Optimization for Cost-Effectively Monitoring Ecological Effects of Water Diversion on the Urban Drinking Water Sources in a Large Eutrophic Lake

Due to the inputs of allochthonous pollutants and biological species from imported water, ecological effects of water diversion on urban drinking sources require long-term monitoring. Since spatial distributions of biological and environmental elements are always susceptible to water diversion, the monitoring specifications in water-receiving regions are always different from conventional ecological monitoring, especially in monitoring parameter selection and site distribution. To construct the method for selecting sensitive monitoring parameters and optimizing sites distribution in lakes, the large river-to-lake water diversion project, Water Diversion from Yangtze River to Lake Taihu in China, was taken as an example. The physicochemical properties and phytoplankton communities in the water-receiving Gonghu Bay and the referenced lake center were investigated and compared between the water diversion and non-diversion days in different seasons from 2013 to 2014. The comparative and collinearity analyses for selecting sensitive physicochemical parameters to water diversion, and the multidimensional scaling analysis based on the matrices of biological and sensitive physicochemical data, were integrated to optimize the monitoring in the water-receiving lake regions. Seven physicochemical parameters, including water temperature, pH, dissolved oxygen, total nitrogen, total phosphorus, chlorophyll a, and active silicate, were demonstrated to be sensitive to seasonal water diversion activities and selected for optimizing the site distribution and daily water quality monitoring. The nonmetric multidimensional scaling analysis results based on the data matrices of sensitive physicochemical parameters and phytoplankton communities were consistent for sites distribution optimization. For cost-effective monitoring, the sites distribution scheme could choose the optimizing results based on the Euclidean distance from 3.0 to 4.0 and the Bray-Curtis similarity from 40 to 60%. This scheme divided the Gonghu Bay into three water regions: the inflow river inlet, bay center, and bay mouth adjacent to the open water region. In each of the three regions, one representative site could be selected. If focusing on more details of each region, the standards with the Euclidean distance lower than 2.0 and the Bray-Curtis similarity higher than 60% should be considered. This optimization method provided an available way to fulfill the cost-effective long-term monitoring of urban drinking water sources influenced by water diversion projects.