Identification of the ＂source＂ and ＂sink＂ patterns influencing non-point source pollution in the Three Gorges Reservoir Area
Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established...
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| Veröffentlicht in: | Journal of geographical sciences 2016-10, Vol.26 (10), p.1431-1448 |
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| creator | Wang, Jinliang Shao, Jing’an Wang, Dan Ni, Jiupai Xie, Deti |
| description | Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape re- sistance and motivation coefficients were constructed based on the distances from the land- scape units to the sub-basin outlets in order to identify the ＂source＂ and ＂sink＂ patterns af- fecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increas- ingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution ＂source＂ and ＂sink＂ patterns. Moreover, the proposed model could be used to de- scribe the large-scale spatial characteristics of non-point source pollution formation based on ＂source＂ and ＂sink＂ landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients. |
| doi_str_mv | 10.1007/s11442-016-1336-6 |
| format | Article |
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In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape re- sistance and motivation coefficients were constructed based on the distances from the land- scape units to the sub-basin outlets in order to identify the ＂source＂ and ＂sink＂ patterns af- fecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increas- ingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution ＂source＂ and ＂sink＂ patterns. Moreover, the proposed model could be used to de- scribe the large-scale spatial characteristics of non-point source pollution formation based on ＂source＂ and ＂sink＂ landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients.</description><identifier>ISSN: 1009-637X</identifier><identifier>EISSN: 1861-9568</identifier><identifier>DOI: 10.1007/s11442-016-1336-6</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Canyons ; Earth and Environmental Science ; Geographical Information Systems/Cartography ; Geography ; Hydrology ; Land use ; Landscape ; Nature Conservation ; Nonpoint source pollution ; Outlets ; Physical Geography ; Point source pollution ; Remote Sensing/Photogrammetry ; Reservoirs ; Spatial distribution ; 三峡库区 ; 动力系数 ; 土地利用 ; 成本模型 ; 景观元素 ; 景观格局指数 ; 生态环境 ; 非点源污染</subject><ispartof>Journal of geographical sciences, 2016-10, Vol.26 (10), p.1431-1448</ispartof><rights>Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2016</rights><rights>Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2016.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c376t-4c6b10319165e38228b953a1203d89c7b729318b24454819008d0e5fc610f9c53</citedby><cites>FETCH-LOGICAL-c376t-4c6b10319165e38228b953a1203d89c7b729318b24454819008d0e5fc610f9c53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/85906X/85906X.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11442-016-1336-6$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918587158?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,33745,41488,42557,43805,51319,64385,64387,64389,72469</link.rule.ids></links><search><creatorcontrib>Wang, Jinliang</creatorcontrib><creatorcontrib>Shao, Jing’an</creatorcontrib><creatorcontrib>Wang, Dan</creatorcontrib><creatorcontrib>Ni, Jiupai</creatorcontrib><creatorcontrib>Xie, Deti</creatorcontrib><title>Identification of the ＂source＂ and ＂sink＂ patterns influencing non-point source pollution in the Three Gorges Reservoir Area</title><title>Journal of geographical sciences</title><addtitle>J. Geogr. Sci</addtitle><addtitle>Journal of Geographical Sciences</addtitle><description>Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape re- sistance and motivation coefficients were constructed based on the distances from the land- scape units to the sub-basin outlets in order to identify the ＂source＂ and ＂sink＂ patterns af- fecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increas- ingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution ＂source＂ and ＂sink＂ patterns. Moreover, the proposed model could be used to de- scribe the large-scale spatial characteristics of non-point source pollution formation based on ＂source＂ and ＂sink＂ landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients.</description><subject>Canyons</subject><subject>Earth and Environmental Science</subject><subject>Geographical Information Systems/Cartography</subject><subject>Geography</subject><subject>Hydrology</subject><subject>Land use</subject><subject>Landscape</subject><subject>Nature Conservation</subject><subject>Nonpoint source pollution</subject><subject>Outlets</subject><subject>Physical Geography</subject><subject>Point source pollution</subject><subject>Remote Sensing/Photogrammetry</subject><subject>Reservoirs</subject><subject>Spatial distribution</subject><subject>三峡库区</subject><subject>动力系数</subject><subject>土地利用</subject><subject>成本模型</subject><subject>景观元素</subject><subject>景观格局指数</subject><subject>生态环境</subject><subject>非点源污染</subject><issn>1009-637X</issn><issn>1861-9568</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kc9qFTEUxgepYFt9AHfBbrqJ5uTfJMtSalsoCFLBXZibe-be1GkyTWYEt-Jj-U59BXPvFAsuXOUk_L7vnJyvad4Cew-MtR8KgJScMtAUhNBUv2gOwWigVmlzUGvGLNWi_fqqOSrljjFhpeaHza_rNcYp9MF3U0iRpJ5MWySPv3-WNGePtSBdXO8fQvy2u47dNGGOhYTYDzNGH-KGxBTpmEKcyKIjYxqGeW8Z4t7ydpsRyWXKGyzkMxbM31PI5Cxj97p52XdDwTdP53Hz5ePF7fkVvfl0eX1-dkO9aPVEpdcrYAIsaIXCcG5WVokOOBNrY327arkVYFZcSiUNWMbMmqHqvQbWW6_EcXO6-I45PcxYJncfisdh6CKmubi6MCM4UxIqevIPelf_Fet0jlswyrSgTKVgoXxOpWTs3ZjDfZd_OGBul4tbcnE1F7fLxemq4YumVDZuMD87_0_07qnRNsXNQ9X97aS11VKJupg_EIafzA</recordid><startdate>20161001</startdate><enddate>20161001</enddate><creator>Wang, Jinliang</creator><creator>Shao, Jing’an</creator><creator>Wang, Dan</creator><creator>Ni, Jiupai</creator><creator>Xie, Deti</creator><general>Science Press</general><general>Springer Nature B.V</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W94</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7TG</scope><scope>7TV</scope><scope>C1K</scope><scope>KL.