Nong Xizhi, Zeng Jun, Chen Lihua, Wei Jiahua, Zhang Yanqing
National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing, 210029, China.
Pinglu Canal Group Corporation Limited, Nanning, 530000, China.
Sci Rep. 2025 Apr 24;15(1):14377. doi: 10.1038/s41598-025-98197-4.
Water quality early warning is crucial for protecting ecological security and controlling pollution in lakes and reservoirs. However, the traditional warning level may not provide accurate data for a specific area. Therefore, it is necessary to design an adaptive early warning threshold and identification system that conforms to the actual operating environment. This study monitored nine water quality parameters-water temperature (WT), pH, dissolved oxygen (DO), permanganate index (COD), chemical oxygen demand (COD), five-day biochemical oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (NH-N)-monthly from 11 sampling sites in the Danjiangkou Reservoir, i.e., the largest artificial lake in Asia, from 2017 to 2022. The reservoir was divided into three sub-areas by cluster analysis: Danku, Hanku, and Water intake. The Water Quality Index (WQI) was used for comprehensive spatiotemporal water quality evaluation, and a minimum WQI (WQI) model was developed using multiple linear regression. Finally, a water quality risk early-warning model was proposed based on frequency analysis, categorizing water quality into six levels. The findings reveal that the water quality in each area maintains at "good" or "excellent" levels during the study period. The average WQI values, from lowest to highest, are Hanku (75.44), Danku (78.78), and Water intake (79.07). This result shows that the water quality of Danjiangkou Reservoir has been maintained at a good level due to the pollution control and management of Chinese government after the operation of the Middle Route of the South-to-North Water Diversion Project of China. The WQI models for each area have different key parameters: WT, DO, TN, TP, and COD are common in all areas, whereas NH-N is included in both Hanku and Danku models. BOD and pH were unique to the Danku and Water intake models, respectively. TN and TP are identified as the key parameters affecting water quality safety in Danjiangkou Reservoir. The risk thresholds for TN and TP in Hanku are significantly higher than those in Danku and Water intake, indicating that the water quality in Hanku is the worst. These thresholds are dynamically revised through the early warning model as new data became available. The proposed risk assessment framework provides a robust tool for water quality risk early warning and offers a scientific and reliable reference for administrative departments to implement effective water environment risk prevention and management strategies.
水质预警对于保护生态安全以及控制湖泊和水库污染至关重要。然而，传统的预警级别可能无法为特定区域提供准确数据。因此，有必要设计一个符合实际运行环境的自适应预警阈值和识别系统。本研究于2017年至2022年期间，每月对亚洲最大的人工湖——丹江口水库的11个采样点的九个水质参数进行监测，这些参数包括水温（WT）、pH值、溶解氧（DO）、高锰酸盐指数（COD）、化学需氧量（COD）、五日生化需氧量（BOD）、总氮（TN）、总磷（TP）和氨氮（NH-N）。通过聚类分析将水库分为三个子区域：丹库、汉库和取水口。采用水质指数（WQI）进行综合时空水质评价，并利用多元线性回归建立了最小WQI（WQI）模型。最后，基于频率分析提出了水质风险预警模型，将水质分为六个等级。研究结果表明，在研究期间，各区域水质均保持在“良好”或“优秀”水平。WQI平均值由低到高依次为汉库（75.44）、丹库（78.78）和取水口（79.07）。这一结果表明，南水北调中线工程运行后，由于中国政府的污染控制和管理，丹江口水库水质一直保持在良好水平。各区域的WQI模型具有不同的关键参数：WT、DO、TN、TP和COD在所有区域都很常见，而NH-N包含在汉库和丹库模型中。BOD和pH值分别是丹库和取水口模型所特有的。TN和TP被确定为影响丹江口水库水质安全的关键参数。汉库中TN和TP的风险阈值明显高于丹库和取水口，表明汉库水质最差。随着新数据的获取，这些阈值通过预警模型进行动态修订。所提出的风险评估框架为水质风险预警提供了一个强大的工具，并为行政部门实施有效的水环境风险预防和管理策略提供了科学可靠的参考。
