Abstract
Lake Pamvotis (Greece) is a shallow hypereutrophic lake with a natural tendency to eutrophication. Several restoration measures were applied, but with no long-term success. To examine the causes for this an Artificial Neural Network (ANN) was created in order to simulate the chlorophyll-a (Chl-a) levels and to investigate the role of the associated environmental parameters. The ANN managed to simulate with good correlation the simulated Chl-a and can be considered as a reliable predictor. The relative importance of the environmental parameters to the simulated Chl-a was calculated with the use of the “Partial Derivatives” (“PaD”) sensitivity method. The water temperature (WT) and soluble reactive phosphorus (SRP) had the highest relative importance, with values of 50% and 17%, respectively. The synergistic effect of the paired parameters was calculated with the use of the “PaD2” algorithm. The SRP-WT paired parameter was the most influential, with a relative contribution of 22%. The ANN showed that Lake Pamvotis is prone to suffer the effects of climatic change, because of the major contribution of WT. The ANN also revealed that combined nutrients reduction would improve water quality status. The ANN findings can act as an advisory tool regarding any restoration efforts.
Highlights
Over the past few decades eutrophication has emerged as a serious problem affecting the water quality of many lakes worldwide, mainly as a result of increased nutrient loadings related to human activities [1]
The relative importance of input variables to the Artificial Neural Network (ANN) was found to have the following order of contribution according the results of the “Partial Derivatives (PaD)” method: water temperature (WT), soluble reactive phosphorus (SRP), Secchi disk (SD), pH, DO, EC, dissolved inorganic inorganic nitrogen nitrogen (DIN) (Figure 2)
Input variables to the ANN was found to have the following order of contribution according the results of the “PaD” method: WT, SRP, SD, pH, DO, EC, DIN (Figure 2)
Summary
Over the past few decades eutrophication has emerged as a serious problem affecting the water quality of many lakes worldwide, mainly as a result of increased nutrient loadings related to human activities [1]. Eutrophic conditions in a water column may lead to a Harmful Algal Bloom (HAB) event [2]. In the case of toxic HABs events, toxin-producing algal species are involved. In freshwater lakes most of these toxic species are cyanobacteria, formally called blue-green algae [4]. Because of their toxin production, cyanobacteria have been characterized as potential key hazardous pollutants, by the European Water Framework Directive (2000) (2000/60/EC) [5]. Aquatic organisms may suffer from poisoning because of cyanotoxins released from cyanobacteria when a HAB occurs [6]
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