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Water resilience mapping of Chennai, India using analytical hierarchy process
Background The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively int...
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Published in: | Ecological processes 2021-12, Vol.10 (1), p.1-22, Article 71 |
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description | Background
The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP).
Methods
The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes.
Results
Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications.
Conclusion
This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures. |
doi_str_mv | 10.1186/s13717-021-00341-1 |
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The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP).
Methods
The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes.
Results
Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications.
Conclusion
This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures.</description><identifier>ISSN: 2192-1709</identifier><identifier>EISSN: 2192-1709</identifier><identifier>DOI: 10.1186/s13717-021-00341-1</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Adequacy ; AHP ; Analysis ; Analytic hierarchy process ; Climate change ; Climate change mitigation ; Decision analysis ; Decision making ; Drought ; Earth and Environmental Science ; Environment ; Geographic information systems ; Geographical information systems ; GIS ; Global climate ; Information systems ; Mitigation ; Multi-criteria decision analysis ; Multiple criterion ; Parameter sensitivity ; Remote sensing ; Resilience ; Resource management ; Sensitivity analysis ; Water resilience ; Water resources ; Water resources management ; Water supply systems</subject><ispartof>Ecological processes, 2021-12, Vol.10 (1), p.1-22, Article 71</ispartof><rights>The Author(s) 2021</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c502t-c135a7050f6ff70f4434714e3f481bcae3614c49ce169a79b6cea186b2f0b4d43</citedby><cites>FETCH-LOGICAL-c502t-c135a7050f6ff70f4434714e3f481bcae3614c49ce169a79b6cea186b2f0b4d43</cites><orcidid>0000-0002-8574-6914</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2607471686/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2607471686?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Kaaviya, R.</creatorcontrib><creatorcontrib>Devadas, V.</creatorcontrib><title>Water resilience mapping of Chennai, India using analytical hierarchy process</title><title>Ecological processes</title><addtitle>Ecol Process</addtitle><description>Background
The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP).
Methods
The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes.
Results
Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications.
Conclusion
This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures.</description><subject>Adequacy</subject><subject>AHP</subject><subject>Analysis</subject><subject>Analytic hierarchy process</subject><subject>Climate change</subject><subject>Climate change mitigation</subject><subject>Decision analysis</subject><subject>Decision making</subject><subject>Drought</subject><subject>Earth and Environmental Science</subject><subject>Environment</subject><subject>Geographic information systems</subject><subject>Geographical information systems</subject><subject>GIS</subject><subject>Global climate</subject><subject>Information systems</subject><subject>Mitigation</subject><subject>Multi-criteria decision analysis</subject><subject>Multiple criterion</subject><subject>Parameter sensitivity</subject><subject>Remote sensing</subject><subject>Resilience</subject><subject>Resource management</subject><subject>Sensitivity analysis</subject><subject>Water resilience</subject><subject>Water resources</subject><subject>Water resources management</subject><subject>Water supply systems</subject><issn>2192-1709</issn><issn>2192-1709</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNp9kT9PwzAQxSMEEhX0CzBFYiXgc1w7GVHFn0pFLCBG6-KcW1dpEux06LfHbRAw4cX26d3v7uklyRWwW4BC3gXIFaiMccgYywVkcJJMOJQ8A8XK0z_v82QawobFUwoQpZokLx84kE89Bdc4ag2lW-x7167SzqbzNbUtupt00dYO01041LHFZj84g026duTRm_U-7X1nKITL5MxiE2j6fV8k748Pb_PnbPn6tJjfLzMzY3zIDOQzVGzGrLRWMStELhQIyq0ooDJIuQRhRGkIZImqrKQhjE4rblklapFfJIuRW3e40b13W_R73aHTx0LnVxp93LEhrXhR1wwt46IQtiwwfmslmZRCESiIrOuRFT187igMetPtfDQZNJdMxcVkIaOKjyrjuxA82Z-pwPQhBT2moGMK-piCPqDzsSlEcbsi_4v-p-sLfsmItA</recordid><startdate>20211208</startdate><enddate>20211208</enddate><creator>Kaaviya, R.</creator><creator>Devadas, V.