Abstract
One of the most important water quality problems affecting lakes and reservoirs is eutrophication, which is caused by multiple physical and chemical factors. As a representative index of eutrophication, the concentration of chlorophyll-a has always been a key indicator monitored by environmental managers. The most influential factors on chlorophyll-a may be dependent on the different water quality patterns in lakes. In this study, data collected from 27 lakes in different provinces of China during 2009–2011 were analyzed. The self-organizing map (SOM) was first applied on the datasets and the lakes were classified into four clusters according to 24 water quality parameters. Comparison amongst the clusters revealed that Cluster I was the least polluted and at the lowest trophic level, while Cluster IV was the most polluted and at the highest trophic level. The genetic algorithm optimized back-propagation neural network (GA-BPNN) was applied to each lake cluster to select the most influential input variables for chlorophyll-a. The results of the four clusters showed that the performance of GA-BPNN was satisfied with nearly half of the input variables selected from the predictor pool. The selected factors varied for the lakes in different clusters, which indicates that the control for eutrophication should be separate for lakes in different provinces of one country.
Highlights
The deleterious proliferation of planktonic algae is a main cause of death of aquatic life and damage to aquatic ecosystems and water functions in lakes [1]
The objectives of the study were: (1) to classify the lakes into clusters with similar water quality characteristics based on the self-organizing map (SOM), and analyze the trophic levels of lakes in each cluster; (2) to select the specific variables that most influenced the growth of algae for each lake cluster by genetic algorithm optimized back-propagation neural network (GA-back propagation neural network (BPNN))
The performance of the genetic algorithm (GA)-BPNNs was assessed by two standard statistical performance criteria, including the coefficient of determination (R2)
Summary
The deleterious proliferation of planktonic algae is a main cause of death of aquatic life and damage to aquatic ecosystems and water functions in lakes [1]. Many factors have influenced the growth of phytoplankton, generally represented by the concentration of chlorophyll-a, such as physical variables, nutrients, organic substances, and metal ions [4,5]. The light conditions in lakes influence the growth of the plankton community, and the eutrophication caused by the high concentration of chlorophyll-a would impact light availability in lakes [6,7]. Excessive nitrogen and phosphorus inputs are important factors to shift lakes from oligotrophic to hypertrophic conditions [8], and lead to dramatic increases in harmful cyanobacteria blooms, which would create a serious threat to lake ecosystems [9]. The excessive amount of organic substances and metal ions in freshwaters generally originate from domestic sewage, urban run-off, industrial effluents and farm wastes, which are main causes of water pollution. Dissolved organic matter in lakes would absorb light and alter the light environment at depth, which would subsequently affect phytoplankton [10] and could be consumed directly or indirectly by aquatic life and have
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