Estimating the spatial variability of hydraulic conductivity K in natural aquifers is important for predicting the transport of dissolved compounds. Especially in the nonreactive case, the plume evolution is mainly controlled by the heterogeneity of K. At the local scale, the spatial distribution of K can be inferred by combining the Lagrangian formulation of the transport with a Kalman-filter-based technique and assimilating a sequence of time-lapse concentration C measurements, which, for example, can be evaluated on site through the application of a geophysical method. The objective of this work is to compare the ensemble Kalman filter (EnKF) and the ensemble smoother (ES) capabilities to retrieve the hydraulic conductivity spatial distribution in a groundwater flow and transport modeling framework. The application refers to a two-dimensional synthetic aquifer in which a tracer test is simulated. Moreover, since Kalman-filter-based methods are optimal only if each of the involved variables fit to a Gaussian probability density function (pdf) and since this condition may not be met by some of the flow and transport state variables, issues related to the non-Gaussianity of the variables are analyzed and different transformation of the pdfs are considered in order to evaluate their influence on the performance of the methods. The results show that the EnKF reproduces with good accuracy the hydraulic conductivity field, outperforming the ES regardless of the pdf of the concentrations.

Seawater intrusion in coastal aquifers is a worldwide problem exacerbated by aquifer overexploitation and climate changes. To limit the deterioration of water quality caused by saline intrusion, research studies are needed to identify and assess the performance of possible countermeasures, e.g., underground barriers. Within this context, numerical models are fundamental to fully understand the process and for evaluating the effectiveness of the proposed solutions to contain the saltwater wedge; on the other hand, they are typically affected by uncertainty on hydrogeological parameters, as well as initial and boundary conditions. Data assimilation methods such as the ensemble Kalman filter (EnKF) represent promising tools that can reduce such uncertainties. Here, we present an application of the EnKF to the numerical modeling of a laboratory experiment where seawater intrusion was reproduced in a specifically designed sandbox and continuously monitored with electrical resistivity tomography (ERT). Combining EnKF and the SUTRA model for the simulation of density-dependent flow and transport in porous media, we assimilated the collected ERT data by means of joint and sequential assimilation approaches. In the joint approach, raw ERT data (electrical resistances) are assimilated to update both salt concentration and soil parameters, without the need for an electrical inversion. In the sequential approach, we assimilated electrical conductivities computed from a previously performed electrical inversion. Within both approaches, we suggest dual-step update strategies to minimize the effects of spurious correlations in parameter estimation. The results show that, in both cases, ERT data assimilation can reduce the uncertainty not only on the system state in terms of salt concentration, but also on the most relevant soil parameters, i.e., saturated hydraulic conductivity and longitudinal dispersivity. However, the sequential approach is more prone to filter inbreeding due to the large number of observations assimilated compared to the ensemble size.

Salt-water intrusion (SWI) is a worldwide problem increasingly affecting coastal aquifers, exacerbated by climate changes and growing demand of fresh-water. Therefore, research on this topic using both physical and numerical modeling has been intensified, aiming to achieve better predictions of the salt-water wedge evolution and to design suitable countermeasures to its negative effects. This work presents a laboratory facility designed to conduct SWI experiments that can be used as benchmarks for numerical models. To this end, the laboratory facility has been designed to limit errors and provide redundant measurements of hydraulic heads and discharged flow rates. Moreover, the size of the facility allows us to monitor the salt-water wedge evolution by a specifically designed electrical resistivity tomography (ERT) monitoring system. To demonstrate the capabilities of the laboratory facility, we carried out a simple 36-h long SWI experiment in a homogeneous porous medium: during the initial 24 h the salt-water wedge evolved without any external forcing, while in the last 12 h, fresh-water was pumped out to simulate aquifer exploitation. The experiment was monitored through ERT and photos of the salt-water wedge collected at regular time intervals. The SUTRA code was used to reproduce the experimental results, by calibrating only the dispersivities. The ERT results show a good correlation with simulated concentrations between the borehole electrodes, the most sensitive zone of the monitored area, demonstrating that ERT can be used for laboratory evaluations of the salt-water evolution. Overall, the agreement between observed data, numerical simulations, and ERT results demonstrates that the proposed laboratory facility can provide valuable benchmarks for future studies of SWI, even in more complex settings.

In the Treviso province (Veneto, Italy) most of the drinking water (nearly 60 %) is supplied from wells located in the northern piedmont area, where agricultural activities are developed using chemical plant protection products (chemical PPPs). In this area the aquifer interested by the groundwater extraction is unconfined, making the subsurface water resource intrinsically vulnerable to any PPP or PPP residue (metabolite) leaching from the agricultural soil to the groundwater table, and raising concerns about the consequences of a possible groundwater contamination on the health of the local inhabitants.To protect the drinking water resource, in 2019 the Veneto Region provided a technical framework for the definition of the wellhead protection areas (WHPAs, Resolution 1621) in accordance with the EU directives 2000/60 and 2006/118, related to the establishment of safeguard zones for the water bodies used for drinking water supply. In the WHPAs the use of PPPs is only allowed when accounting for the vulnerability of the groundwater and the well extracting water for human consumption. To define the vulnerability of wells supplying drinking water, a procedure that considers the tridimensional behavior of a possible contaminant is suggested, taking into account the mobility of the chemical species across the vadose zone, the total amount of PPPs applied on the soil, and combining the probability of contaminant infiltration with the groundwater pathlines reaching the well.An application has been developed in the piedmont area of the Treviso province where a geospatial analysis of the vine-specific PPPs sales data identified over 30 WHPAs potentially affected by the PPPs use. The 3D vulnerability assessment couples the position of the vulnerable WHPAs retrieved from the geospatial analysis with 1) the data related to the infiltration capacity of agricultural and not-agricultural unsaturated soils in the piedmont area of the Treviso province, 2) the mobility of the vine-specific PPPs, and 3) the groundwater pathlines in the superficial phreatic aquifer obtained by physically-based numerical modeling.This research has been funded by the contribution from the UNI-IMPRESA 2021 joint research project (Centre of Hydrology ‘Dino Tonini’ - University of Padua, Alto Trevigiano Servizi Spa, Piave Servizi Spa): Subsurface Water quality and Agricultural pracTices monitoring 2 (SWAT-2).