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Threats of climate change and land use patterns enhance the susceptibility of future floods in India
The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study p...
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Published in: | Journal of environmental management 2022-03, Vol.305, p.114317-114317, Article 114317 |
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creator | Pal, Subodh Chandra Chowdhuri, Indrajit Das, Biswajit Chakrabortty, Rabin Roy, Paramita Saha, Asish Shit, Manisa |
description | The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study presents high-resolution flood susceptibility maps of different future periods (up to 2100) using a combination of remote sensing data and GIS modelling. To quantify the future flood susceptibility various flood causative factors, Global circulation model (GCM) rainfall and land use and land cover (LULC) data are envisaged. The present flood susceptibility model has been evaluated through receiver operating characteristic (ROC) curve, where area under curve (AUC) value shows the 91.57% accuracy of this flood susceptibility model and it can be used for future flood susceptibility modelling. Based on the projected LULC, rainfall and flood susceptibility, the results of the study indicating maximum monthly rainfall will increase by approximately 40–50 mm in 2100, while the conversion of natural vegetation to agricultural and built-up land is about 0.071 million sq. km. and the severe flood event area will increase by up to 122% (0.15 million sq. km) from now on.
[Display omitted]
•Maximum monthly rainfall will increase 40–50 mm in future monsoon periods.•̴0.071 million km2 expansion of cropland and built-up-land will occur in future.•Machine learning logistic regression model applied for flood susceptibility modelling.•In India, rainfall and severe flood susceptible area will increases in future period. |
doi_str_mv | 10.1016/j.jenvman.2021.114317 |
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[Display omitted]
•Maximum monthly rainfall will increase 40–50 mm in future monsoon periods.•̴0.071 million km2 expansion of cropland and built-up-land will occur in future.•Machine learning logistic regression model applied for flood susceptibility modelling.•In India, rainfall and severe flood susceptible area will increases in future period.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2021.114317</identifier><identifier>PMID: 34954685</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Climate Change ; Flood ; Floods ; Forecasting ; GCM ; Humans ; India ; Land use ; ROC Curve</subject><ispartof>Journal of environmental management, 2022-03, Vol.305, p.114317-114317, Article 114317</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright © 2021 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-afa96e7f1dc24455aeefd46e75c991e1510aa96d201ce230a10c60aec3e9f6f13</citedby><cites>FETCH-LOGICAL-c365t-afa96e7f1dc24455aeefd46e75c991e1510aa96d201ce230a10c60aec3e9f6f13</cites><orcidid>0000-0003-0805-8007 ; 0000-0002-9032-2198</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34954685$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Pal, Subodh Chandra</creatorcontrib><creatorcontrib>Chowdhuri, Indrajit</creatorcontrib><creatorcontrib>Das, Biswajit</creatorcontrib><creatorcontrib>Chakrabortty, Rabin</creatorcontrib><creatorcontrib>Roy, Paramita</creatorcontrib><creatorcontrib>Saha, Asish</creatorcontrib><creatorcontrib>Shit, Manisa</creatorcontrib><title>Threats of climate change and land use patterns enhance the susceptibility of future floods in India</title><title>Journal of environmental management</title><addtitle>J Environ Manage</addtitle><description>The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study presents high-resolution flood susceptibility maps of different future periods (up to 2100) using a combination of remote sensing data and GIS modelling. To quantify the future flood susceptibility various flood causative factors, Global circulation model (GCM) rainfall and land use and land cover (LULC) data are envisaged. The present flood susceptibility model has been evaluated through receiver operating characteristic (ROC) curve, where area under curve (AUC) value shows the 91.57% accuracy of this flood susceptibility model and it can be used for future flood susceptibility modelling. Based on the projected LULC, rainfall and flood susceptibility, the results of the study indicating maximum monthly rainfall will increase by approximately 40–50 mm in 2100, while the conversion of natural vegetation to agricultural and built-up land is about 0.071 million sq. km. and the severe flood event area will increase by up to 122% (0.15 million sq. km) from now on.
