Abstract

This paper concerns the simulation of the water table elevation in shallow unconfined aquifers where infiltration is assumed as the main mechanism of recharge. The main aim is providing a reliable tool for groundwater management, that satisfies water supply managers. Such a tool is a candidate as a physically based alternative to the use of empirical methods or General Circulation Models. It is based on the use of two widely available sets of data: the water table elevation measurements and soil moisture time-series. In fact, the former are usually provided by government agencies on public websites whereas the latter are included in the atmospheric global datasets (reanalysis). It is worth noting that data from reanalysis are accessible to any citizen and organization around the world on a open access basis (e.g., Copernicus). In the proposed method, the measured water table elevations are correlated quantitatively with the water fluxes towards the aquifer evaluated using the soil moisture data from ERA5 reanalysis (provided by ECMWF) within a Richard equation-based approach. The analysis is executed using data from the Umbria region (Italy) on both a daily and monthly scale. In fact, these are the time intervals of interest for a proper management of groundwater resources. The proposed relationships include both a logarithmic and linear term and point out the possible different regimes of the shallow aquifers with regard to the recharge due to infiltration. These different mechanisms reflect in the different role played by the water fluxes towards the aquifer in terms of water table elevation changes according to the considered time scale.

Given the regional surface network of the Umbria region, a mountainous area located in central Italy, the observed hourly temperature time series from 2010 to 2017 were analysed by applying basic and extended quality control procedures following World Meteorological Organization (WMO) standards. The validation procedure consisted of automatic quality control, producing validated data with metadata subsequently recorded in the NetCDF format. After these controls, data were checked manually and an extended procedure was applied to reconstruct the temperature time series for missing data. The spatiotemporal method used to reconstruct the data was a linear interpolation for 1 hr gaps and the empirical orthogonal function (EOF) algorithm for gaps ≥ 2 hr. The introduction of a complete and homogeneous data set of hourly reanalysis ERA5 (from the European Center for Medium-Range Weather Forecasts-ECMWF) allowed for the reconstruction of the longest gaps with statistical and physical consistency. The final product of the study is a continuous station time series of hourly temperatures that will be available to the public by the end of 2020; a daily version of the original time series is already available on the regional website.

In the EFFS Project, an attempt has been made to develop a general framework to study the predictability of severe convective rainfall events in the presence of orography. Convective activity is embedded in orographic rainfall and can be thought as the result of several physical mechanisms. Quantifying its variability on selected area and time scales requires choosing the best physical representation of the rainfall variability on these scales. The main goal was (i) to formulate a meaningful set of experiments to compute the oscillation of variance due to convection inside model forecasts in the presence of orography and (ii) to give a statistical measure of it that might be of value in the operational use of atmospheric data. The study has been limited to atmospheric scales that span the atmosphere from 2 to 200 km and has been focused on extreme events with deep convection. Suitable measures of the changing of convection in the presence of orography have been related to the physical properties of the rainfall environment. Preliminary results for the statistical variability of the convective field are presented.

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