Evolutionary data-driven modeling of Salento shallow aquifer response to rainfall

Data-driven techniques are among the most powerful approaches to model environmental phenomena. Evolutionary modelling constitutes and interesting approach able to combine the regressive feature of data-driven modelling with the power of evolutionary optimization. Here an evolutionary data-driven paradigm is used in order to model aquifer response to rainfall. The aquifer is shallow and located in south-east Apulia, south Italy, for which a long and reliable time series of monthly water table levels, measured in monitoring wells, are available. The identified models are consistent with past studies and with the hydrogeological characteristics of the aquifer, allowing for explicating the main rainfall components influencing the water table and the lag between rainfall and water table oscillations.