Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model
As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quanti...
Gespeichert in:
Veröffentlicht in: | Water (Basel) 2023-02, Vol.15 (3), p.514 |
---|---|
Hauptverfasser: | , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 3 |
container_start_page | 514 |
container_title | Water (Basel) |
container_volume | 15 |
creator | Wang, Zongmin Li, Qizhao Liu, Lin Zhao, Hongling Ru, Hongen Wu, Jiapeng Deng, Yanli |
description | As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quantitative analysis of the driving forces of climate change and land use on water-yield change. Quantitative evaluation of water yield in the XRB is of great significance for optimizing water-resource planning and allocation and maintaining ecological balance in the basin. In this paper, the seasonal water-yield InVEST model and modified Morris sensitivity analysis were combined to study the characteristics of monthly water yield in the XRB. Seventeen attributes were identified using the Budyko framework. The results show that: (1) the water yield of the XRB showed an increase trend from northeast to southwest from 2006 to 2020; (2) the transfer-in of unused land, grassland, woodland and farmland as well as the transfer-out of water and construction land have positive effects on the increase in water yield, and the change to construction land has the greatest impact on water yield; (3) water yield is positively correlated with NDVI and precipitation and negatively correlated with potential evapotranspiration; (4) climate change and land-use change contributed to water-yield changes of 67.08% and 32.92%, respectively. |
doi_str_mv | 10.3390/w15030514 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_3153196413</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A793564706</galeid><sourcerecordid>A793564706</sourcerecordid><originalsourceid>FETCH-LOGICAL-c364t-b2e2ab9f92e200568aee255f75fb62270edca5321269b93aa71f2083d069d1c53</originalsourceid><addsrcrecordid>eNpdkd1LHDEQwJfSgmLvwf8g4Is-nOZz9_J4yrUKiuBZa5-W2d2J5sgl1ySn-OLf3hwrpXQG5vM3A8NU1SGjp0JoevbKFBVUMfmp2ue0EVMpJfv8T7xXTVJa0SJSz2aK7lfvyw1kGzKuNyGCI4uX4Lal4An4gcxzjrYb87kH95ZsIsGQn5Axkl8W3UCsJ_kZyaMF_7TaGXJnX0r3HFJpHT_enZ_sYhxIGMkr_7BY3pObMKD7Wn0x4BJOPvxB9ePb4v7icnp9-_3qYn497UUt87TjyKHTRhdPqapngMiVMo0yXc15Q3HoQQnOeK07LQAaZjidiYHWemC9EgfV8bh3E8PvLabcrm3q0TnwGLapFUwJpmvJREGP_kNXYRvL8anlTSO1ElTvqNORegKHrfUm5Ah90QHXtg8ejS31eaOFqmVD6zJwMg70MaQU0bSbaNcQ31pG29332r_fE38AhNSJ-g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2774953093</pqid></control><display><type>article</type><title>Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Wang, Zongmin ; Li, Qizhao ; Liu, Lin ; Zhao, Hongling ; Ru, Hongen ; Wu, Jiapeng ; Deng, Yanli</creator><creatorcontrib>Wang, Zongmin ; Li, Qizhao ; Liu, Lin ; Zhao, Hongling ; Ru, Hongen ; Wu, Jiapeng ; Deng, Yanli</creatorcontrib><description>As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quantitative analysis of the driving forces of climate change and land use on water-yield change. Quantitative evaluation of water yield in the XRB is of great significance for optimizing water-resource planning and allocation and maintaining ecological balance in the basin. In this paper, the seasonal water-yield InVEST model and modified Morris sensitivity analysis were combined to study the characteristics of monthly water yield in the XRB. Seventeen attributes were identified using the Budyko framework. The results show that: (1) the water yield of the XRB showed an increase trend from northeast to southwest from 2006 to 2020; (2) the transfer-in of unused land, grassland, woodland and farmland as well as the transfer-out of water and construction land have positive effects on the increase in water yield, and the change to construction land has the greatest impact on water yield; (3) water yield is positively correlated with NDVI and precipitation and negatively correlated with potential evapotranspiration; (4) climate change and land-use change contributed to water-yield changes of 67.08% and 32.92%, respectively.