A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile
We predict flood events by fitting two simple logistic regression models between mesoscale rainfall and El Niño‐Southern Oscillation (ENSO) index with local scale flooding into the Biobío River Basin in Chile from 1948 to 2002. Two different and complementary logistic models were studied: Logit and...
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| Veröffentlicht in: | Journal of flood risk management 2017-03, Vol.10 (1), p.17-29 |
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| container_title | Journal of flood risk management |
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| creator | Fustos, I. Abarca‐del‐Rio, R. Ávila, A. Orrego, R. |
| description | We predict flood events by fitting two simple logistic regression models between mesoscale rainfall and El Niño‐Southern Oscillation (ENSO) index with local scale flooding into the Biobío River Basin in Chile from 1948 to 2002. Two different and complementary logistic models were studied: Logit and Probit. The models perform alike suggesting that the methodology is robust. The best model is most accurate during the autumn over 80% hit rate and in winter 66% hit rate, which are the seasons with high risk of floods. This work represents a first step in the development of a complete hydrological framework for the Biobío River Basin. The Logit distribution shows better results; thus, we suggest to use this distribution to relate flood events with mesoscale precipitation and ENSO index in the Biobío River Basin. Finally, these results explain the flood events and its relation with risk management. In forthcoming studies we will extend the methodology over this region and Chile taking advantage of the availability of higher resolution (temporal and spatial) weather products along with investigating climatic patterns and Intergovernmental Panel on Climate Change (IPCC) climate change scenarios. |
| doi_str_mv | 10.1111/jfr3.12131 |
| format | Article |
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Two different and complementary logistic models were studied: Logit and Probit. The models perform alike suggesting that the methodology is robust. The best model is most accurate during the autumn over 80% hit rate and in winter 66% hit rate, which are the seasons with high risk of floods. This work represents a first step in the development of a complete hydrological framework for the Biobío River Basin. The Logit distribution shows better results; thus, we suggest to use this distribution to relate flood events with mesoscale precipitation and ENSO index in the Biobío River Basin. Finally, these results explain the flood events and its relation with risk management. In forthcoming studies we will extend the methodology over this region and Chile taking advantage of the availability of higher resolution (temporal and spatial) weather products along with investigating climatic patterns and Intergovernmental Panel on Climate Change (IPCC) climate change scenarios.</description><identifier>ISSN: 1753-318X</identifier><identifier>EISSN: 1753-318X</identifier><identifier>DOI: 10.1111/jfr3.12131</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Publishing Ltd</publisher><subject>Climate change ; Climate change scenarios ; Distribution ; El Nino ; El Nino phenomena ; El Nino-Southern Oscillation event ; Environmental risk ; Estimation ; Flood control ; Flood management ; Flood predictions ; Flooding ; Floods ; Frameworks ; Freshwater ; Hydrologic models ; Hydrology ; Intergovernmental Panel on Climate Change ; Methods ; modelling ; Precipitation ; Rain ; Rainfall ; Regression analysis ; Regression models ; Risk management ; River basins ; Rivers ; Southern Oscillation ; Spatial distribution</subject><ispartof>Journal of flood risk management, 2017-03, Vol.10 (1), p.17-29</ispartof><rights>2014 The Chartered Institution of Water and Environmental Management (CIWEM) and John Wiley & Sons Ltd</rights><rights>Copyright © 2017 The Chartered Institution of Water and Environmental Management (CIWEM) and John Wiley & Sons Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3621-86d2d1e7d58ce91fb2cdae3120cf6f6d58f0db83cc99976828ddfce888f07b833</citedby><cites>FETCH-LOGICAL-c3621-86d2d1e7d58ce91fb2cdae3120cf6f6d58f0db83cc99976828ddfce888f07b833</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fjfr3.12131$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fjfr3.12131$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids></links><search><creatorcontrib>Fustos, I.</creatorcontrib><creatorcontrib>Abarca‐del‐Rio, R.</creatorcontrib><creatorcontrib>Ávila, A.</creatorcontrib><creatorcontrib>Orrego, R.</creatorcontrib><title>A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile</title><title>Journal of flood risk management</title><description>We predict flood events by fitting two simple logistic regression models between mesoscale rainfall and El Niño‐Southern Oscillation (ENSO) index with local scale flooding into the Biobío River Basin in Chile from 1948 to 2002. Two different and complementary logistic models were studied: Logit and Probit. The models perform alike suggesting that the methodology is robust. The best model is most accurate during the autumn over 80% hit rate and in winter 66% hit rate, which are the seasons with high risk of floods. This work represents a first step in the development of a complete hydrological framework for the Biobío River Basin. The Logit distribution shows better results; thus, we suggest to use this distribution to relate flood events with mesoscale precipitation and ENSO index in the Biobío River Basin. Finally, these results explain the flood events and its relation with risk management. In forthcoming studies we will extend the methodology over this region and Chile taking advantage of the availability of higher resolution (temporal and spatial) weather products along with investigating climatic patterns and Intergovernmental Panel on Climate Change (IPCC) climate change scenarios.