Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios
Evaluating the impact of climate change at river basin level has become essential for proper management of the water resources. In the present study, Godavari River basin in India is taken as study area to project the monthly monsoon precipitation using statistical downscaling. The downscaling metho...
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| Veröffentlicht in: | Water resources management 2016-12, Vol.30 (15), p.5575-5587 |
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| description | Evaluating the impact of climate change at river basin level has become essential for proper management of the water resources. In the present study, Godavari River basin in India is taken as study area to project the monthly monsoon precipitation using statistical downscaling. The downscaling method used is a regression based downscaling termed as fuzzy clustering with multiple regression. Among the atmospheric variables simulated by global circulation/climate model (GCM) mean sea level pressure, specific humidity and 500 hPa geopotential height are used as predictors. 1
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gridded rainfall data over Godavari river basin are collected from India Meteorological Department (IMD). A statistical relationship is established between the predictors and predictand (monsoon rainfall) to project the monsoon rainfall for the future using the Canadian Earth System Model (CanESM2) over IMD grid points under the Representative Concentration Pathways 2.6, 4.5 and 8.5 (RCP 2.6, 4.5, 8.5) scenarios of Fifth Coupled Model Inter-Comparison Project (CMIP 5). Downscaling procedure is applied to all 25 IMD grid points over the basin to find out the spatial distribution of monsoon rainfall for the future scenarios. For 2.6 and 4.5 scenarios results show an increasing trend. For scenario 8.5 rainfall showed a mixed trend with rainfall decreasing in the first thirty years of prediction and then increasing gradually over the next sixty years. |
| doi_str_mv | 10.1007/s11269-016-1549-6 |
| format | Article |
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gridded rainfall data over Godavari river basin are collected from India Meteorological Department (IMD). A statistical relationship is established between the predictors and predictand (monsoon rainfall) to project the monsoon rainfall for the future using the Canadian Earth System Model (CanESM2) over IMD grid points under the Representative Concentration Pathways 2.6, 4.5 and 8.5 (RCP 2.6, 4.5, 8.5) scenarios of Fifth Coupled Model Inter-Comparison Project (CMIP 5). Downscaling procedure is applied to all 25 IMD grid points over the basin to find out the spatial distribution of monsoon rainfall for the future scenarios. For 2.6 and 4.5 scenarios results show an increasing trend. For scenario 8.5 rainfall showed a mixed trend with rainfall decreasing in the first thirty years of prediction and then increasing gradually over the next sixty years.</description><identifier>ISSN: 0920-4741</identifier><identifier>EISSN: 1573-1650</identifier><identifier>DOI: 10.1007/s11269-016-1549-6</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Atmospheric Sciences ; Basins ; Civil Engineering ; Climate change ; Climate models ; Earth and Environmental Science ; Earth Sciences ; Environment ; Environmental impact ; Freshwater ; Geopotential height ; Geotechnical Engineering & Applied Earth Sciences ; Humidity ; Hydrogeology ; Hydrologic data ; Hydrology ; Hydrology/Water Resources ; Marine ; Mathematical models ; Monsoons ; Precipitation ; Principal components analysis ; Rainfall ; Regression ; River basins ; Rivers ; Sea level ; Spatial distribution ; Specific humidity ; Trends ; Variables ; Water resources ; Wind</subject><ispartof>Water resources management, 2016-12, Vol.30 (15), p.5575-5587</ispartof><rights>Springer Science+Business Media Dordrecht 2016</rights><rights>Water Resources Management is a copyright of Springer, 2016.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c382t-e6688c58ed71891d0a1fab0716d49fe9ad693083fbae35f29817e04dad4b5d083</citedby><cites>FETCH-LOGICAL-c382t-e6688c58ed71891d0a1fab0716d49fe9ad693083fbae35f29817e04dad4b5d083</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11269-016-1549-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11269-016-1549-6$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Das, Jew</creatorcontrib><creatorcontrib>Umamahesh, Nanduri V.</creatorcontrib><title>Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios</title><title>Water resources management</title><addtitle>Water Resour Manage</addtitle><description>Evaluating the impact of climate change at river basin level has become essential for proper management of the water resources. In the present study, Godavari River basin in India is taken as study area to project the monthly monsoon precipitation using statistical downscaling. The downscaling method used is a regression based downscaling termed as fuzzy clustering with multiple regression. Among the atmospheric variables simulated by global circulation/climate model (GCM) mean sea level pressure, specific humidity and 500 hPa geopotential height are used as predictors. 1
