Spatio‐temporal analysis of copula‐based probabilistic multivariate drought index using CMIP6 model
Studies on multivariate drought assessment and the climate change impact on a river basin scale are limited in India. Drought monitoring is a challenging subject due to its dependence on different climatic variables. To overcome this, a copula‐based probabilistic multivariate drought index (MDI) has...
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Veröffentlicht in: | International journal of climatology 2022-06, Vol.42 (8), p.4333-4350 |
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description | Studies on multivariate drought assessment and the climate change impact on a river basin scale are limited in India. Drought monitoring is a challenging subject due to its dependence on different climatic variables. To overcome this, a copula‐based probabilistic multivariate drought index (MDI) has been developed which simultaneously represents the meteorological, hydrological and agricultural drought phenomenon. The four variate Archimedean copula is used in this study to integrate the precipitation, evapotranspiration, soil moisture and streamflow. Hydrologic variables like evapotranspiration, soil moisture and streamflow were simulated using the Soil and Water Assessment Tool model. The future MDI is also analysed to identify the impact of climate change on drought phenomenon using Coupled Model Intercomparison Project‐6 Global Climate Models under four Socio‐Economic Shared Pathways. Drought characteristics like severity and duration were evaluated to identify the present and future drought events. The precipitation and minimum and maximum temperatures were identified to have increasing tendencies in the future scenarios. Most of the future scenarios showed lower drought duration and severity when compared to the reference period. The drought duration and severity are likely to decrease in the future time scales especially under the high emission scenarios. The present study used a novel approach to examine the drought from various perspectives and the study will be useful for drought mitigation and adaptation strategies over the basin.
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doi_str_mv | 10.1002/joc.7469 |
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Location map of the study area.</description><subject>Agricultural drought</subject><subject>Climate change</subject><subject>Climate models</subject><subject>CMIP6</subject><subject>copula</subject><subject>Drought</subject><subject>Drought characteristics</subject><subject>Drought index</subject><subject>Drought monitoring</subject><subject>Duration</subject><subject>Economic models</subject><subject>Economics</subject><subject>Emission analysis</subject><subject>Environmental impact</subject><subject>Environmental monitoring</subject><subject>Evapotranspiration</subject><subject>Global climate</subject><subject>Global climate models</subject><subject>Hydrologic drought</subject><subject>Hydrology</subject><subject>Intercomparison</subject><subject>Maximum temperatures</subject><subject>MDI</subject><subject>Mitigation</subject><subject>Modelling</subject><subject>Moisture effects</subject><subject>Multivariate analysis</subject><subject>Precipitation</subject><subject>River basins</subject><subject>Soil</subject><subject>Soil moisture</subject><subject>Soil water</subject><subject>SSPs</subject><subject>Stream discharge</subject><subject>Stream flow</subject><subject>SWAT</subject><issn>0899-8418</issn><issn>1097-0088</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp10M1OwzAMAOAIgcQYSDxCJC5cOpy0a5MjqvgZGhoScK7cJB2Z2qUkLbAbj8Az8iR0jCvywQd_tmwTcspgwgD4xcqpSZakco-MGMgsAhBin4xASBmJhIlDchTCCgCkZOmILB9b7Kz7_vzqTNM6jzXFNdabYAN1FVWu7WscqiUGo2nrXYmlrW3orKJNX3f2Db3FzlDtXb986ahda_NB-2DXS5rfzx5S2jht6mNyUGEdzMlfHpPn66un_DaaL25m-eU8UlzGMoqNlFCZOC2BM82rUkyFzoQCSBKsEKaYIE9UGSNWsUh0ahgHZbQwYISOIR6Ts93cYdXX3oSuWLneDxeFgqfZVKZD8EGd75TyLgRvqqL1tkG_KRgU2zcOXarYvnGg0Y6-29ps_nXF3SL_9T8WVnc4</recordid><startdate>20220630</startdate><enddate>20220630</enddate><creator>Dixit, Soumyashree</creator><creator>Jayakumar, K. V.