Abstract
AbstractPrediction of the leachate pollutants is of prime importance to detect nearby water resources pollution. In this way, electrical conductivity (EC) as a physicochemical water pollution parameter with the possibility of portable measurement can be used as an indicator of the leachate quality. For this purpose, two lysimeter experiments were carried out simultaneously to simulate the Tychy-Urbanowice landfills. During the tests, the EC, waste temperature, and the moisture data were measured by the installed sensors. This study aims to develop an artificial neural network (ANN) model to determine the parameters affecting the EC value and subsequently, predict the EC parameter of the lysimeter employing the developed ANN model. The performance of the model was evaluated by determination coefficient (DC) as well as root mean square error (RMSE). The study results declared that the moisture content of the lysimeters had a significant contribution to the EC value prediction.KeywordsLandfill leachateLysimeterElectrical conductivityArtificial Neural Network (ANN) Introduction
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