Abstract
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.
Highlights
Water diversion projects, as popular engineering projects for water supply and environmental improvement, have been implemented in many countries for over several decades (Hu et al, 2008)
Since the global lake eutrophication problem became prominent in the 1960s, water diversion has been taken as an efficient way to improve hydro-environments and to deal with cyanobacterial blooms in drinking water sources in many eutrophic lakes such as Lake Green in the USA (Oglesby, 1968), Lake Veluwe in the Netherlands (Jagtman et al, 1992), and others (Lake Taihu, Lake Chaohu, Lake Dianchi, Lake Baiyangdian, etc.) in China (Hu et al, 2008; Zhai et al, 2010; Li et al, 2011, 2013; Zhang et al, 2016; Chen et al, 2017; Cao et al, 2018; Dai et al, 2018, 2020; Qu et al, 2020; Zhang et al, 2021)
The average contents of CODMn and chlorophyll a (Chl a) in Gonghu Bay were more influenced by the growth of phytoplankton in Gonghu Bay, but the average content of Chl a was lower on the water diversion days than that on the non-diversion days in autumn (Figure 3)
Summary
As popular engineering projects for water supply and environmental improvement, have been implemented in many countries for over several decades (Hu et al, 2008). To reveal the ecological effects of water diversion projects on drinking water sources in lakes, long-term ecological monitoring work is necessary. The ecological monitoring procedure for rivers and lakes always has standard specifications for sampling sites, sampling time, monitoring parameters, and other procedures (Wang et al, 2013). Due to the mixing effects of water diversion in the water-receiving regions, the original spatial differences in concentrations of some physicochemical parameters among the adjacent sites during the non-diversion period might be eliminated by the water diversion (Dai et al, 2020). The normal specification of lake ecological monitoring always has many physicochemical parameters (Wang et al, 2013), some of which may not be sensitive to the water diversion. To save monitoring costs, sensitive physicochemical parameters should be selected for the long-term monitoring of the ecological effects induced by water diversion
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