</creator><general>John Wiley & Sons, Ltd</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0002-4929-0155</orcidid></search><sort><creationdate>20220630</creationdate><title>Spatio‐temporal analysis of copula‐based probabilistic multivariate drought index using CMIP6 model</title><author>Dixit, Soumyashree ; Jayakumar, K. V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2939-3e990fe36b021d2fb858d78c0044afa05a4a24cb3aaf384d6e120ced8e0e8d303</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Agricultural drought</topic><topic>Climate change</topic><topic>Climate models</topic><topic>CMIP6</topic><topic>copula</topic><topic>Drought</topic><topic>Drought characteristics</topic><topic>Drought index</topic><topic>Drought monitoring</topic><topic>Duration</topic><topic>Economic models</topic><topic>Economics</topic><topic>Emission analysis</topic><topic>Environmental impact</topic><topic>Environmental monitoring</topic><topic>Evapotranspiration</topic><topic>Global climate</topic><topic>Global climate models</topic><topic>Hydrologic drought</topic><topic>Hydrology</topic><topic>Intercomparison</topic><topic>Maximum temperatures</topic><topic>MDI</topic><topic>Mitigation</topic><topic>Modelling</topic><topic>Moisture effects</topic><topic>Multivariate analysis</topic><topic>Precipitation</topic><topic>River basins</topic><topic>Soil</topic><topic>Soil moisture</topic><topic>Soil water</topic><topic>SSPs</topic><topic>Stream discharge</topic><topic>Stream flow</topic><topic>SWAT</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dixit, Soumyashree</creatorcontrib><creatorcontrib>Jayakumar, K. V.</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>International journal of climatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dixit, Soumyashree</au><au>Jayakumar, K. V.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatio‐temporal analysis of copula‐based probabilistic multivariate drought index using CMIP6 model</atitle><jtitle>International journal of climatology</jtitle><date>2022-06-30</date><risdate>2022</risdate><volume>42</volume><issue>8</issue><spage>4333</spage><epage>4350</epage><pages>4333-4350</pages><issn>0899-8418</issn><eissn>1097-0088</eissn><abstract>Studies on multivariate drought assessment and the climate change impact on a river basin scale are limited in India. Drought monitoring is a challenging subject due to its dependence on different climatic variables. To overcome this, a copula‐based probabilistic multivariate drought index (MDI) has been developed which simultaneously represents the meteorological, hydrological and agricultural drought phenomenon. The four variate Archimedean copula is used in this study to integrate the precipitation, evapotranspiration, soil moisture and streamflow. Hydrologic variables like evapotranspiration, soil moisture and streamflow were simulated using the Soil and Water Assessment Tool model. The future MDI is also analysed to identify the impact of climate change on drought phenomenon using Coupled Model Intercomparison Project‐6 Global Climate Models under four Socio‐Economic Shared Pathways. Drought characteristics like severity and duration were evaluated to identify the present and future drought events. The precipitation and minimum and maximum temperatures were identified to have increasing tendencies in the future scenarios. Most of the future scenarios showed lower drought duration and severity when compared to the reference period. The drought duration and severity are likely to decrease in the future time scales especially under the high emission scenarios. The present study used a novel approach to examine the drought from various perspectives and the study will be useful for drought mitigation and adaptation strategies over the basin.
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subjects | Agricultural drought Climate change Climate models CMIP6 copula Drought Drought characteristics Drought index Drought monitoring Duration Economic models Economics Emission analysis Environmental impact Environmental monitoring Evapotranspiration Global climate Global climate models Hydrologic drought Hydrology Intercomparison Maximum temperatures MDI Mitigation Modelling Moisture effects Multivariate analysis Precipitation River basins Soil Soil moisture Soil water SSPs Stream discharge Stream flow SWAT |
title | Spatio‐temporal analysis of copula‐based probabilistic multivariate drought index using CMIP6 model |
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