</scope></search><sort><creationdate>20161001</creationdate><title>Identification of the ＂source＂ and ＂sink＂ patterns influencing non-point source pollution in the Three Gorges Reservoir Area</title><author>Wang, Jinliang ; Shao, Jing’an ; Wang, Dan ; Ni, Jiupai ; Xie, Deti</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c376t-4c6b10319165e38228b953a1203d89c7b729318b24454819008d0e5fc610f9c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Canyons</topic><topic>Earth and Environmental Science</topic><topic>Geographical Information Systems/Cartography</topic><topic>Geography</topic><topic>Hydrology</topic><topic>Land use</topic><topic>Landscape</topic><topic>Nature Conservation</topic><topic>Nonpoint source pollution</topic><topic>Outlets</topic><topic>Physical Geography</topic><topic>Point source pollution</topic><topic>Remote Sensing/Photogrammetry</topic><topic>Reservoirs</topic><topic>Spatial distribution</topic><topic>三峡库区</topic><topic>动力系数</topic><topic>土地利用</topic><topic>成本模型</topic><topic>景观元素</topic><topic>景观格局指数</topic><topic>生态环境</topic><topic>非点源污染</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Jinliang</creatorcontrib><creatorcontrib>Shao, Jing’an</creatorcontrib><creatorcontrib>Wang, Dan</creatorcontrib><creatorcontrib>Ni, Jiupai</creatorcontrib><creatorcontrib>Xie, Deti</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-自然科学</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Earth, Atmospheric & Aquatic Science 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>Meteorological & Geoastrophysical Abstracts</collection><collection>Pollution Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><jtitle>Journal of geographical sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Jinliang</au><au>Shao, Jing’an</au><au>Wang, Dan</au><au>Ni, Jiupai</au><au>Xie, Deti</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of the ＂source＂ and ＂sink＂ patterns influencing non-point source pollution in the Three Gorges Reservoir Area</atitle><jtitle>Journal of geographical sciences</jtitle><stitle>J. Geogr. Sci</stitle><addtitle>Journal of Geographical Sciences</addtitle><date>2016-10-01</date><risdate>2016</risdate><volume>26</volume><issue>10</issue><spage>1431</spage><epage>1448</epage><pages>1431-1448</pages><issn>1009-637X</issn><eissn>1861-9568</eissn><abstract>Non-point source pollution is one of the primarily ecological issues affecting the Three Gorges Reservoir Area. In this paper, landscape resistance and motivation coefficient, which integrated various landscape elements, such as land use, soil, hydrology, topography, and vegetation, was established based on the effects of large-scale resistance and motivation on the formation of non-point source pollution. In addition, cost models of the landscape re- sistance and motivation coefficients were constructed based on the distances from the land- scape units to the sub-basin outlets in order to identify the ＂source＂ and ＂sink＂ patterns af- fecting the formation of non-point source pollution. The results indicated that the changes in the landscape resistance and motivation coefficients of the 16 sub-basins exhibited inverse relationships to their spatial distributions. The landscape resistance and motivation cost curves were more volatile than the landscape resistance and motivation coefficient curves. The landscape resistance and motivation cost trends of the 16 sub-basins became increas- ingly apparent along the flow of the Yangtze River. The landscape resistance and motivation cost models proposed in this paper could be used to identify large-scale non-point source pollution ＂source＂ and ＂sink＂ patterns. Moreover, the proposed model could be used to de- scribe the large-scale spatial characteristics of non-point source pollution formation based on ＂source＂ and ＂sink＂ landscape pattern indices, spatial localization, and landscape resistance and motivation coefficients.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s11442-016-1336-6</doi><tpages>18</tpages></addata></record> |
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| subjects | Canyons Earth and Environmental Science Geographical Information Systems/Cartography Geography Hydrology Land use Landscape Nature Conservation Nonpoint source pollution Outlets Physical Geography Point source pollution Remote Sensing/Photogrammetry Reservoirs Spatial distribution 三峡库区 动力系数 土地利用 成本模型 景观元素 景观格局指数 生态环境 非点源污染 |
| title | Identification of the ＂source＂ and ＂sink＂ patterns influencing non-point source pollution in the Three Gorges Reservoir Area |
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