Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed
Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processe...
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Veröffentlicht in: | Journal of environmental management 2023-01, Vol.325, p.116559-116559, Article 116559 |
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description | Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.
[Display omitted]
•Subbasins with high nutrient loads and yields were identified as hotspots.•Nutrient source contributions showed spatial variability with urbanization levels.•Landscape configuration regulate the land to water transport processes of nutrients.•The biggest patch index of grassland promoted the land-water delivery of TN and TP. |
doi_str_mv | 10.1016/j.jenvman.2022.116559 |
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[Display omitted]
•Subbasins with high nutrient loads and yields were identified as hotspots.•Nutrient source contributions showed spatial variability with urbanization levels.•Landscape configuration regulate the land to water transport processes of nutrients.•The biggest patch index of grassland promoted the land-water delivery of TN and TP.</description><identifier>ISSN: 0301-4797</identifier><identifier>EISSN: 1095-8630</identifier><identifier>DOI: 10.1016/j.jenvman.2022.116559</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>forests ; grasslands ; Landscape pattern ; landscapes ; nitrogen ; Nutrient ; nutrient transport ; pollutants ; pollution ; rivers ; sewage ; sewage treatment ; SPARROW model ; Urban ; urbanization ; Water quality ; watershed management ; watersheds</subject><ispartof>Journal of environmental management, 2023-01, Vol.325, p.116559-116559, Article 116559</ispartof><rights>2022 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-8528259c2e03a43b78d26a02d8f5f58ae1d931560177287a4f186feaf0134fa53</citedby><cites>FETCH-LOGICAL-c375t-8528259c2e03a43b78d26a02d8f5f58ae1d931560177287a4f186feaf0134fa53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0301479722021326$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Liu, Jin</creatorcontrib><creatorcontrib>Yan, Tiezhu</creatorcontrib><creatorcontrib>Bai, Jianwen</creatorcontrib><creatorcontrib>Shen, Zhenyao</creatorcontrib><title>Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed</title><title>Journal of environmental management</title><description>Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.
[Display omitted]
•Subbasins with high nutrient loads and yields were identified as hotspots.•Nutrient source contributions showed spatial variability with urbanization levels.•Landscape configuration regulate the land to water transport processes of nutrients.•The biggest patch index of grassland promoted the land-water delivery of TN and TP.</description><subject>forests</subject><subject>grasslands</subject><subject>Landscape pattern</subject><subject>landscapes</subject><subject>nitrogen</subject><subject>Nutrient</subject><subject>nutrient transport</subject><subject>pollutants</subject><subject>pollution</subject><subject>rivers</subject><subject>sewage</subject><subject>sewage treatment</subject><subject>SPARROW model</subject><subject>Urban</subject><subject>urbanization</subject><subject>Water quality</subject><subject>watershed management</subject><subject>watersheds</subject><issn>0301-4797</issn><issn>1095-8630</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkUtLAzEUhYMoWB8_QcjSzdQ8mklmJVJ8FAQ3ug63mTs1ZZoZk0yl4o93at27uRcu3zlw7iHkirMpZ7y8WU_XGLYbCFPBhJhyXipVHZEJZ5UqTCnZMZkwyXgx05U-JWcprRljUnA9Id-LkHEVIfuwoqkbokMKfd_F7LuwwZAphJq240gOeqQ95IwxJJo7Oh7yEJGGIUe_R7cQPSx96_OOgotdShRo3vXeQUuHuITgv7CmnzBapHesL8hJA23Cy799Tt4e7l_nT8Xzy-NifvdcOKlVLowSRqjKCWQSZnKpTS1KYKI2jWqUAeR1JbkqGddaGA2zhpuyQWgYl7MGlDwn1wffPnYfA6ZsNz45bMdY2A3JjmJpRKkr8y8qtKiYqEqzR9UB_U0asbF99BuIO8uZ3Rdj1_avGLsvxh6KGXW3Bx2Okbceo01ufJ_D2kd02dad_8fhB7m9nBo</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Liu, Jin</creator><creator>Yan, Tiezhu</creator><creator>Bai, Jianwen</creator><creator>Shen, Zhenyao</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20230101</creationdate><title>Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed</title><author>Liu, Jin ; Yan, Tiezhu ; Bai, Jianwen ; Shen, Zhenyao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-8528259c2e03a43b78d26a02d8f5f58ae1d931560177287a4f186feaf0134fa53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>forests</topic><topic>grasslands</topic><topic>Landscape pattern</topic><topic>landscapes</topic><topic>nitrogen</topic><topic>Nutrient</topic><topic>nutrient transport</topic><topic>pollutants</topic><topic>pollution</topic><topic>rivers</topic><topic>sewage</topic><topic>sewage treatment</topic><topic>SPARROW model</topic><topic>Urban</topic><topic>urbanization</topic><topic>Water quality</topic><topic>watershed management</topic><topic>watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Jin</creatorcontrib><creatorcontrib>Yan, Tiezhu</creatorcontrib><creatorcontrib>Bai, Jianwen</creatorcontrib><creatorcontrib>Shen, Zhenyao</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of environmental management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Jin</au><au>Yan, Tiezhu</au><au>Bai, Jianwen</au><au>Shen, Zhenyao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed</atitle><jtitle>Journal of environmental management</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>325</volume><spage>116559</spage><epage>116559</epage><pages>116559-116559</pages><artnum>116559</artnum><issn>0301-4797</issn><eissn>1095-8630</eissn><abstract>Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.
[Display omitted]
•Subbasins with high nutrient loads and yields were identified as hotspots.•Nutrient source contributions showed spatial variability with urbanization levels.•Landscape configuration regulate the land to water transport processes of nutrients.•The biggest patch index of grassland promoted the land-water delivery of TN and TP.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.jenvman.2022.116559</doi><tpages>1</tpages></addata></record> |
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subjects | forests grasslands Landscape pattern landscapes nitrogen Nutrient nutrient transport pollutants pollution rivers sewage sewage treatment SPARROW model Urban urbanization Water quality watershed management watersheds |
title | Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed |
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