Risk Assessment and Prediction of Reclaimed Water Utilization in Yuyao City, China

Reclaimed water can alleviate urban water scarcity, but its utilization involves risks across production, transmission, utilization, and management. This study established an 18-indicator assessment system for Yuyao City. Analytic hierarchy process (AHP) and entropy weights were combined using a game-theory-based procedure, while a fuzzy matter-element model assessed historical risks during 2020–2023. Nonlinear autoregressive models generated three output settings for seven time series, forming 2187 nonprobabilistic input combinations for 2025, 2030, and 2035. Historical risk remained within the medium-risk class but declined annually. Production and utilization received the largest criterion weights (0.352 and 0.336, respectively). The proportion of reclaimed water usage, reclaimed water utilization rate, green space rate in built-up areas, investment proportion, and industrial water reuse rate received the highest indicator weights. Across the constructed combinations, risk indices ranged from 0.361 to 0.469 in 2025, 0.376 to 0.420 in 2030, and 0.286 to 0.339 in 2035, with arithmetic means of 0.413, 0.395, and 0.312, respectively. All ranges remained within the medium-risk class. Further risk reduction requires coordinated improvements in production capacity, pipeline coverage, utilization, and institutional support. Future studies should use longer time series, time-ordered validation, and sensitivity tests of weights and thresholds.

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Publication Details

Journal
Water
Published
2026-10-29
DOI
https://doi.org/10.3390/w18212697
Primary Topic
Wastewater Treatment and Reuse
Type
article
Field-Weighted Citation Impact
0.00

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article

Risk Assessment and Prediction of Reclaimed Water Utilization in Yuyao City, China

Xiaomeng Song, Xiaojun Wang, 王德欣, Chenxu Guo
1 links
Water
Wastewater Treatment and Reuse
article

Risk Assessment and Prediction of Reclaimed Water Utilization in Yuyao City, China

Xiaomeng Song, Xiaojun Wang, 王德欣, Chenxu Guo
article en

Abstract

Reclaimed water can alleviate urban water scarcity, but its utilization involves risks across production, transmission, utilization, and management. This study established an 18-indicator assessment system for Yuyao City. Analytic hierarchy process (AHP) and entropy weights were combined using a game-theory-based procedure, while a fuzzy matter-element model assessed historical risks during 2020–2023. Nonlinear autoregressive models generated three output settings for seven time series, forming 2187 nonprobabilistic input combinations for 2025, 2030, and 2035. Historical risk remained within the medium-risk class but declined annually. Production and utilization received the largest criterion weights (0.352 and 0.336, respectively). The proportion of reclaimed water usage, reclaimed water utilization rate, green space rate in built-up areas, investment proportion, and industrial water reuse rate received the highest indicator weights. Across the constructed combinations, risk indices ranged from 0.361 to 0.469 in 2025, 0.376 to 0.420 in 2030, and 0.286 to 0.339 in 2035, with arithmetic means of 0.413, 0.395, and 0.312, respectively. All ranges remained within the medium-risk class. Further risk reduction requires coordinated improvements in production capacity, pipeline coverage, utilization, and institutional support. Future studies should use longer time series, time-ordered validation, and sensitivity tests of weights and thresholds.

WaterVol. 18(21)
China University of Mining and Technology (CN), Nanjing Hydraulic Research Institute (CN), Ministry of Water Resources of the People's Republic of China (CN)
National Natural Science Foundation of China
Clean water and sanitation, Sustainable cities and communities, Responsible consumption and production, Climate action, Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Wastewater Treatment and Reuse
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Risk Assessment and Prediction of Reclaimed Water Utilization in Yuyao City, China — Xiaomeng Song, Xiaojun Wang, et al. · Water (2026) | TGRS Research Map | TGRS