Groundwater hydrodynamic behaviours based on water table levels to identify natural and anthropic controlling factors in the Piedmont Plain (Italy).

Water table level monitoring and analysis are among the tools available to identify variations in the quantitative state of groundwater. Moreover, these levels highlight the response of groundwater to climate change and other global change drivers, including land use changes. In this study, water table level (37 monitoring wells) and rainfall (30 rain gauges) data analyses were performed in an alluvial unconfined aquifer in the Piedmont Plain (NW Italy) for the 2002-2017 period. The aim of this study was to identify possible trends in the time series and classify the groundwater hydrodynamic behaviours, as well as their spatial distributions and the main drivers of change in the plain. Moreover, two different sub-periods (2002-2008 and 2009-2017), which were identified with a change point analysis, were analysed to highlight possible variations in the groundwater hydrodynamic behaviours. The results of this study highlighted the lack of a trend in the rainfall time series, while a trend was detected for the water table. To explain this inconsistency, water table behaviours were analysed during the year, highlighting different groundwater hydrodynamic behaviours. Over time, the groundwater hydrodynamic behaviour generally showed the dependence of the water table level on rainfall occurrence. This correlation was also underscored by analysing the standardised anomalies of rainfall and groundwater levels. A different behaviour was observed in the paddy field areas, where the main driver of water level modification is the agricultural technique of rice cultivation. Furthermore, a reduction in the maximum water table level period was observed in 2009-2017 in this area. More specifically, the high water table period passes from 4 to 3 months, which could be the result of changes in irrigation methods. In this study, by analysing the present resource status, a first step is made to obtain future insights into flow dynamics and trends in storage.