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gridded rainfall data over Godavari river basin are collected from India Meteorological Department (IMD). A statistical relationship is established between the predictors and predictand (monsoon rainfall) to project the monsoon rainfall for the future using the Canadian Earth System Model (CanESM2) over IMD grid points under the Representative Concentration Pathways 2.6, 4.5 and 8.5 (RCP 2.6, 4.5, 8.5) scenarios of Fifth Coupled Model Inter-Comparison Project (CMIP 5). Downscaling procedure is applied to all 25 IMD grid points over the basin to find out the spatial distribution of monsoon rainfall for the future scenarios. For 2.6 and 4.5 scenarios results show an increasing trend. For scenario 8.5 rainfall showed a mixed trend with rainfall decreasing in the first thirty years of prediction and then increasing gradually over the next sixty years.</description><subject>Atmospheric Sciences</subject><subject>Basins</subject><subject>Civil Engineering</subject><subject>Climate change</subject><subject>Climate models</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Environment</subject><subject>Environmental impact</subject><subject>Freshwater</subject><subject>Geopotential height</subject><subject>Geotechnical Engineering & Applied Earth Sciences</subject><subject>Humidity</subject><subject>Hydrogeology</subject><subject>Hydrologic data</subject><subject>Hydrology</subject><subject>Hydrology/Water Resources</subject><subject>Marine</subject><subject>Mathematical models</subject><subject>Monsoons</subject><subject>Precipitation</subject><subject>Principal components analysis</subject><subject>Rainfall</subject><subject>Regression</subject><subject>River basins</subject><subject>Rivers</subject><subject>Sea level</subject><subject>Spatial distribution</subject><subject>Specific humidity</subject><subject>Trends</subject><subject>Variables</subject><subject>Water resources</subject><subject>Wind</subject><issn>0920-4741</issn><issn>1573-1650</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNqNkUFLAzEQhYMoWKs_wNuCFy_Rmc1uNjlq1SpUhKrnkG6ydcs2qUm34r83pR5EELzMwMz3Hsw8Qk4RLhCguoyIOZcUkFMsC0n5HhlgWTGKvIR9MgCZAy2qAg_JUYwLgKSSMCDqxn-4WOuudfPs0bvovcumunWN7rrMb2zIpu22jr3RGx3a7FrH1mW9M2l40zaNDdats1HXLvXa0tGbdnObPdfWJdjHY3KQnKI9-e5D8np3-zK6p5On8cPoakJrJvI1tZwLUZfCmgqFRAMaGz2DCrkpZGOlNlwyEKyZacvKJpcCKwuF0aaYlSYthuR857sK_r23ca2Wbaxt12lnfR8VCgGQC8zxHygXjDEhZELPfqEL3weXDtlSZV5IrFiicEfVwccYbKNWIX0jfCoEtU1H7dJRKR21TUfxpMl3mpjY9LHww_lP0RcR0pFm</recordid><startdate>20161201</startdate><enddate>20161201</enddate><creator>Das, Jew</creator><creator>Umamahesh, Nanduri V.</creator><general>Springer Netherlands</general><general>Springer Nature 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Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios</title><author>Das, Jew ; Umamahesh, Nanduri V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-e6688c58ed71891d0a1fab0716d49fe9ad693083fbae35f29817e04dad4b5d083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Atmospheric Sciences</topic><topic>Basins</topic><topic>Civil Engineering</topic><topic>Climate change</topic><topic>Climate models</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Environment</topic><topic>Environmental impact</topic><topic>Freshwater</topic><topic>Geopotential height</topic><topic>Geotechnical Engineering & Applied Earth Sciences</topic><topic>Humidity</topic><topic>Hydrogeology</topic><topic>Hydrologic data</topic><topic>Hydrology</topic><topic>Hydrology/Water Resources</topic><topic>Marine</topic><topic>Mathematical 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has become essential for proper management of the water resources. In the present study, Godavari River basin in India is taken as study area to project the monthly monsoon precipitation using statistical downscaling. The downscaling method used is a regression based downscaling termed as fuzzy clustering with multiple regression. Among the atmospheric variables simulated by global circulation/climate model (GCM) mean sea level pressure, specific humidity and 500 hPa geopotential height are used as predictors. 1
o
× 1
o
gridded rainfall data over Godavari river basin are collected from India Meteorological Department (IMD). A statistical relationship is established between the predictors and predictand (monsoon rainfall) to project the monsoon rainfall for the future using the Canadian Earth System Model (CanESM2) over IMD grid points under the Representative Concentration Pathways 2.6, 4.5 and 8.5 (RCP 2.6, 4.5, 8.5) scenarios of Fifth Coupled Model Inter-Comparison Project (CMIP 5). Downscaling procedure is applied to all 25 IMD grid points over the basin to find out the spatial distribution of monsoon rainfall for the future scenarios. For 2.6 and 4.5 scenarios results show an increasing trend. For scenario 8.5 rainfall showed a mixed trend with rainfall decreasing in the first thirty years of prediction and then increasing gradually over the next sixty years.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s11269-016-1549-6</doi><tpages>13</tpages></addata></record> |
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| subjects | Atmospheric Sciences Basins Civil Engineering Climate change Climate models Earth and Environmental Science Earth Sciences Environment Environmental impact Freshwater Geopotential height Geotechnical Engineering & Applied Earth Sciences Humidity Hydrogeology Hydrologic data Hydrology Hydrology/Water Resources Marine Mathematical models Monsoons Precipitation Principal components analysis Rainfall Regression River basins Rivers Sea level Spatial distribution Specific humidity Trends Variables Water resources Wind |
| title | Downscaling Monsoon Rainfall over River Godavari Basin under Different Climate-Change Scenarios |
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