The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia
This study aims to compare the relationship between climate variables and rice productivity under different irrigation systems (irrigated and rainfed) in the clustering area on Java Island, Indonesia. This study used the clustering areas resulting from the previous study. The climate variables used...
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creator | Aprilina, K Sopaheluwakan, A Susandi, A Hadi, T W Trilaksono, N J Lubis, A Dayantolis, W Permana, D S Nuryanto, D E Anggraeni, R Komalasari, K E Fajariana, Y Yuliyanti, M S Haryoko, U Hidayanto, N Linarka, U A |
description | This study aims to compare the relationship between climate variables and rice productivity under different irrigation systems (irrigated and rainfed) in the clustering area on Java Island, Indonesia. This study used the clustering areas resulting from the previous study. The climate variables used are bias-corrected MERRA2 data from the period 1987–2017, cropped for Java Island. The rice productivity and reference evapotranspiration data used in this study are the results of the simulation of Aquacrop modeling. The result from the cluster method used tends to divide Java Island into 2 clusters with different altitudes (lowland and highland) areas. The results show that the correlation values between the precipitation variable and rice productivity from Aquacrop simulation (both irrigated or rainfed) in cluster 1 (dominated lowlands) are higher than in cluster 2 (dominated highlands), contrary to that the correlation values between the reference evapotranspiration variable with rice productivity from Aquacrop simulation (both irrigated or rainfed) are higher in cluster 2 (dominated highlands) areas, compared to cluster 1 areas (dominated lowlands). R-square values from response surface methodology (RSM) on the rainfed system in both clusters are higher than those on the irrigated system. This indicates that rainfed agriculture is highly dependent on climate variables, especially precipitation and reference evapotranspiration variables compared with the regular irrigated agricultural system. The RSM result also shows that climate variables significantly contribute to the variation of rice productivity generated by Aquacrop modeling in irrigated and rainfed systems and in all clusters. |
doi_str_mv | 10.1088/1755-1315/1167/1/012016 |
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This study used the clustering areas resulting from the previous study. The climate variables used are bias-corrected MERRA2 data from the period 1987–2017, cropped for Java Island. The rice productivity and reference evapotranspiration data used in this study are the results of the simulation of Aquacrop modeling. The result from the cluster method used tends to divide Java Island into 2 clusters with different altitudes (lowland and highland) areas. The results show that the correlation values between the precipitation variable and rice productivity from Aquacrop simulation (both irrigated or rainfed) in cluster 1 (dominated lowlands) are higher than in cluster 2 (dominated highlands), contrary to that the correlation values between the reference evapotranspiration variable with rice productivity from Aquacrop simulation (both irrigated or rainfed) are higher in cluster 2 (dominated highlands) areas, compared to cluster 1 areas (dominated lowlands). R-square values from response surface methodology (RSM) on the rainfed system in both clusters are higher than those on the irrigated system. This indicates that rainfed agriculture is highly dependent on climate variables, especially precipitation and reference evapotranspiration variables compared with the regular irrigated agricultural system. The RSM result also shows that climate variables significantly contribute to the variation of rice productivity generated by Aquacrop modeling in irrigated and rainfed systems and in all clusters.</description><identifier>ISSN: 1755-1307</identifier><identifier>EISSN: 1755-1315</identifier><identifier>DOI: 10.1088/1755-1315/1167/1/012016</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Aquacrop crop modeling ; Clustering ; Evapotranspiration ; Farming systems ; Highlands ; Irrigation systems ; Lowlands ; Modelling ; Precipitation ; Productivity ; Rainfall ; Rainfed farming ; Response surface methodology ; Rice ; Rice productivity ; Simulation ; Variables</subject><ispartof>IOP conference series. Earth and environmental science, 2023-05, Vol.1167 (1), p.12016</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (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><cites>FETCH-LOGICAL-c2736-5ca32367d2aa3d2dd9072411f661ea17618dea7a614b16d130f210927eb874093</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1755-1315/1167/1/012016/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27901,27902,38845,38867,53815,53842</link.rule.ids></links><search><creatorcontrib>Aprilina, K</creatorcontrib><creatorcontrib>Sopaheluwakan, A</creatorcontrib><creatorcontrib>Susandi, A</creatorcontrib><creatorcontrib>Hadi, T W</creatorcontrib><creatorcontrib>Trilaksono, N J</creatorcontrib><creatorcontrib>Lubis, A</creatorcontrib><creatorcontrib>Dayantolis, W</creatorcontrib><creatorcontrib>Permana, D S</creatorcontrib><creatorcontrib>Nuryanto, D E</creatorcontrib><creatorcontrib>Anggraeni, R</creatorcontrib><creatorcontrib>Komalasari, K E</creatorcontrib><creatorcontrib>Fajariana, Y</creatorcontrib><creatorcontrib>Yuliyanti, M S</creatorcontrib><creatorcontrib>Haryoko, U</creatorcontrib><creatorcontrib>Hidayanto, N</creatorcontrib><creatorcontrib>Linarka, U A</creatorcontrib><title>The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia</title><title>IOP conference series. Earth and environmental science</title><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><description>This study aims to compare the relationship between climate variables and rice productivity under different irrigation systems (irrigated and rainfed) in the clustering area on Java Island, Indonesia. This study used the clustering areas resulting from the previous study. The climate variables used are bias-corrected MERRA2 data from the period 1987–2017, cropped for Java Island. The rice productivity and reference evapotranspiration data used in this study are the results of the simulation of Aquacrop modeling. The result from the cluster method used tends to divide Java Island into 2 clusters with different altitudes (lowland and highland) areas. The results show that the correlation values between the precipitation variable and rice productivity from Aquacrop simulation (both irrigated or rainfed) in cluster 1 (dominated lowlands) are higher than in cluster 2 (dominated highlands), contrary to that the correlation values between the reference evapotranspiration variable with rice productivity from Aquacrop simulation (both irrigated or rainfed) are higher in cluster 2 (dominated highlands) areas, compared to cluster 1 areas (dominated lowlands). R-square values from response surface methodology (RSM) on the rainfed system in both clusters are higher than those on the irrigated system. This indicates that rainfed agriculture is highly dependent on climate variables, especially precipitation and reference evapotranspiration variables compared with the regular irrigated agricultural system. The RSM result also shows that climate variables significantly contribute to the variation of rice productivity generated by Aquacrop modeling in irrigated and rainfed systems and in all clusters.</description><subject>Aquacrop crop modeling</subject><subject>Clustering</subject><subject>Evapotranspiration</subject><subject>Farming systems</subject><subject>Highlands</subject><subject>Irrigation systems</subject><subject>Lowlands</subject><subject>Modelling</subject><subject>Precipitation</subject><subject>Productivity</subject><subject>Rainfall</subject><subject>Rainfed farming</subject><subject>Response surface methodology</subject><subject>Rice</subject><subject>Rice productivity</subject><subject>Simulation</subject><subject>Variables</subject><issn>1755-1307</issn><issn>1755-1315</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkE1LxDAQhoso-PkbDHgSXDeTtkn3KLLqiuDB9Rxmm6kbqUlNuiue_OumrCiC4CmBPO87mSfLjoGfA6-qMaiyHEEO5RhAqjGMOQgOcivb-37Z_r5ztZvtx_jMuVRFPtnLPuZLYrV_6TDY6B3zDQvUYm-9i0vbsQX1b0SO1a19wZ7YOnG4aCkydIYFWxPrgjerurdr278z61g_NLar2FOw7olhIGSp-RbXyGaxTbkzNnPGO4oWD7OdBttIR1_nQfZ4NZ1f3ozu7q9nlxd3o1qoXI7KGnORS2UEYm6EMROuRAHQSAmEoCRUhlChhGIB0qRFGwF8IhQtKlXwSX6QnWx6029fVxR7_exXwaWRWlRQFgqqEhKlNlQdfIyBGt2FtHd418D1YFsPHvXgVA-2NeiN7ZQ83SSt736qp9OH35zuTJPY_A_2vwmfc9OPIA</recordid><startdate>20230501</startdate><enddate>20230501</enddate><creator>Aprilina, K</creator><creator>Sopaheluwakan, A</creator><creator>Susandi, A</creator><creator>Hadi, T W</creator><creator>Trilaksono, N J</creator><creator>Lubis, A</creator><creator>Dayantolis, W</creator><creator>Permana, D S</creator><creator>Nuryanto, D E</creator><creator>Anggraeni, R</creator><creator>Komalasari, K E</creator><creator>Fajariana, Y</creator><creator>Yuliyanti, M S</creator><creator>Haryoko, U</creator><creator>Hidayanto, N</creator><creator>Linarka, U A</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope></search><sort><creationdate>20230501</creationdate><title>The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia</title><author>Aprilina, K ; Sopaheluwakan, A ; Susandi, A ; Hadi, T W ; Trilaksono, N J ; Lubis, A ; Dayantolis, W ; Permana, D S ; Nuryanto, D E ; Anggraeni, R ; Komalasari, K E ; Fajariana, Y ; Yuliyanti, M S ; Haryoko, U ; Hidayanto, N ; Linarka, U A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2736-5ca32367d2aa3d2dd9072411f661ea17618dea7a614b16d130f210927eb874093</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Aquacrop crop modeling</topic><topic>Clustering</topic><topic>Evapotranspiration</topic><topic>Farming systems</topic><topic>Highlands</topic><topic>Irrigation systems</topic><topic>Lowlands</topic><topic>Modelling</topic><topic>Precipitation</topic><topic>Productivity</topic><topic>Rainfall</topic><topic>Rainfed farming</topic><topic>Response surface methodology</topic><topic>Rice</topic><topic>Rice productivity</topic><topic>Simulation</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aprilina, K</creatorcontrib><creatorcontrib>Sopaheluwakan, A</creatorcontrib><creatorcontrib>Susandi, A</creatorcontrib><creatorcontrib>Hadi, T W</creatorcontrib><creatorcontrib>Trilaksono, N J</creatorcontrib><creatorcontrib>Lubis, A</creatorcontrib><creatorcontrib>Dayantolis, W</creatorcontrib><creatorcontrib>Permana, D S</creatorcontrib><creatorcontrib>Nuryanto, D E</creatorcontrib><creatorcontrib>Anggraeni, R</creatorcontrib><creatorcontrib>Komalasari, K E</creatorcontrib><creatorcontrib>Fajariana, Y</creatorcontrib><creatorcontrib>Yuliyanti, M S</creatorcontrib><creatorcontrib>Haryoko, U</creatorcontrib><creatorcontrib>Hidayanto, N</creatorcontrib><creatorcontrib>Linarka, U A</creatorcontrib><collection>IOP Publishing Free Content</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</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>ProQuest Central China</collection><collection>Environmental Science Collection</collection><jtitle>IOP conference series. Earth and environmental science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aprilina, K</au><au>Sopaheluwakan, A</au><au>Susandi, A</au><au>Hadi, T W</au><au>Trilaksono, N J</au><au>Lubis, A</au><au>Dayantolis, W</au><au>Permana, D S</au><au>Nuryanto, D E</au><au>Anggraeni, R</au><au>Komalasari, K E</au><au>Fajariana, Y</au><au>Yuliyanti, M S</au><au>Haryoko, U</au><au>Hidayanto, N</au><au>Linarka, U A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia</atitle><jtitle>IOP conference series. Earth and environmental science</jtitle><addtitle>IOP Conf. Ser.: Earth Environ. Sci</addtitle><date>2023-05-01</date><risdate>2023</risdate><volume>1167</volume><issue>1</issue><spage>12016</spage><pages>12016-</pages><issn>1755-1307</issn><eissn>1755-1315</eissn><abstract>This study aims to compare the relationship between climate variables and rice productivity under different irrigation systems (irrigated and rainfed) in the clustering area on Java Island, Indonesia. This study used the clustering areas resulting from the previous study. The climate variables used are bias-corrected MERRA2 data from the period 1987–2017, cropped for Java Island. The rice productivity and reference evapotranspiration data used in this study are the results of the simulation of Aquacrop modeling. The result from the cluster method used tends to divide Java Island into 2 clusters with different altitudes (lowland and highland) areas. The results show that the correlation values between the precipitation variable and rice productivity from Aquacrop simulation (both irrigated or rainfed) in cluster 1 (dominated lowlands) are higher than in cluster 2 (dominated highlands), contrary to that the correlation values between the reference evapotranspiration variable with rice productivity from Aquacrop simulation (both irrigated or rainfed) are higher in cluster 2 (dominated highlands) areas, compared to cluster 1 areas (dominated lowlands). R-square values from response surface methodology (RSM) on the rainfed system in both clusters are higher than those on the irrigated system. This indicates that rainfed agriculture is highly dependent on climate variables, especially precipitation and reference evapotranspiration variables compared with the regular irrigated agricultural system. The RSM result also shows that climate variables significantly contribute to the variation of rice productivity generated by Aquacrop modeling in irrigated and rainfed systems and in all clusters.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1755-1315/1167/1/012016</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aquacrop crop modeling Clustering Evapotranspiration Farming systems Highlands Irrigation systems Lowlands Modelling Precipitation Productivity Rainfall Rainfed farming Response surface methodology Rice Rice productivity Simulation Variables |
title | The comparison of relationship between climate variables and rice productivity in the clustering area on Java Island, Indonesia |
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