Artificial Neural Networks (ANNs) have been successfully employed for predicting and forecasting groundwater levels up to some time steps ahead. In this paper, we present an application of feed forward neural networks (FFNs) for long period simulations of hourly groundwater levels in a coastal unconfined aquifer sited in the Lagoon of Venice, Italy. After initialising the model with groundwater...

background & aims of the study: heavy metals are one of the most important environmental pollutants which agricultural and industrial activities and urban development increased their entry rate to the underground resources. this study aimed to investigate the concentration of chromium, nickel and manganese in groundwater resources in asadabad plain. materials & methods: sampling of groundwater ...

excessive withdrawal of groundwater and reduced rainfall in recent years have caused the drawdown of groundwater table. therefore, it is necessary to manage it for preventing its damage. the present study was carried out to investigate the effect of increasing the irrigation efficiency on groundwater fluctuation on ajab-shir plain aquifer. the aquifer was simulated by using visual modflow 3.1 s...

The first comprehensive use of wavelet methods to identify non-stationary time-frequency relations between North Atlantic ocean-atmosphere teleconnection patterns and groundwater levels is described. Long-term hydrogeological time series from three boreholes within different aquifers across the UK are analysed to identify statistically significant wavelet coherence between the North Atlantic Os...