[Display omitted]
•Maximum monthly rainfall will increase 40–50 mm in future monsoon periods.•̴0.071 million km2 expansion of cropland and built-up-land will occur in future.•Machine learning logistic regression model applied for flood susceptibility modelling.•In India, rainfall and severe flood susceptible area will increases in future period.</description><subject>Climate Change</subject><subject>Flood</subject><subject>Floods</subject><subject>Forecasting</subject><subject>GCM</subject><subject>Humans</subject><subject>India</subject><subject>Land use</subject><subject>ROC Curve</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqFkE1PwyAYx4nRuDn9CBqOXjp5SmnXkzHGlyVLvMwzYfDgWLp2Al2yby9Lp1cvkMDvefn_CLkFNgUG5cNmusF2v1XtNGc5TAEKDtUZGQOrRTYrOTsnY8YZZEVVVyNyFcKGMcZzqC7JiBe1KMqZGBOzXHtUMdDOUt24rYpI9Vq1X0hVa2hzPPqAdKdiRN8Gim361UjjGmnog8ZddCvXuHg4trB97D1S23SdCdS1dN4ap67JhVVNwJvTPSGfry_L5_ds8fE2f35aZJqXImbKqrrEyoLReVEIoRCtKdKL0HUNCAKYSoTJGWjMOVPAdMkUao61LS3wCbkf-u58991jiHLr0oZNSoFdH2ReQlEJwWGWUDGg2ncheLRy51N6f5DA5FGw3MiTYHkULAfBqe7uNKJfbdH8Vf0aTcDjAGAKunfoZdAOkzHjPOooTef-GfEDNS2QMg</recordid><startdate>20220301</startdate><enddate>20220301</enddate><creator>Pal, Subodh Chandra</creator><creator>Chowdhuri, Indrajit</creator><creator>Das, Biswajit</creator><creator>Chakrabortty, Rabin</creator><creator>Roy, Paramita</creator><creator>Saha, Asish</creator><creator>Shit, Manisa</creator><general>Elsevier Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0805-8007</orcidid><orcidid>https://orcid.org/0000-0002-9032-2198</orcidid></search><sort><creationdate>20220301</creationdate><title>Threats of climate change and land use patterns enhance the susceptibility of future floods in India</title><author>Pal, Subodh Chandra ; Chowdhuri, Indrajit ; Das, Biswajit ; Chakrabortty, Rabin ; Roy, Paramita ; Saha, Asish ; Shit, Manisa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-afa96e7f1dc24455aeefd46e75c991e1510aa96d201ce230a10c60aec3e9f6f13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Climate Change</topic><topic>Flood</topic><topic>Floods</topic><topic>Forecasting</topic><topic>GCM</topic><topic>Humans</topic><topic>India</topic><topic>Land use</topic><topic>ROC Curve</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pal, Subodh Chandra</creatorcontrib><creatorcontrib>Chowdhuri, Indrajit</creatorcontrib><creatorcontrib>Das, Biswajit</creatorcontrib><creatorcontrib>Chakrabortty, Rabin</creatorcontrib><creatorcontrib>Roy, Paramita</creatorcontrib><creatorcontrib>Saha, Asish</creatorcontrib><creatorcontrib>Shit, Manisa</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pal, Subodh Chandra</au><au>Chowdhuri, Indrajit</au><au>Das, Biswajit</au><au>Chakrabortty, Rabin</au><au>Roy, Paramita</au><au>Saha, Asish</au><au>Shit, Manisa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Threats of climate change and land use patterns enhance the susceptibility of future floods in India</atitle><jtitle>Journal of environmental management</jtitle><addtitle>J Environ Manage</addtitle><date>2022-03-01</date><risdate>2022</risdate><volume>305</volume><spage>114317</spage><epage>114317</epage><pages>114317-114317</pages><artnum>114317</artnum><issn>0301-4797</issn><eissn>1095-8630</eissn><abstract>The main objective of this work is the future prediction of the floods in India due to climate and land change. Human activity and related carbon emissions are the primary cause of land use and climate change, which has a substantial impact on extreme weather conditions, such as floods. This study presents high-resolution flood susceptibility maps of different future periods (up to 2100) using a combination of remote sensing data and GIS modelling. To quantify the future flood susceptibility various flood causative factors, Global circulation model (GCM) rainfall and land use and land cover (LULC) data are envisaged. The present flood susceptibility model has been evaluated through receiver operating characteristic (ROC) curve, where area under curve (AUC) value shows the 91.57% accuracy of this flood susceptibility model and it can be used for future flood susceptibility modelling. Based on the projected LULC, rainfall and flood susceptibility, the results of the study indicating maximum monthly rainfall will increase by approximately 40–50 mm in 2100, while the conversion of natural vegetation to agricultural and built-up land is about 0.071 million sq. km. and the severe flood event area will increase by up to 122% (0.15 million sq. km) from now on.
[Display omitted]
•Maximum monthly rainfall will increase 40–50 mm in future monsoon periods.•̴0.071 million km2 expansion of cropland and built-up-land will occur in future.•Machine learning logistic regression model applied for flood susceptibility modelling.•In India, rainfall and severe flood susceptible area will increases in future period.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>34954685</pmid><doi>10.1016/j.jenvman.2021.114317</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-0805-8007</orcidid><orcidid>https://orcid.org/0000-0002-9032-2198</orcidid></addata></record> |
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subjects | Climate Change Flood Floods Forecasting GCM Humans India Land use ROC Curve |
title | Threats of climate change and land use patterns enhance the susceptibility of future floods in India |
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