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><general>SpringerOpen</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H95</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>LK8</scope><scope>M7P</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-8574-6914</orcidid></search><sort><creationdate>20211208</creationdate><title>Water resilience mapping of Chennai, India using analytical hierarchy process</title><author>Kaaviya, R. ; Devadas, V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c502t-c135a7050f6ff70f4434714e3f481bcae3614c49ce169a79b6cea186b2f0b4d43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adequacy</topic><topic>AHP</topic><topic>Analysis</topic><topic>Analytic hierarchy process</topic><topic>Climate change</topic><topic>Climate change mitigation</topic><topic>Decision analysis</topic><topic>Decision making</topic><topic>Drought</topic><topic>Earth and Environmental Science</topic><topic>Environment</topic><topic>Geographic information systems</topic><topic>Geographical information systems</topic><topic>GIS</topic><topic>Global climate</topic><topic>Information systems</topic><topic>Mitigation</topic><topic>Multi-criteria decision analysis</topic><topic>Multiple criterion</topic><topic>Parameter sensitivity</topic><topic>Remote sensing</topic><topic>Resilience</topic><topic>Resource management</topic><topic>Sensitivity analysis</topic><topic>Water resilience</topic><topic>Water resources</topic><topic>Water resources management</topic><topic>Water supply systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kaaviya, R.</creatorcontrib><creatorcontrib>Devadas, V.</creatorcontrib><collection>SpringerOpen</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Ecological processes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kaaviya, R.</au><au>Devadas, V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Water resilience mapping of Chennai, India using analytical hierarchy process</atitle><jtitle>Ecological processes</jtitle><stitle>Ecol Process</stitle><date>2021-12-08</date><risdate>2021</risdate><volume>10</volume><issue>1</issue><spage>1</spage><epage>22</epage><pages>1-22</pages><artnum>71</artnum><issn>2192-1709</issn><eissn>2192-1709</eissn><abstract>Background
The urban water system is the worst hit in global climate change. Water resilience is the system’s ability to retaliate and recover from various water-related disruptions. The present study aims to delineate the water resilience zones in Chennai city, Tamil Nadu, India, by effectively integrating the geographic information system, remote sensing, and analytical hierarchy process (AHP).
Methods
The methodology incorporated 15 vital factors. A multi-criteria decision analysis technique was adopted to assign a weight to each parameter using the AHP. A pairwise decision matrix was constructed, parameter’s relative importance and the consistency ratio were established. Integration of all maps by weighted overlay analysis technique depicted water resilience intensities of five different classes.
Results
Very low, low and moderate water resilience areas accounted for more than three-fourth of the study area. Area Under Curve score (80.12%) depicted the accuracy of the developed model. Sensitivity analysis determined the significance of the parameters in the delineation. The logical structural approach can be employed in other parts of India or elsewhere with modifications.
Conclusion
This study is novel in its approach by holistically analyzing water resilience by integrating disruptions related to flood, drought and the city's water infrastructure system's adequacy and efficiency. Researchers and planners can effectively use the study results to ensure resilience as a new perspective on effective water resource management and climate change mitigation. It becomes a decision aid mechanism identifying where the system is vulnerable to potential water-related risks for employing resilience measures.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1186/s13717-021-00341-1</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0002-8574-6914</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adequacy AHP Analysis Analytic hierarchy process Climate change Climate change mitigation Decision analysis Decision making Drought Earth and Environmental Science Environment Geographic information systems Geographical information systems GIS Global climate Information systems Mitigation Multi-criteria decision analysis Multiple criterion Parameter sensitivity Remote sensing Resilience Resource management Sensitivity analysis Water resilience Water resources Water resources management Water supply systems |
title | Water resilience mapping of Chennai, India using analytical hierarchy process |
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