</description><subject>Climate change</subject><subject>Climate change scenarios</subject><subject>Distribution</subject><subject>El Nino</subject><subject>El Nino phenomena</subject><subject>El Nino-Southern Oscillation event</subject><subject>Environmental risk</subject><subject>Estimation</subject><subject>Flood control</subject><subject>Flood management</subject><subject>Flood predictions</subject><subject>Flooding</subject><subject>Floods</subject><subject>Frameworks</subject><subject>Freshwater</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Intergovernmental Panel on Climate Change</subject><subject>Methods</subject><subject>modelling</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk management</subject><subject>River basins</subject><subject>Rivers</subject><subject>Southern Oscillation</subject><subject>Spatial distribution</subject><issn>1753-318X</issn><issn>1753-318X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp90c1KAzEQB_BFFKzVi08Q8CLC1mTT3WSPbbF-IAhFwVvYJhObkm5qslvpQ_kUvpip60E8NJcM__wShkySnBM8IHFdL7WnA5IRSg6SHmE5TSnhr4d_6uPkJIQlxgXjbNhL_AgFs1pbQNa9mdAYiVZOgUWNQ22twIemqhVqFoCclK33UMtYaqStcwrBBuomIFNHvjNj4-Zfnw7NzAY8GlfB1PEQyah8ZdFkYSycJke6sgHOfvd-8jK9eZ7cpY9Pt_eT0WMqaZGRlBcqUwSYyrmEkuh5JlUFlGRY6kIXMdZYzTmVsixLVvCMK6UlcB5zFnPaTy67d9fevbcQGrEyQYK1VQ2uDYJwlvEhoxhHevGPLl3r69idICWmLGP5kOxVvOB5SWMjUV11SnoXggct1t6sKr8VBIvdkMRuSOJnSBGTDn_Ej9nukeJhOqPdnW-HKZRP</recordid><startdate>201703</startdate><enddate>201703</enddate><creator>Fustos, I.</creator><creator>Abarca‐del‐Rio, R.</creator><creator>Ávila, A.</creator><creator>Orrego, R.</creator><general>Blackwell Publishing Ltd</general><general>John Wiley & Sons, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>H97</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>201703</creationdate><title>A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile</title><author>Fustos, I. ; Abarca‐del‐Rio, R. ; Ávila, A. ; Orrego, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3621-86d2d1e7d58ce91fb2cdae3120cf6f6d58f0db83cc99976828ddfce888f07b833</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Climate change</topic><topic>Climate change scenarios</topic><topic>Distribution</topic><topic>El Nino</topic><topic>El Nino phenomena</topic><topic>El Nino-Southern Oscillation event</topic><topic>Environmental risk</topic><topic>Estimation</topic><topic>Flood control</topic><topic>Flood management</topic><topic>Flood predictions</topic><topic>Flooding</topic><topic>Floods</topic><topic>Frameworks</topic><topic>Freshwater</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Intergovernmental Panel on Climate Change</topic><topic>Methods</topic><topic>modelling</topic><topic>Precipitation</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Risk management</topic><topic>River basins</topic><topic>Rivers</topic><topic>Southern Oscillation</topic><topic>Spatial distribution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fustos, I.</creatorcontrib><creatorcontrib>Abarca‐del‐Rio, R.</creatorcontrib><creatorcontrib>Ávila, A.</creatorcontrib><creatorcontrib>Orrego, R.</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of flood risk management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fustos, I.</au><au>Abarca‐del‐Rio, R.</au><au>Ávila, A.</au><au>Orrego, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile</atitle><jtitle>Journal of flood risk management</jtitle><date>2017-03</date><risdate>2017</risdate><volume>10</volume><issue>1</issue><spage>17</spage><epage>29</epage><pages>17-29</pages><issn>1753-318X</issn><eissn>1753-318X</eissn><abstract>We predict flood events by fitting two simple logistic regression models between mesoscale rainfall and El Niño‐Southern Oscillation (ENSO) index with local scale flooding into the Biobío River Basin in Chile from 1948 to 2002. Two different and complementary logistic models were studied: Logit and Probit. The models perform alike suggesting that the methodology is robust. The best model is most accurate during the autumn over 80% hit rate and in winter 66% hit rate, which are the seasons with high risk of floods. This work represents a first step in the development of a complete hydrological framework for the Biobío River Basin. The Logit distribution shows better results; thus, we suggest to use this distribution to relate flood events with mesoscale precipitation and ENSO index in the Biobío River Basin. Finally, these results explain the flood events and its relation with risk management. In forthcoming studies we will extend the methodology over this region and Chile taking advantage of the availability of higher resolution (temporal and spatial) weather products along with investigating climatic patterns and Intergovernmental Panel on Climate Change (IPCC) climate change scenarios.</abstract><cop>Oxford, UK</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/jfr3.12131</doi><tpages>13</tpages></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete; EZB-FREE-00999 freely available EZB journals |
| subjects | Climate change Climate change scenarios Distribution El Nino El Nino phenomena El Nino-Southern Oscillation event Environmental risk Estimation Flood control Flood management Flood predictions Flooding Floods Frameworks Freshwater Hydrologic models Hydrology Intergovernmental Panel on Climate Change Methods modelling Precipitation Rain Rainfall Regression analysis Regression models Risk management River basins Rivers Southern Oscillation Spatial distribution |
| title | A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile |
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