Regional flood frequency analysis in North Africa

•First regional flood frequency analysis in North Africa with 98 time series of river discharge.•A regional envelope curve for maximum flood in Maghreb countries is provided.•No regional trends in flood hazards.•Regional estimation of flood quantiles from catchment characteristics with 50% mean abso...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of hydrology (Amsterdam) 2024-02, Vol.630, p.130678, Article 130678
Hauptverfasser: Tramblay, Yves, El Khalki, El Mahdi, Khedimallah, Abderrahmane, Sadaoui, Mahrez, Benaabidate, Lahcen, Boulmaiz, Tayeb, Boutaghane, Hamouda, Dakhlaoui, Hamouda, Hanich, Lahoucine, Ludwig, Wolfgang, Meddi, Mohamed, Elmehdi Saidi, Mohamed, Mahé, Gil
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page 130678
container_title Journal of hydrology (Amsterdam)
container_volume 630
creator Tramblay, Yves
El Khalki, El Mahdi
Khedimallah, Abderrahmane
Sadaoui, Mahrez
Benaabidate, Lahcen
Boulmaiz, Tayeb
Boutaghane, Hamouda
Dakhlaoui, Hamouda
Hanich, Lahoucine
Ludwig, Wolfgang
Meddi, Mohamed
Elmehdi Saidi, Mohamed
Mahé, Gil
description •First regional flood frequency analysis in North Africa with 98 time series of river discharge.•A regional envelope curve for maximum flood in Maghreb countries is provided.•No regional trends in flood hazards.•Regional estimation of flood quantiles from catchment characteristics with 50% mean absolute relative errors. The Maghreb countries located in North Africa are strongly impacted by floods, causing extended damage and numerous deaths. Until now, the lack of accessibility of river discharge data prevented regional studies on potential changes in flood hazards or the development of regional flood frequency estimation methods. A new database of daily river discharge data for 98 river basins located in Algeria, Morocco, and Tunisia, has been compiled, with an average of 36 years of complete records over the time period 1960–2018. A peaks-over-threshold sampling of flood events is considered first to detect trends in the annual frequency and the magnitude of floods. The trend analysis results revealed no significant changes in flood frequency or magnitude at the regional level, with only a few spurious trends due to isolated extreme or clustered events. An envelope curve relating maximum floods for a range of catchment areas in North Africa has been developed, for the first time in this region with such a large database. Then, regional estimation methods for flood quantiles were compared. The regional estimation from multiple catchment characteristics (including soil types, land use, elevation, and geology) was performed by comparing two multiple linear regression methods, Stepwise regression and Lasso regression, and a machine learning algorithm, Random Forests. Results indicate a better performance of the Lasso regression to estimate flood quantiles at ungauged locations, with mean absolute relative errors close to 50 % and relative bias close to 20 %. The most relevant catchment predictors identified by the regression models are the topographic wetness index, which provides better estimates than catchment area, but also altitude, mean annual rainfall, and soil bulk density. The results of this study could be useful to improve operational procedures for sizing hydraulic structures at ungauged sites.
doi_str_mv 10.1016/j.jhydrol.2024.130678
format Article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_insu_04729600v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0022169424000726</els_id><sourcerecordid>3153194837</sourcerecordid><originalsourceid>FETCH-LOGICAL-a395t-4dc7c8ebe176beabbf147ffa9b74f7dbb9a4195b2bdbff4f603fdcf42d9f4d7e3</originalsourceid><addsrcrecordid>eNqFkE1Lw0AQhhdRsFZ_gpCjCIn7lWz2JKWoFYqC6HnZT7shzdbdtJB_b0qKV-cyMDzzMvMAcItggSCqHpqi2QwmhrbAENMCEVix-gzMUM14jhlk52AGIcY5qji9BFcpNXAsQugMoA_77UMn28y1IZjMRfuzt50eMjkOh-RT5rvsLcR-ky1c9Fpegwsn22RvTn0Ovp6fPperfP3-8rpcrHNJeNnn1Gima6ssYpWyUimHKHNOcsWoY0YpLinipcLKKOeoqyBxRjuKDXfUMEvm4H7K3chW7KLfyjiIIL1YLdbCd2kvIGWYVxAe0AjfTfAuhvH-1IutT9q2rexs2CdBUEkQpzVhI1pOqI4hpWjdXziC4uhTNOLkUxx9isnnuPc47dnx6YO3USTtR1PW-Gh1L0zw_yT8As5yga8</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3153194837</pqid></control><display><type>article</type><title>Regional flood frequency analysis in North Africa</title><source>Elsevier ScienceDirect Journals</source><creator>Tramblay, Yves ; El Khalki, El Mahdi ; Khedimallah, Abderrahmane ; Sadaoui, Mahrez ; Benaabidate, Lahcen ; Boulmaiz, Tayeb ; Boutaghane, Hamouda ; Dakhlaoui, Hamouda ; Hanich, Lahoucine ; Ludwig, Wolfgang ; Meddi, Mohamed ; Elmehdi Saidi, Mohamed ; Mahé, Gil</creator><creatorcontrib>Tramblay, Yves ; El Khalki, El Mahdi ; Khedimallah, Abderrahmane ; Sadaoui, Mahrez ; Benaabidate, Lahcen ; Boulmaiz, Tayeb ; Boutaghane, Hamouda ; Dakhlaoui, Hamouda ; Hanich, Lahoucine ; Ludwig, Wolfgang ; Meddi, Mohamed ; Elmehdi Saidi, Mohamed ; Mahé, Gil</creatorcontrib><description>•First regional flood frequency analysis in North Africa with 98 time series of river discharge.