We studied and mapped the ground deformation in Catania plain in Italy using artificial intelligence techniques applied to displacement time series of Sentinel-1 satellites. We estimated the dates when the velocities of displacement time series changed. We observed significant land subsidence in the south part of Catania Airport and showed how the precipitation cycles and trend change had a potential impact on ground deformation.

To ensure the effective and sustainable operation of water exploitation projects, it is imperative to select appropriate extraction technologies.

Our study addresses the challenges of costly groundwater investigation in the catchments by integrating in-situ groundwater data with terrain classification. This approach allows us to identify terrain-based groundwater potential and characterize groundwater levels. We aim for our findings to guide ongoing researchers in planning more detailed studies within their respective areas. These insights contribute to sustainable groundwater management and resource planning in similar topographies.

The impacts of climate change have become increasingly apparent, even in Slovakia. To monitor and issue drought warnings, we conduct analyses and prepare documents. Our analysis, covering the last decade (2013-2022) and 2022, provides a map of surface and groundwater abstractions throughout Slovakia, categorized by sector. This comprehensive approach enables us to better understand and manage our water resources effectively.

This study proposes an offline machine-learning (ML) algorithm that ranks candidate training points by scoring them based on their distance to the closest training point and on the local gradient of the surrogate estimate and then choosing the highest-rank point. The effectiveness of this method is confirmed in developing surrogates to solve a two-objective groundwater pumping optimization problem formulated on a three-dimensional island aquifer.

Water is historically abundant in Northern Italy, but it was hit by a major meteorological drought recently. In this study, a possible adaptation measure to these extreme events is proposed and evaluated: the flooding of fields during periods of water abundance to recharge aquifers. Results show that the measure has a considerable potential in infiltrating high volumes of water. This work only shows the first results, more data and improved numerical models will be achieved in the next years.

In Colombia there are many areas with little or no hydrometeorological information that would allow for adequate water resource management, especially in times of low supply of the resource. In this work, several modeling techniques are implemented to generate data grids of meteorological variables that allow for reliable calculations of the potential recharge of aquifers, controlling uncertainties.

As groundwater serves as the principal source of water worldwide, its quality is of paramount importance. In this study, the evolution of groundwater quality in California is assessed using the Water Quality Index & Weighted Index Overlay Analysis methods. Several water quality parameters are considered for the analysis, and the results from both methods are compared. The study shows that in most parts of California, groundwater quality is potable, as per WHO guidelines, except in a few places. 

We examined how water quality in aquifers and streams varies along the Besòs catchment, and changes in streams during wet and dry periods. Analysis of water quality data (2013-2023) in open databases shows nutrients and salinity increase towards the outlet, and more markedly during dry periods. Since such dry periods may become more frequent with climate change in this Mediterranean basin, this highlights the importance of controlling pollution sources affecting water quality and availability.