Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China
The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial change...
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| Veröffentlicht in: | Sustainability 2023-01, Vol.15 (2), p.1269 |
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| creator | Xu, Cundong Hu, Xiaomeng Liu, Zijin Wang, Xin Tian, Junjiao Zhao, Zhihong |
| description | The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization. |
| doi_str_mv | 10.3390/su15021269 |
| format | Article |
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This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su15021269</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Arid zones ; Carrying capacity ; Climate change ; Desertification ; Deserts ; Irrigation ; Land resources ; Land use ; Landsat ; Markov chains ; Precipitation ; Regional development ; Regional planning ; Regions ; Remote sensing ; Resource allocation ; Resource availability ; Salinization ; Simulation ; Soil salinity ; Subjectivity ; Sustainability ; Sustainable development</subject><ispartof>Sustainability, 2023-01, Vol.15 (2), p.1269</ispartof><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-c295t-88229e74830a299dae203f89c0dfafca4805fdf0f5394c117ac9f233668eb37a3</citedby><cites>FETCH-LOGICAL-c295t-88229e74830a299dae203f89c0dfafca4805fdf0f5394c117ac9f233668eb37a3</cites><orcidid>0000-0002-4566-7234 ; 0000-0003-3626-887X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Xu, Cundong</creatorcontrib><creatorcontrib>Hu, Xiaomeng</creatorcontrib><creatorcontrib>Liu, Zijin</creatorcontrib><creatorcontrib>Wang, Xin</creatorcontrib><creatorcontrib>Tian, Junjiao</creatorcontrib><creatorcontrib>Zhao, Zhihong</creatorcontrib><title>Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China</title><title>Sustainability</title><description>The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization.</description><subject>Arid zones</subject><subject>Carrying capacity</subject><subject>Climate change</subject><subject>Desertification</subject><subject>Deserts</subject><subject>Irrigation</subject><subject>Land resources</subject><subject>Land use</subject><subject>Landsat</subject><subject>Markov chains</subject><subject>Precipitation</subject><subject>Regional development</subject><subject>Regional planning</subject><subject>Regions</subject><subject>Remote sensing</subject><subject>Resource allocation</subject><subject>Resource availability</subject><subject>Salinization</subject><subject>Simulation</subject><subject>Soil salinity</subject><subject>Subjectivity</subject><subject>Sustainability</subject><subject>Sustainable development</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpNkMtKAzEUhoMoWGo3PkHAnVDNZW5Z1qFeoFWRisvhmEna1DqpSabSnXuXvqFPYoYKehbnAuf_DudH6JiSM84FOfctTQmjLBN7qMdIToeUpGT_X3-IBt4vSQzOqaBZD33eO1UbGUwzx2Gh8HhjV20wtsEzp5oaW42fICiHIQ6TLj0ob1snFS7BuW2nK2EN0oQtvgCvoqTB5ej742sK7sVu8NTWaoVNEwl45EwHmHf8SL61LizelQ-4XJgGjtCBhpVXg9_aR4-X41l5PZzcXd2Uo8lQMpGGYVEwJlSeFJwAE6IGxQjXhZCk1qAlJAVJda2JTrlIJKU5SKEZ51lWqGeeA--jkx137exbG89Xy_hRE09WLM9yJookzePW6W5LOuu9U7paO_MKbltRUnV-V39-8x_YnHNQ</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Xu, Cundong</creator><creator>Hu, Xiaomeng</creator><creator>Liu, Zijin</creator><creator>Wang, Xin</creator><creator>Tian, Junjiao</creator><creator>Zhao, Zhihong</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>4U-</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><orcidid>https://orcid.org/0000-0002-4566-7234</orcidid><orcidid>https://orcid.org/0000-0003-3626-887X</orcidid></search><sort><creationdate>20230101</creationdate><title>Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China</title><author>Xu, Cundong ; Hu, Xiaomeng ; Liu, Zijin ; Wang, Xin ; Tian, Junjiao ; Zhao, Zhihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-88229e74830a299dae203f89c0dfafca4805fdf0f5394c117ac9f233668eb37a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Arid zones</topic><topic>Carrying capacity</topic><topic>Climate change</topic><topic>Desertification</topic><topic>Deserts</topic><topic>Irrigation</topic><topic>Land resources</topic><topic>Land use</topic><topic>Landsat</topic><topic>Markov chains</topic><topic>Precipitation</topic><topic>Regional development</topic><topic>Regional planning</topic><topic>Regions</topic><topic>Remote sensing</topic><topic>Resource allocation</topic><topic>Resource availability</topic><topic>Salinization</topic><topic>Simulation</topic><topic>Soil salinity</topic><topic>Subjectivity</topic><topic>Sustainability</topic><topic>Sustainable development</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Cundong</creatorcontrib><creatorcontrib>Hu, Xiaomeng</creatorcontrib><creatorcontrib>Liu, Zijin</creatorcontrib><creatorcontrib>Wang, Xin</creatorcontrib><creatorcontrib>Tian, Junjiao</creatorcontrib><creatorcontrib>Zhao, Zhihong</creatorcontrib><collection>CrossRef</collection><collection>University Readers</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><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Cundong</au><au>Hu, Xiaomeng</au><au>Liu, Zijin</au><au>Wang, Xin</au><au>Tian, Junjiao</au><au>Zhao, Zhihong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China</atitle><jtitle>Sustainability</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>15</volume><issue>2</issue><spage>1269</spage><pages>1269-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>The evolution of water and land resource carrying capacity significantly impacts optimal water and land resource allocation and regional sustainable development in arid regions. This study proposes a model that combines cellular automaton (CA) and Markov; this model aids in predicting spatial changes in water and land resource availability. In this study, taking the Jingdian Irrigation District in China’s northwest arid region as an example, we used long-series monitoring data and a Landsat dataset to create a raster-weighted fusion of 18 indicators and quantitatively analyzed the carrying status of water and land resources from 1994 to 2018. The CA–Markov model was used to simulate the carrying status of water and land resources in 2018 and to perform accuracy correction. The validated CA–Markov model was used to predict water and land resource carrying status in 2026 and 2034. The results show (1) from 1994 to 2018, the area of “good carrying” zone increased by 10.42%, the area of “safe carrying” zone increased by 7%, and spatially rose in an arc from the town to the surrounding regions. The area of “critical carrying” zone remains almost unchanged. The area of “slight carrying” zone decreased by 5.18% and the area of “severe carrying” zone decreased by 11.99%. (2) Comparing the actual and predicted carrying state of water and land resources in 2018, it was found that the simulation accuracy of “good carrying”, “safe carrying”, “critical carrying”, “slight carrying”, and “severe carrying” reached 98.71%, 92.07%, 95.34%, 94.05%, and 93.73%, respectively. This indicates that the simulation results have high reliability and applicability. (3) The future medium and long-term carrying status of water and land resources are healthy, but this trend is gradually slowing. The “slight carrying” and “severe carrying” zones show the gradual spatial transition from land desertification to soil salinization.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su15021269</doi><orcidid>https://orcid.org/0000-0002-4566-7234</orcidid><orcidid>https://orcid.org/0000-0003-3626-887X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Arid zones Carrying capacity Climate change Desertification Deserts Irrigation Land resources Land use Landsat Markov chains Precipitation Regional development Regional planning Regions Remote sensing Resource allocation Resource availability Salinization Simulation Soil salinity Subjectivity Sustainability Sustainable development |
| title | Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China |
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