Integrated Assessment and Spatial Coordination Analysis of Water Resources Carrying Capacity in the Changbai Mountain Headwater Region Using Cloud Model and Geodetector Approach

Integrated Assessment and Spatial Coordination Analysis of Water Resources Carrying Capacity in the Changbai Mountain Headwater Region Using Cloud Model and Geodetector Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Integrated Assessment and Spatial Coordination Analysis of Water Resources Carrying Capacity in the Changbai Mountain Headwater Region Using Cloud Model and Geodetector Approach Yuqian Wang, Siyu Nie, Weimeng Han, BingWen Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6985728/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract The evaluation of Water Resources Carrying Capacity (WRCC) plays a critical role in understanding regional resource dynamics and guiding the sustainable allocation of water resources. Addressing the inherent uncertainties in hydrological systems and the subjectivity associated with indicator weighting, this study focuses on the headwater region of the Changbai Mountain area. A total of 28 indicators were selected from the "production–living–ecology" framework. A cloud model integrated with the entropy weight method was applied to comprehensively assess WRCC, while a geographical detector model was employed to identify key driving factors. Furthermore, the Coupled Coordination Degree Model (CCDM) was utilized to investigate the spatial coordination among WRCC subsystems across multiple administrative units. Key findings include: (1) From 2013 to 2022, the WRCC levels in Fusong County predominantly falled within levels II (Good load bearing) and III (Loadable weak), while Jingyu County and Changbai Korean Autonomous County were primarily at level IV (Loadable not loadable), and Linjiang City was largely at level III (Loadable weak). (2) WRCC indices generally declined from northeast to southwest. (3) Urbanization rate (0.712), water consumption rate for forestry (0.584), animal husbandry and fishery (0.539) were the most significant drivers. (4) Coupling degrees among regions ranged from 0.973 to 0.996, with most areas transitioning from imbalance to coordination, except Jingyu County. The study provides scientific insights for optimizing water resource allocation and balancing economic development, human livelihoods, and ecological preservation in the Changbai Mountain area and the middle and lower reaches of the cities in Jilin Province. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Earth and environmental sciences/Hydrology Water resources carrying capacity Cloud modeling Entropy method Coupled coordination degree Geodetector Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 29 Jul, 2025 Reviewers agreed at journal 28 Jul, 2025 Reviews received at journal 27 Jul, 2025 Reviewers agreed at journal 27 Jul, 2025 Reviews received at journal 19 Jul, 2025 Reviewers agreed at journal 16 Jul, 2025 Reviewers agreed at journal 15 Jul, 2025 Reviewers agreed at journal 15 Jul, 2025 Reviewers invited by journal 15 Jul, 2025 Editor assigned by journal 15 Jul, 2025 Editor invited by journal 07 Jul, 2025 Submission checks completed at journal 01 Jul, 2025 First submitted to journal 01 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6985728","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":486385445,"identity":"8ac9b131-30bc-4148-aae7-54ceeb25ce40","order_by":0,"name":"Yuqian Wang","email":"","orcid":"","institution":"Changchun Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yuqian","middleName":"","lastName":"Wang","suffix":""},{"id":486385448,"identity":"68735ea0-27d6-4c9c-8456-48f1acce9848","order_by":1,"name":"Siyu Nie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYDACZiBOYGCQY2BgbIByidRiDNTS2ECcFihIbIBYQ4QWc3bmwx8eth1O728/3P6AocI6sYH97AG8Wiyb2dIkEtsO5844kwh02Jn0xAaevAS8WgwO85gxgLRskAD6hbHtcGKDBI8BAS38nz8AtaQbgLX8I0oLDwPIYQkQLQ1EaWEzk0g4l24I8suMhGPpxm08OQS0nD/8+OOPMmt5/vbjDz58qLGW7Wc/g18LGDCyQRkJQMyGRyES+EOcslEwCkbBKBihAAA8wUXRlGSL2AAAAABJRU5ErkJggg==","orcid":"","institution":"Changchun Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Siyu","middleName":"","lastName":"Nie","suffix":""},{"id":486385449,"identity":"f218263f-dede-470d-a4be-040ca6ff94ad","order_by":2,"name":"Weimeng Han","email":"","orcid":"","institution":"Changchun Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Weimeng","middleName":"","lastName":"Han","suffix":""},{"id":486385450,"identity":"018569dd-864b-4059-b349-690ce3473aa2","order_by":3,"name":"BingWen Huang","email":"","orcid":"","institution":"Changchun Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"BingWen","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-06-26 17:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6985728/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6985728/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-23531-9","type":"published","date":"2025-11-13T15:58:35+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96105850,"identity":"1a2ff3b5-db23-42ba-ba1d-2199e930a96d","added_by":"auto","created_at":"2025-11-17 16:12:02","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1331310,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6985728/v1_covered_976dc6aa-a073-4101-9bb8-e5c9fdb2839a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated Assessment and Spatial Coordination Analysis of Water Resources Carrying Capacity in the Changbai Mountain Headwater Region Using Cloud Model and Geodetector Approach","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Water resources carrying capacity, Cloud modeling, Entropy method, Coupled coordination degree, Geodetector","lastPublishedDoi":"10.21203/rs.3.rs-6985728/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6985728/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe evaluation of Water Resources Carrying Capacity (WRCC) plays a critical role in understanding regional resource dynamics and guiding the sustainable allocation of water resources. Addressing the inherent uncertainties in hydrological systems and the subjectivity associated with indicator weighting, this study focuses on the headwater region of the Changbai Mountain area. A total of 28 indicators were selected from the \"production\u0026ndash;living\u0026ndash;ecology\" framework. A cloud model integrated with the entropy weight method was applied to comprehensively assess WRCC, while a geographical detector model was employed to identify key driving factors. Furthermore, the Coupled Coordination Degree Model (CCDM) was utilized to investigate the spatial coordination among WRCC subsystems across multiple administrative units. Key findings include: (1) From 2013 to 2022, the WRCC levels in Fusong County predominantly falled within levels II (Good load bearing) and III (Loadable weak), while Jingyu County and Changbai Korean Autonomous County were primarily at level IV (Loadable not loadable), and Linjiang City was largely at level III (Loadable weak). (2) WRCC indices generally declined from northeast to southwest. (3) Urbanization rate (0.712), water consumption rate for forestry (0.584), animal husbandry and fishery (0.539) were the most significant drivers. (4) Coupling degrees among regions ranged from 0.973 to 0.996, with most areas transitioning from imbalance to coordination, except Jingyu County. 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