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w15030514</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural land ; Analysis ; Aquatic resources ; Basins ; China ; Climate change ; Climatic changes ; Ecological balance ; Evapotranspiration ; Grasslands ; Human influences ; humans ; Hydrology ; Land use ; land use change ; Precipitation ; Precipitation (Meteorology) ; Quantitative analysis ; Radiation ; Remote sensing ; River basins ; River networks ; Rivers ; Runoff ; Sensitivity analysis ; Software ; Sustainable development ; Temperature ; water ; Water analysis ; Water resources ; Water shortages ; Water yield ; watersheds ; Woodlands</subject><ispartof>Water (Basel), 2023-02, Vol.15 (3), p.514</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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><citedby>FETCH-LOGICAL-c364t-b2e2ab9f92e200568aee255f75fb62270edca5321269b93aa71f2083d069d1c53</citedby><cites>FETCH-LOGICAL-c364t-b2e2ab9f92e200568aee255f75fb62270edca5321269b93aa71f2083d069d1c53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Wang, Zongmin</creatorcontrib><creatorcontrib>Li, Qizhao</creatorcontrib><creatorcontrib>Liu, Lin</creatorcontrib><creatorcontrib>Zhao, Hongling</creatorcontrib><creatorcontrib>Ru, Hongen</creatorcontrib><creatorcontrib>Wu, Jiapeng</creatorcontrib><creatorcontrib>Deng, Yanli</creatorcontrib><title>Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model</title><title>Water (Basel)</title><description>As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quantitative analysis of the driving forces of climate change and land use on water-yield change. Quantitative evaluation of water yield in the XRB is of great significance for optimizing water-resource planning and allocation and maintaining ecological balance in the basin. In this paper, the seasonal water-yield InVEST model and modified Morris sensitivity analysis were combined to study the characteristics of monthly water yield in the XRB. Seventeen attributes were identified using the Budyko framework. The results show that: (1) the water yield of the XRB showed an increase trend from northeast to southwest from 2006 to 2020; (2) the transfer-in of unused land, grassland, woodland and farmland as well as the transfer-out of water and construction land have positive effects on the increase in water yield, and the change to construction land has the greatest impact on water yield; (3) water yield is positively correlated with NDVI and precipitation and negatively correlated with potential evapotranspiration; (4) climate change and land-use change contributed to water-yield changes of 67.08% and 32.92%, respectively.</description><subject>Agricultural land</subject><subject>Analysis</subject><subject>Aquatic resources</subject><subject>Basins</subject><subject>China</subject><subject>Climate change</subject><subject>Climatic changes</subject><subject>Ecological balance</subject><subject>Evapotranspiration</subject><subject>Grasslands</subject><subject>Human influences</subject><subject>humans</subject><subject>Hydrology</subject><subject>Land use</subject><subject>land use change</subject><subject>Precipitation</subject><subject>Precipitation (Meteorology)</subject><subject>Quantitative analysis</subject><subject>Radiation</subject><subject>Remote sensing</subject><subject>River basins</subject><subject>River networks</subject><subject>Rivers</subject><subject>Runoff</subject><subject>Sensitivity analysis</subject><subject>Software</subject><subject>Sustainable development</subject><subject>Temperature</subject><subject>water</subject><subject>Water analysis</subject><subject>Water resources</subject><subject>Water shortages</subject><subject>Water yield</subject><subject>watersheds</subject><subject>Woodlands</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpdkd1LHDEQwJfSgmLvwf8g4Is-nOZz9_J4yrUKiuBZa5-W2d2J5sgl1ySn-OLf3hwrpXQG5vM3A8NU1SGjp0JoevbKFBVUMfmp2ue0EVMpJfv8T7xXTVJa0SJSz2aK7lfvyw1kGzKuNyGCI4uX4Lal4An4gcxzjrYb87kH95ZsIsGQn5Axkl8W3UCsJ_kZyaMF_7TaGXJnX0r3HFJpHT_enZ_sYhxIGMkr_7BY3pObMKD7Wn0x4BJOPvxB9ePb4v7icnp9-_3qYn497UUt87TjyKHTRhdPqapngMiVMo0yXc15Q3HoQQnOeK07LQAaZjidiYHWemC9EgfV8bh3E8PvLabcrm3q0TnwGLapFUwJpmvJREGP_kNXYRvL8anlTSO1ElTvqNORegKHrfUm5Ah90QHXtg8ejS31eaOFqmVD6zJwMg70MaQU0bSbaNcQ31pG29332r_fE38AhNSJ-g</recordid><startdate>20230201</startdate><enddate>20230201</enddate><creator>Wang, Zongmin</creator><creator>Li, Qizhao</creator><creator>Liu, Lin</creator><creator>Zhao, Hongling</creator><creator>Ru, Hongen</creator><creator>Wu, Jiapeng</creator><creator>Deng, Yanli</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20230201</creationdate><title>Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model</title><author>Wang, Zongmin ; Li, Qizhao ; Liu, Lin ; Zhao, Hongling ; Ru, Hongen ; Wu, Jiapeng ; Deng, Yanli</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-b2e2ab9f92e200568aee255f75fb62270edca5321269b93aa71f2083d069d1c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Agricultural land</topic><topic>Analysis</topic><topic>Aquatic resources</topic><topic>Basins</topic><topic>China</topic><topic>Climate change</topic><topic>Climatic changes</topic><topic>Ecological