Optimization of Reclaimed Water Utilization in Urban Environmental Development: A Case Study of Shenzhen City

Optimization of Reclaimed Water Utilization in Urban Environmental Development: A Case Study of Shenzhen City | 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 Optimization of Reclaimed Water Utilization in Urban Environmental Development: A Case Study of Shenzhen City Jiawei Lei, Junfeng Zhang, Guochun Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8286135/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Reclaimed water utilization serves as a crucial approach to improving urban environments and addressing water scarcity in cities. Taking Shenzhen as an example, this study analyzes the factors influencing reclaimed water usage, conducts forecasts, and explores multi-objective optimization strategies to provide decision-making support for reclaimed water planning and construction. Twenty-six indicators were selected from both the supply and demand sides. Spearman correlation analysis and VIF multicollinearity diagnosis, combined with Lasso regression and XGBoost algorithms, were employed to screen key influencing factors. A Lasso regression model was constructed to predict reclaimed water utilization volume, while an NSGA-II algorithm-based multi-objective optimization model balanced the goals of maximizing utilization and minimizing costs. Six key influencing factors, including reclaimed water production capacity, were identified. The Lasso model demonstrated excellent predictive accuracy, with projected utilization volumes for 2024–2026 ranging from 203.7681 to 243.2656 million m³. Using NSGA-II to establish a mathematical model, a Pareto optimal solution set was generated. Combined with the entropy-weighted TOPSIS method, an objective decision scheme was obtained: controlling reclaimed water production capacity at 2.401 million m³/day and setting the reclaimed water price at ¥9,500/10,000 m³. The technology chain developed in this study enables precise analysis of reclaimed water utilization drivers. The predictive outcomes provide a quantitative basis for facility construction, while the optimized solution meets objective decision-making requirements. This approach supports sustainable water resource management in Shenzhen and offers a reference value for water resource management in other cities. Physical sciences/Engineering Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences Earth and environmental sciences/Hydrology Physical sciences/Mathematics and computing Scientific community and society/Water resources Reclaimed Water Utilization Volume Analysis of Influencing Factors Lasso Regression Prediction NSGA-II Entropy-Weighted TOPSIS Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8286135","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":562298351,"identity":"f73f5c2d-74ee-41f8-9dee-6812c35248d2","order_by":0,"name":"Jiawei Lei","email":"","orcid":"","institution":"Yunnan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jiawei","middleName":"","lastName":"Lei","suffix":""},{"id":562298352,"identity":"b40e2405-a7b3-49ae-ae60-d00d5dbb3920","order_by":1,"name":"Junfeng Zhang","email":"","orcid":"","institution":"Yunnan Agricultural 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Taking Shenzhen as an example, this study analyzes the factors influencing reclaimed water usage, conducts forecasts, and explores multi-objective optimization strategies to provide decision-making support for reclaimed water planning and construction. Twenty-six indicators were selected from both the supply and demand sides. Spearman correlation analysis and VIF multicollinearity diagnosis, combined with Lasso regression and XGBoost algorithms, were employed to screen key influencing factors. A Lasso regression model was constructed to predict reclaimed water utilization volume, while an NSGA-II algorithm-based multi-objective optimization model balanced the goals of maximizing utilization and minimizing costs. Six key influencing factors, including reclaimed water production capacity, were identified. 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