters and tends to take advantage of a few long-term well-documented series. Therefore, a data extension procedure based on the fractiles method has been used to extend the 1951–1995 observation period to the 1910–1995 reference period. This ensures the temporal homogeneity of the series by assessing the possible missing extremes and it places all the series in a reference period, where the stationarity of the extreme precipitation has been verified. Using the nine historical series and generating randomly located missing values the efficiency of three data extension methods has been evaluated. This comparison indicates that a procedure using the regional growth curve satisfies this task. It shows that the residual mean square error of the at-site means is reduced when the mean correlation between the reference station and the series presenting gaps exceeds 0.52 but that the corresponding error on high order fractiles is reduced for all the observed correlation and for large numbers (40–50) of missing values. A practical estimation of the confidence intervals is proposed.</description><subject>Areal geology. Maps</subject><subject>Belgium</subject><subject>Data extension</subject><subject>Earth sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>Extreme precipitation</subject><subject>General extreme value distribution</subject><subject>Geologic maps, cartography</subject><subject>Hydrology</subject><subject>Hydrology. Hydrogeology</subject><subject>L-moments</subject><subject>Regionalisation</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNqFkU-P1SAUxYnRxOfoRzBho9FFFSiFsjLOyziaTOLCP1tC4fLEtPTJbY3GLy99b6LLYUPC-R3uzTmEPOXsFWdcvf7EmBANV0a-YOIlq0-sMffIjvfaNEIzfZ_s_iEPySPE76yetpU78mc_T0PKKR9ogUOasxupOx7L7Pw36nKgwS2Owq8FMlaVVsVDWAvQOBfqEAFxM19ffaUh4VLSsC4bOMfNVWCC6gGfjmlxJyFlegnjIa3TY_IguhHhye19Qb68u_q8f9_cfLz-sH970zgpxNLoNhjpY-ADM4p3hougtPRsUAb8EJXxXe96xkynQ-CC6ShdKzkXPCjhY9tekOfnf-vyP1bAxU4JPYyjyzCvaGtEiveyuxPkvWqVkKyC3Rn0ZUYsEO2xpMmV35Yzu3ViT53YLXDLhD11Yk31Pbsd4NC7MRaXfcL_Ztl2QgtduTdnDmosPxMUiz5BrsmnmuViw5zumPQX12Whxg</recordid><startdate>20021101</startdate><enddate>20021101</enddate><creator>Gellens, Daniel</creator><general>Elsevier B.V</general><general>Elsevier Science</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>KL.</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20021101</creationdate><title>Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium</title><author>Gellens, Daniel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a422t-73d94cfd1b09615912d674c0b69ecbf69c58a800957dd1207f4a341121d62cf33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Areal geology. Maps</topic><topic>Belgium</topic><topic>Data extension</topic><topic>Earth sciences</topic><topic>Earth, ocean, space</topic><topic>Exact sciences and technology</topic><topic>Extreme precipitation</topic><topic>General extreme value distribution</topic><topic>Geologic maps, cartography</topic><topic>Hydrology</topic><topic>Hydrology. Hydrogeology</topic><topic>L-moments</topic><topic>Regionalisation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gellens, Daniel</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gellens, Daniel</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2002-11-01</date><risdate>2002</risdate><volume>268</volume><issue>1</issue><spage>113</spage><epage>126</epage><pages>113-126</pages><issn>0022-1694</issn><eissn>1879-2707</eissn><coden>JHYDA7</coden><abstract>The
k-day extreme precipitation depths (
k=1, 2, 3, 4, 5, 7, 10, 15, 20, 25 and 30) at the climatological network of Belgium (165 stations) are analysed to assess the regional general extreme value (GEV) growth curves and to determine the at-site fractiles. The calendar year and the hydrological summer and winter are considered separately. The method proposed combines regional L-moment estimates of the GEV parameters and tends to take advantage of a few long-term well-documented series. Therefore, a data extension procedure based on the fractiles method has been used to extend the 1951–1995 observation period to the 1910–1995 reference period. This ensures the temporal homogeneity of the series by assessing the possible missing extremes and it places all the series in a reference period, where the stationarity of the extreme precipitation has been verified. Using the nine historical series and generating randomly located missing values the efficiency of three data extension methods has been evaluated. This comparison indicates that a procedure using the regional growth curve satisfies this task. It shows that the residual mean square error of the at-site means is reduced when the mean correlation between the reference station and the series presenting gaps exceeds 0.52 but that the corresponding error on high order fractiles is reduced for all the observed correlation and for large numbers (40–50) of missing values. A practical estimation of the confidence intervals is proposed.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0022-1694(02)00160-9</doi><tpages>14</tpages></addata></record> |
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source | Elsevier ScienceDirect Journals |
subjects | Areal geology. Maps Belgium Data extension Earth sciences Earth, ocean, space Exact sciences and technology Extreme precipitation General extreme value distribution Geologic maps, cartography Hydrology Hydrology. Hydrogeology L-moments Regionalisation |
title | Combining regional approach and data extension procedure for assessing GEV distribution of extreme precipitation in Belgium |
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