•A regional envelope curve for maximum flood in Maghreb countries is provided.•No regional trends in flood hazards.•Regional estimation of flood quantiles from catchment characteristics with 50% mean absolute relative errors. The Maghreb countries located in North Africa are strongly impacted by floods, causing extended damage and numerous deaths. Until now, the lack of accessibility of river discharge data prevented regional studies on potential changes in flood hazards or the development of regional flood frequency estimation methods. A new database of daily river discharge data for 98 river basins located in Algeria, Morocco, and Tunisia, has been compiled, with an average of 36 years of complete records over the time period 1960–2018. A peaks-over-threshold sampling of flood events is considered first to detect trends in the annual frequency and the magnitude of floods. The trend analysis results revealed no significant changes in flood frequency or magnitude at the regional level, with only a few spurious trends due to isolated extreme or clustered events. An envelope curve relating maximum floods for a range of catchment areas in North Africa has been developed, for the first time in this region with such a large database. Then, regional estimation methods for flood quantiles were compared. The regional estimation from multiple catchment characteristics (including soil types, land use, elevation, and geology) was performed by comparing two multiple linear regression methods, Stepwise regression and Lasso regression, and a machine learning algorithm, Random Forests. Results indicate a better performance of the Lasso regression to estimate flood quantiles at ungauged locations, with mean absolute relative errors close to 50 % and relative bias close to 20 %. The most relevant catchment predictors identified by the regression models are the topographic wetness index, which provides better estimates than catchment area, but also altitude, mean annual rainfall, and soil bulk density. The results of this study could be useful to improve operational procedures for sizing hydraulic structures at ungauged sites.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2024.130678</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Algeria ; algorithms ; altitude ; land use ; Maghreb ; Morocco ; rain ; regression analysis ; river flow ; rivers ; Sciences of the Universe ; soil density ; Tunisia ; watersheds</subject><ispartof>Journal of hydrology (Amsterdam), 2024-02, Vol.630, p.130678, Article 130678</ispartof><rights>2024 The Author(s)</rights><rights>Attribution</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a395t-4dc7c8ebe176beabbf147ffa9b74f7dbb9a4195b2bdbff4f603fdcf42d9f4d7e3</cites><orcidid>0000-0002-5776-7638 ; 0000-0003-0002-0696 ; 0000-0003-0481-5330 ; 0000-0002-0081-750X ; 0000-0002-0736-5948</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0022169424000726$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://insu.hal.science/insu-04729600$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Tramblay, Yves</creatorcontrib><creatorcontrib>El Khalki, El Mahdi</creatorcontrib><creatorcontrib>Khedimallah, Abderrahmane</creatorcontrib><creatorcontrib>Sadaoui, Mahrez</creatorcontrib><creatorcontrib>Benaabidate, Lahcen</creatorcontrib><creatorcontrib>Boulmaiz, Tayeb</creatorcontrib><creatorcontrib>Boutaghane, Hamouda</creatorcontrib><creatorcontrib>Dakhlaoui, Hamouda</creatorcontrib><creatorcontrib>Hanich, Lahoucine</creatorcontrib><creatorcontrib>Ludwig, Wolfgang</creatorcontrib><creatorcontrib>Meddi, Mohamed</creatorcontrib><creatorcontrib>Elmehdi Saidi, Mohamed</creatorcontrib><creatorcontrib>Mahé, Gil</creatorcontrib><title>Regional flood frequency analysis in North Africa</title><title>Journal of hydrology (Amsterdam)</title><description>•First regional flood frequency analysis in North Africa with 98 time series of river discharge.•A regional envelope curve for maximum flood in Maghreb countries is provided.•No regional trends in flood hazards.