Detection and Driving Factor Analysis of Hypoxia in River Estuarine Zones by Entropy Methods

• Published in: Water (Basel) Vol. 17; no. 13; p. 1862
• Main Authors: Pang, Tianrui, Zhang, Xiaoyu, Xiong, Ye, Wang, Hongjie, Chang, Sheng, Zheng, Tong, Jiang, Jiping
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2025
• Subjects: Datasets; Entropy; Environmental aspects; Environmental monitoring; Estuaries; Eutrophication; Fourier transforms; Hypoxia; Hypoxia (Aquatic ecology); Methods; Nitrogen; Pollution; Quality management; Rivers; Seasonal variations; Surface water; Temperature; Trends; Water quality; Wavelet transforms; China
• ISSN: 2073-4441; 2073-4441
• DOI: 10.3390/w17131862

Hypoxia in river estuaries poses significant ecological and water safety risks, yet long-term high-frequency monitoring data for comprehensive analysis remain scarce. This study investigates hypoxia dynamics in the Shenzhen River Estuary (southern China) using two-year high-frequency monitoring data. A hybrid anomaly detection method integrating wavelet analysis and temporal information entropy was developed to identify hypoxia events. The drivers of hypoxia were also identified with correlation coefficients and transfer entropy (TE). The results reveal frequent spring–summer hypoxia. Turbidity and total nitrogen (TN) exhibited significant negative correlations and time-lagged effects on dissolved oxygen (DO), where TE reaches a peak of 0.05 with lags of 36 and 72 h, respectively. Wastewater treatment plant (WWTP) loads, particularly suspended solids (SSs), showed a linear negative correlation with estuarine DO. Notably, the 2022 data showed minimal correlations (except SSs) due to high baseline pollution, whereas the post-remediation 2023 data revealed stronger linear linkages (especially r = −0.81 for SSs). The proposed “high-frequency localization–low-frequency assessment” detection method demonstrated robust accuracy in identifying hypoxia events, and mechanistic analysis corroborated the time-lagged pollutant impacts. These findings advance hypoxia identification frameworks and highlight the critical role of Turbidity and SSs in driving estuarine oxygen depletion, offering actionable insights for adaptive water quality management.