Combining Artificial Neural Network and Driver–Pressure–State–Impact–Response Approach for Evaluating a Mediterranean Lake

The main objective of this research was to evaluate the surface water system Lake Vegoritida (Region Central Macedonia, Greece). Driver–Pressure–State–Impact–Response (DPSIR) methodological approach used. analysis includes data from three (3) stations monitoring point source pollution and recording most critical quality measurement parameters in a time series 1983 1997. will contribute used investigate, identify, possible sources chemical ecological changes recorded lake. artificial neural network (ANN) is valuable tool for making predictions based on set. findings highlighted increased concentration nutrients that presence eutrophic conditions, while their seasonal variability mainly due factors, such as level fluctuations biological processes above, combined with biotic indicators factors alongside reduction biodiversity, indicated only resistant species survive, confirming previous finding. In Greece, systematic reporting programs have recently been implemented, ECOFRAME scheme guidelines proposed by “Intercalibration Group Mediterranean Lakes”. status could be classified “High”, “High Good”, Poor”, respectively, overall assessment tends change poor conditions. actions required at an early stage concern planning sustainable management land uses pollution, well applied quantities agrochemicals cultivated study area.