•Regional estimation of flood quantiles from catchment characteristics with 50% mean absolute relative errors. The Maghreb countries located in North Africa are strongly impacted by floods, causing extended damage and numerous deaths. Until now, the lack of accessibility of river discharge data prevented regional studies on potential changes in flood hazards or the development of regional flood frequency estimation methods. A new database of daily river discharge data for 98 river basins located in Algeria, Morocco, and Tunisia, has been compiled, with an average of 36 years of complete records over the time period 1960–2018. A peaks-over-threshold sampling of flood events is considered first to detect trends in the annual frequency and the magnitude of floods. The trend analysis results revealed no significant changes in flood frequency or magnitude at the regional level, with only a few spurious trends due to isolated extreme or clustered events. An envelope curve relating maximum floods for a range of catchment areas in North Africa has been developed, for the first time in this region with such a large database. Then, regional estimation methods for flood quantiles were compared. The regional estimation from multiple catchment characteristics (including soil types, land use, elevation, and geology) was performed by comparing two multiple linear regression methods, Stepwise regression and Lasso regression, and a machine learning algorithm, Random Forests. Results indicate a better performance of the Lasso regression to estimate flood quantiles at ungauged locations, with mean absolute relative errors close to 50 % and relative bias close to 20 %. The most relevant catchment predictors identified by the regression models are the topographic wetness index, which provides better estimates than catchment area, but also altitude, mean annual rainfall, and soil bulk density. The results of this study could be useful to improve operational procedures for sizing hydraulic structures at ungauged sites.</description><subject>Algeria</subject><subject>algorithms</subject><subject>altitude</subject><subject>land use</subject><subject>Maghreb</subject><subject>Morocco</subject><subject>rain</subject><subject>regression analysis</subject><subject>river flow</subject><subject>rivers</subject><subject>Sciences of the Universe</subject><subject>soil density</subject><subject>Tunisia</subject><subject>watersheds</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkE1Lw0AQhhdRsFZ_gpCjCIn7lWz2JKWoFYqC6HnZT7shzdbdtJB_b0qKV-cyMDzzMvMAcItggSCqHpqi2QwmhrbAENMCEVix-gzMUM14jhlk52AGIcY5qji9BFcpNXAsQugMoA_77UMn28y1IZjMRfuzt50eMjkOh-RT5rvsLcR-ky1c9Fpegwsn22RvTn0Ovp6fPperfP3-8rpcrHNJeNnn1Gima6ssYpWyUimHKHNOcsWoY0YpLinipcLKKOeoqyBxRjuKDXfUMEvm4H7K3chW7KLfyjiIIL1YLdbCd2kvIGWYVxAe0AjfTfAuhvH-1IutT9q2rexs2CdBUEkQpzVhI1pOqI4hpWjdXziC4uhTNOLkUxx9isnnuPc47dnx6YO3USTtR1PW-Gh1L0zw_yT8As5yga8</recordid><startdate>20240201</startdate><enddate>20240201</enddate><creator>Tramblay, Yves</creator><creator>El Khalki, El Mahdi</creator><creator>Khedimallah, Abderrahmane</creator><creator>Sadaoui, Mahrez</creator><creator>Benaabidate, Lahcen</creator><creator>Boulmaiz, Tayeb</creator><creator>Boutaghane, Hamouda</creator><creator>Dakhlaoui, Hamouda</creator><creator>Hanich, Lahoucine</creator><creator>Ludwig, Wolfgang</creator><creator>Meddi, Mohamed</creator><creator>Elmehdi Saidi, Mohamed</creator><creator>Mahé, Gil</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7S9</scope><scope>L.6</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-5776-7638</orcidid><orcidid>https://orcid.org/0000-0003-0002-0696</orcidid><orcidid>https://orcid.org/0000-0003-0481-5330</orcidid><orcidid>https://orcid.org/0000-0002-0081-750X</orcidid><orcidid>https://orcid.org/0000-0002-0736-5948</orcidid></search><sort><creationdate>20240201</creationdate><title>Regional flood frequency analysis in North Africa</title><author>Tramblay, Yves ; El Khalki, El Mahdi ; Khedimallah, Abderrahmane ; Sadaoui, Mahrez ; Benaabidate, Lahcen ; Boulmaiz, Tayeb ; Boutaghane, Hamouda ; Dakhlaoui, Hamouda ; Hanich, Lahoucine ; Ludwig, Wolfgang ; Meddi, Mohamed ; Elmehdi Saidi, Mohamed ; Mahé, Gil</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a395t-4dc7c8ebe176beabbf147ffa9b74f7dbb9a4195b2bdbff4f603fdcf42d9f4d7e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Algeria</topic><topic>algorithms</topic><topic>altitude</topic><topic>land use</topic><topic>Maghreb</topic><topic>Morocco</topic><topic>rain</topic><topic>regression analysis</topic><topic>river flow</topic><topic>rivers</topic><topic>Sciences of the Universe</topic><topic>soil density</topic><topic>Tunisia</topic><topic>watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tramblay, Yves</creatorcontrib><creatorcontrib>El Khalki, El