Water Environmental Health Assessment and Optimization Within a Pressure–State–Response Framework: A Case Study of the Hangzhou Bay Region, China

A healthy water environment is fundamental to maintaining ecosystem functions and supporting regional sustainable development. Water environmental health (WEH) management in estuarine and bay regions is challenged by interannual indicator variability, system imbalances, and management complexity. This study developed an integrated Water Environmental Health Assessment–Diagnosis–Optimization (WEH-ADO) framework combining interval information entropy (IIE), coupling coordination analysis, and indicator-adjustment optimization within pressure–state–response (PSR) structure. The framework was applied to the Zhejiang portion of the Hangzhou Bay region. The regional WEH index, constructed by aggregating the normalized pressure, state, and response indicators using IIE-derived weights, showed three distinct periods of change: an early decline, a mid-period improvement, and a later period of adjustment. Compared with the conventional entropy weight method, the IIE reduced the influence of individual indicators with high data dispersion. The coupling coordination analysis indicated high coupling among the PSR subsystems, with regional coordination classified as primarily or moderately coordinated. Using 2023 as the baseline year, a genetic algorithm was used to determine adjustment levels for eight indicators while holding the weights and non-adjustable indicators constant. The best-found scenario increased the mean WEH index from 0.498 to 0.528 and the mean coupling coordination degree from 0.657 to 0.681. These changes represent improvements in the calculated indices rather than simulated water-quality responses. A key finding was that the lowest-scoring indicators were not necessarily assigned the highest adjustment priorities by the optimization model. At the city level, Hangzhou, Ningbo, and Shaoxing together accounted for 82.3% of the total increase in the WEH index; at the indicator-adjustment level, ecological water replenishment (29.2%), soil erosion control (19.6%), wastewater discharge reduction (17.1%), and chemical oxygen demand discharge reduction (16.7%) jointly accounted for 82.6% of this increase. Overall, the WEH-ADO framework incorporates observed interannual variability into indicator weighting and links assessment and subsystem diagnosis to city- and indicator-specific adjustment scenarios.

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Journal
Sustainability
Published
2026-10-09
DOI
https://doi.org/10.3390/su182010262
Primary Topic
Water Resources and Sustainability
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Water Environmental Health Assessment and Optimization Within a Pressure–State–Response Framework: A Case Study of the Hangzhou Bay Region, China

Yuhan Han, Shan Zhang, Zhuo Zeng, Fusen Wei
Sustainability
Water Resources and Sustainability
article

Water Environmental Health Assessment and Optimization Within a Pressure–State–Response Framework: A Case Study of the Hangzhou Bay Region, China

Yuhan Han, Shan Zhang, Zhuo Zeng, Fusen Wei
article en

Abstract

A healthy water environment is fundamental to maintaining ecosystem functions and supporting regional sustainable development. Water environmental health (WEH) management in estuarine and bay regions is challenged by interannual indicator variability, system imbalances, and management complexity. This study developed an integrated Water Environmental Health Assessment–Diagnosis–Optimization (WEH-ADO) framework combining interval information entropy (IIE), coupling coordination analysis, and indicator-adjustment optimization within pressure–state–response (PSR) structure. The framework was applied to the Zhejiang portion of the Hangzhou Bay region. The regional WEH index, constructed by aggregating the normalized pressure, state, and response indicators using IIE-derived weights, showed three distinct periods of change: an early decline, a mid-period improvement, and a later period of adjustment. Compared with the conventional entropy weight method, the IIE reduced the influence of individual indicators with high data dispersion. The coupling coordination analysis indicated high coupling among the PSR subsystems, with regional coordination classified as primarily or moderately coordinated. Using 2023 as the baseline year, a genetic algorithm was used to determine adjustment levels for eight indicators while holding the weights and non-adjustable indicators constant. The best-found scenario increased the mean WEH index from 0.498 to 0.528 and the mean coupling coordination degree from 0.657 to 0.681. These changes represent improvements in the calculated indices rather than simulated water-quality responses. A key finding was that the lowest-scoring indicators were not necessarily assigned the highest adjustment priorities by the optimization model. At the city level, Hangzhou, Ningbo, and Shaoxing together accounted for 82.3% of the total increase in the WEH index; at the indicator-adjustment level, ecological water replenishment (29.2%), soil erosion control (19.6%), wastewater discharge reduction (17.1%), and chemical oxygen demand discharge reduction (16.7%) jointly accounted for 82.6% of this increase. Overall, the WEH-ADO framework incorporates observed interannual variability into indicator weighting and links assessment and subsystem diagnosis to city- and indicator-specific adjustment scenarios.

SustainabilityVol. 18(20)
Zhejiang University of Water Resource and Electric Power (CN), Zhejiang University (CN)
Openalex Percentile: Top 24%
Water Resources and Sustainability
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