balance</topic><topic>Evapotranspiration</topic><topic>Grasslands</topic><topic>Human influences</topic><topic>humans</topic><topic>Hydrology</topic><topic>Land use</topic><topic>land use change</topic><topic>Precipitation</topic><topic>Precipitation (Meteorology)</topic><topic>Quantitative analysis</topic><topic>Radiation</topic><topic>Remote sensing</topic><topic>River basins</topic><topic>River networks</topic><topic>Rivers</topic><topic>Runoff</topic><topic>Sensitivity analysis</topic><topic>Software</topic><topic>Sustainable development</topic><topic>Temperature</topic><topic>water</topic><topic>Water analysis</topic><topic>Water resources</topic><topic>Water shortages</topic><topic>Water yield</topic><topic>watersheds</topic><topic>Woodlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Zongmin</creatorcontrib><creatorcontrib>Li, Qizhao</creatorcontrib><creatorcontrib>Liu, Lin</creatorcontrib><creatorcontrib>Zhao, Hongling</creatorcontrib><creatorcontrib>Ru, Hongen</creatorcontrib><creatorcontrib>Wu, Jiapeng</creatorcontrib><creatorcontrib>Deng, Yanli</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</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>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Zongmin</au><au>Li, Qizhao</au><au>Liu, Lin</au><au>Zhao, Hongling</au><au>Ru, Hongen</au><au>Wu, Jiapeng</au><au>Deng, Yanli</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model</atitle><jtitle>Water (Basel)</jtitle><date>2023-02-01</date><risdate>2023</risdate><volume>15</volume><issue>3</issue><spage>514</spage><pages>514-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>As a result of climate change and human activities, water resources in the Xiangjiang River Basin (XRB) are subject to seasonal and regional shortages. However, previous studies have lacked assessment of the spatiotemporal evolution of water yield in the XRB at seasonal and monthly scales and quantitative analysis of the driving forces of climate change and land use on water-yield change. Quantitative evaluation of water yield in the XRB is of great significance for optimizing water-resource planning and allocation and maintaining ecological balance in the basin. In this paper, the seasonal water-yield InVEST model and modified Morris sensitivity analysis were combined to study the characteristics of monthly water yield in the XRB. Seventeen attributes were identified using the Budyko framework. The results show that: (1) the water yield of the XRB showed an increase trend from northeast to southwest from 2006 to 2020; (2) the transfer-in of unused land, grassland, woodland and farmland as well as the transfer-out of water and construction land have positive effects on the increase in water yield, and the change to construction land has the greatest impact on water yield; (3) water yield is positively correlated with NDVI and precipitation and negatively correlated with potential evapotranspiration; (4) climate change and land-use change contributed to water-yield changes of 67.08% and 32.92%, respectively.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w15030514</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2073-4441 |
ispartof | Water (Basel), 2023-02, Vol.15 (3), p.514 |
issn | 2073-4441 2073-4441 |
language | eng |
recordid | cdi_proquest_miscellaneous_3153196413 |
source | MDPI - Multidisciplinary Digital Publishing Institute; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Agricultural land Analysis Aquatic resources Basins China Climate change Climatic changes Ecological balance Evapotranspiration Grasslands Human influences humans Hydrology Land use land use change Precipitation Precipitation (Meteorology) Quantitative analysis Radiation Remote sensing River basins River networks Rivers Runoff Sensitivity analysis Software Sustainable development Temperature water Water analysis Water resources Water shortages Water yield watersheds Woodlands |
title | Spatiotemporal Evolution and Attribution Analysis of Water Yield in the Xiangjiang River Basin (XRB) Based on the InVEST Model |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-12T23%3A55%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Spatiotemporal%20Evolution%20and%20Attribution%20Analysis%20of%20Water%20Yield%20in%20the%20Xiangjiang%20River%20Basin%20(XRB)%20Based%20on%20the%20InVEST%20Model&rft.jtitle=Water%20(Basel)&rft.au=Wang,%20Zongmin&rft.date=2023-02-01&rft.volume=15&rft.issue=3&rft.spage=514&rft.pages=514-&rft.issn=2073-4441&rft.eissn=2073-4441&rft_id=info:doi/10.3390/w15030514&rft_dat=%3Cgale_proqu%3EA793564706%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2774953093&rft_id=info:pmid/&rft_galeid=A793564706&rfr_iscdi=true |