Mahdi</creatorcontrib><creatorcontrib>Khedimallah, Abderrahmane</creatorcontrib><creatorcontrib>Sadaoui, Mahrez</creatorcontrib><creatorcontrib>Benaabidate, Lahcen</creatorcontrib><creatorcontrib>Boulmaiz, Tayeb</creatorcontrib><creatorcontrib>Boutaghane, Hamouda</creatorcontrib><creatorcontrib>Dakhlaoui, Hamouda</creatorcontrib><creatorcontrib>Hanich, Lahoucine</creatorcontrib><creatorcontrib>Ludwig, Wolfgang</creatorcontrib><creatorcontrib>Meddi, Mohamed</creatorcontrib><creatorcontrib>Elmehdi Saidi, Mohamed</creatorcontrib><creatorcontrib>Mahé, Gil</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tramblay, Yves</au><au>El Khalki, El Mahdi</au><au>Khedimallah, Abderrahmane</au><au>Sadaoui, Mahrez</au><au>Benaabidate, Lahcen</au><au>Boulmaiz, Tayeb</au><au>Boutaghane, Hamouda</au><au>Dakhlaoui, Hamouda</au><au>Hanich, Lahoucine</au><au>Ludwig, Wolfgang</au><au>Meddi, Mohamed</au><au>Elmehdi Saidi, Mohamed</au><au>Mahé, Gil</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regional flood frequency analysis in North Africa</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2024-02-01</date><risdate>2024</risdate><volume>630</volume><spage>130678</spage><pages>130678-</pages><artnum>130678</artnum><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>•First regional flood frequency analysis in North Africa with 98 time series of river discharge.•A regional envelope curve for maximum flood in Maghreb countries is provided.•No regional trends in flood hazards.•Regional estimation of flood quantiles from catchment characteristics with 50% mean absolute relative errors. The Maghreb countries located in North Africa are strongly impacted by floods, causing extended damage and numerous deaths. Until now, the lack of accessibility of river discharge data prevented regional studies on potential changes in flood hazards or the development of regional flood frequency estimation methods. A new database of daily river discharge data for 98 river basins located in Algeria, Morocco, and Tunisia, has been compiled, with an average of 36 years of complete records over the time period 1960–2018. A peaks-over-threshold sampling of flood events is considered first to detect trends in the annual frequency and the magnitude of floods. The trend analysis results revealed no significant changes in flood frequency or magnitude at the regional level, with only a few spurious trends due to isolated extreme or clustered events. An envelope curve relating maximum floods for a range of catchment areas in North Africa has been developed, for the first time in this region with such a large database. Then, regional estimation methods for flood quantiles were compared. The regional estimation from multiple catchment characteristics (including soil types, land use, elevation, and geology) was performed by comparing two multiple linear regression methods, Stepwise regression and Lasso regression, and a machine learning algorithm, Random Forests. Results indicate a better performance of the Lasso regression to estimate flood quantiles at ungauged locations, with mean absolute relative errors close to 50 % and relative bias close to 20 %. The most relevant catchment predictors identified by the regression models are the topographic wetness index, which provides better estimates than catchment area, but also altitude, mean annual rainfall, and soil bulk density. The results of this study could be useful to improve operational procedures for sizing hydraulic structures at ungauged sites.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2024.130678</doi><orcidid>https://orcid.org/0000-0002-5776-7638</orcidid><orcidid>https://orcid.org/0000-0003-0002-0696</orcidid><orcidid>https://orcid.org/0000-0003-0481-5330</orcidid><orcidid>https://orcid.org/0000-0002-0081-750X</orcidid><orcidid>https://orcid.org/0000-0002-0736-5948</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0022-1694
ispartof Journal of hydrology (Amsterdam), 2024-02, Vol.630, p.130678, Article 130678
issn 0022-1694
1879-2707
language eng
recordid cdi_hal_primary_oai_HAL_insu_04729600v1
source Elsevier ScienceDirect Journals
subjects Algeria
algorithms
altitude
land use
Maghreb
Morocco
rain
regression analysis
river flow
rivers
Sciences of the Universe
soil density
Tunisia
watersheds
title Regional flood frequency analysis in North Africa
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T21%3A35%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Regional%20flood%20frequency%20analysis%20in%20North%20Africa&rft.jtitle=Journal%20of%20hydrology%20(Amsterdam)&rft.au=Tramblay,%20Yves&rft.date=2024-02-01&rft.volume=630&rft.spage=130678&rft.pages=130678-&rft.artnum=130678&rft.issn=0022-1694&rft.eissn=1879-2707&rft_id=info:doi/10.1016/j.jhydrol.2024.130678&rft_dat=%3Cproquest_hal_p%3E3153194837%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3153194837&rft_id=info:pmid/&rft_els_id=S0022169424000726&rfr_iscdi=true