Evaluation, prediction, and protection of water quality in Danjiangkou Reservoir, China

The water quality in the Danjiangkou Reservoir has attracted considerable attention from the Chinese public and government since the announcement of the Middle Route of the South to North Water Diversion Project （SNWDP）, which commenced transferring water in 2014. Integrated research on the evaluation, prediction, and protection of water quality in the Danjiangkou Reservoir was carried out in this study in order to improve environmental management. Based on 120 water samples, wherein 17 water quality indices were measured at 20 monitoring sites, a single factor evaluation method was used to evaluate the current status of water quality. The results show that the main indices influencing the water quality in the Danjiangkou Reservoir are total phosphorus （TP）, permanganate index （CODM,）, dissolved oxygen （DO）, and five-day biochemical oxygen demand （BODs）, and the concentrations of TP, BODs, ammonia nitrogen （NH3--N）, CODM,, DO, and anionic surfactant （Surfa） do not reach the specified standard levels in the tributaries. Seasonal Mann--Kendall tests indicated that the CODMn concentration shows a highly significant increasing trend, and the TP concentration shows a significant increasing trend in the Danjiangkou Reservoir. The distribution of the main water quality indices in the Danjiangkou Reservoir was predicted using a two-dimensional water quality numerical model, and showed that the sphere of influence from the tributaries can spread across half of the Han Reservoir if the pollutants are not controlled. Cluster analysis （CA） results suggest that the Shending River is heavily polluted, that the Jianghe, Sihe, and Jianhe rivers are moderately polluted, and that they should be the focus of environmental remediation.

Spatial and Temporal Variation and Trend Analysis of Water Quality in Large Reservoirs in Ji’an City

Based on the water quality monitoring data of 5 large reservoirs in Ji’an City,Jiangxi Province from 2015-2021,the temporal and spatial variation characteristics and trends of water quality of the reservoirs were analyzed by single-factor evaluation method and seasonal Kendall test to evaluate the trophic status of the reservoirs and explore the influencing factors of characteristic pollutants.The results showed that:①the water quality of the reservoirs was good and could meet the water needs of various functions;②the water quality of the reservoirs had generally changed from bad to good in recent years,indicating that the implementation of“river chief system”has achieved certain results;③Kendall test analysis showed that,except for individual projects which showed an upward trend in water quality,other projects showed no obvious change trend or downward trend,indicating that the water quality of the reservoirs is indeed improving;④the causes of water pollution in reservoir area were further analyzed by exploring the natural and human factors of the characteristic pollutant total phosphorus.It is recommended to strengthen supervision in the later stage to control point and non-point source pollution.

Application of IGM(0,N)Model to Simulate Trends in Estuarine Water Quality

The water quality of rivers flowing into lakes is a reflection of the regional environment and significantly contributes to the nutrient levels of the lake.Based on multi-year monitoring data of the estuarine water quality of the Zi River which flows into the Dongting Lake,single factor analysis was performed for the dissolved oxygen,nitrogen ammonia(NH3-N),chemical oxygen demand,total phosphorus,permanganate index,and biochemical oxygen demand.The analysis indicated that the estuarine water quality class was dependent on the NH3-N level.The NH3-N trend of the Zi River was then simulated using an improved grey model IGM(0,N)based on a grey correlation analysis.The IGM(0,N)model produced a smaller average relative error and a more accurate prediction compared with a multiple regression model,thus validating the use of the IGM(0,N)model as a suitable method to simulate the estuarine water quality with a complex multi-factor system.