Analysis of black water aggregation in Taihu Lake

Black water aggregation （BWA） in Taihu Lake is a disaster for the lake environment. It is a phenomenon resulting from water environmental deterioration and eutrophication caused by accumulation of pollutants in the lake, according to research on the water quality, pollutants of BWA, and occurrence mechanisms of BWA. Dead algae are the material base of BWA, the polluted sediment is an important factor for the formation of BWA, and hydrological and meteorological conditions such as sun light, air temperature, wind speed, and water flow are the other factors that may lead to the formation of BWA. Thioether substances such as dimethyl trisulfide are the representative pollutants of BWA. Parameters such as chlorophyll-a, DO, pH, and water temperature are sensitive indicators of BWA. Measures such as algae collection, ecological dredging, pollution control, and water diversion from the Yangtze River to the lake, are effective, and strengthening aeration is an emergency measure to control BWA.

Water quality monitoring and evaluation using remote sensing techniques in China:a systematic review

Introduction:The application of remote-sensing techniques for water quality assessment has become increasingly popular in China.However,existing reviews are often limited to qualitative description and are quite fragmented.Outcomes:We conducted a quantitative systematic review to display current research status and identify the existing challenges and future directions.Our review revealed that the application of remote-sensing techniques in water quality research has expanded dramatically in China,but the spatial distribution is quite uneven.Second,the ground object spectrometer is the most widely applied data source.Water color indicators such as chlorophyll a and suspended solid are the most widely investigated in China.Third,semiempirical method is the most commonly used inversion method.Existing studies rarely considered the anthropogenic factors,which limited the model robustness and its application in humandominated aquatic ecosystems.Discussion and Conclusion:We concluded that,in the past several decades,China has made notable progresses in monitoring and evaluation of water quality using the remote-sensing techniques(especially in inland lakes).We proposed that further improvements would be needed in terms of temporal and spatial coverage,indicator list,the incorporation of human–nature interactions,inversion accuracy,and model generalization.

Is urban development an urban river killer? A case study of Yongding Diversion Channel in Beijing, China

The high population and concrete environment alter urban areas by changing temperature, rainfall runoff, and water resource utilization activities. This study was conducted to investigate the water quality features of the Yongding Diversion Channel in Beijing, China, and its relationship with rainfall and urban development. Monthly water quality data were obtained from April to October of 2004 at monitoring sites of Sanjiadian, Gaojing, Luodaozhuang, and Yuyuangtan. The monthly water quality grades from 2007 to 2011 were also investigated and compared with those of other rivers. Dissolved oxygen and pH showed greater decreases after one or two moderate rainfall events than several light rainfall events. The potassium permanganate index （CODMn）, ammonia nitrogen （NH3-N） and total phosphorus （TP） increased more after several light rainfall events than after one or two moderate or heavy rainfall events. Pollutant concentrations （CODMn, NH3-N, TP） in downstream regions showed greater changes than those in upstream areas after heavy rainfall events. Intense human activities around the channel greatly influenced the water quality of the channel in rainy season because of runoff pollution; however, heavy rainfall had a strong dilution effect on the pollutant concentrations in rivers. Overall, urban development has obviously deteriorated the water quality of the Yongding Diversion Channel as indicated by an increase in the water quality index from 3.22 in 2008 to 4.55 in 2010. The Pearson correlation between monthly rainfall and water quality indices from 2007 to 2011 ranged from 0.1286 to 0.6968, generally becoming weaker as rainfall and rainfall runoff became more random and extreme.