The increasing occurrence of widespread drought phenomena is a global environmental emergency, especially for the effects of ongoing climate change on groundwater availability. Dry years and extreme temperatures are common drivers of current climate impacts all over the world, including, for example, the freshwater supply for drinking and agriculture purposes, ecosystems, forestry, health, etc. In this frame, to ensure temporal water availability in water-stressed areas, sustainable groundwater management is an increasing challenge. Most groundwater in the South-East Latium Region, Central Italy, as in the whole Apennine Mountains chain, is stored in karst aquifers. In this area important water resources are present, but even here in the last decades they are affected by groundwater depletion as a consequence of occurring drought events, the upward trend in the global average temperature and the increase in groundwater extraction. Due to the lack of flow rate data of springs in many areas of Italy, spring response modeling could be a useful tool for supporting proper water resource management. Several research studies proposed methods based on relationships between spring discharges and rainfall data. The goal of this paper is to propose a simple linear model, based on rainfall-discharge cross correlations, in order to be able to simulate the effects of variation in rainfall on water resource connected Capodacqua di Spigno Spring minimum discharge. The results obtained using the developed model has been compared to an existing method that uses the Standard Precipitation Index (SPI) for the estimation of the minimum annual spring discharge.

Karst aquifer recharge areas are usually difficult to identify because of the complexity of these aquifers’ characteristics. On the other hand, their identification is very important in the aim of protecting the groundwater resources that these aquifers host. Regarding this topic, this paper presents an approach aimed at identifying karst aquifer recharge areas by the application of oxygen-18 and deuterium isotopes composition of groundwater coupled with hydrological features. Oxygen-18 and deuterium isotope composition of Capodacqua di Spigno Spring, in the South of the Latium Region, has been applied with rainfall and discharge values related to the feeding aquifer of this spring. As δ¹⁸O and δ²H values of groundwater samples are natural tracers of the recharge area’s elevation, we propose a model, based on the distribution of the basin surfaces involved as recharge areas, in relation to elevations. The model estimates, for any discharge value, the percentage of the topographic area involved in the aquifer recharge. The setting up of this simulated distribution is supported by a Weibull cumulative probability function. The results show that the measured discharges increase as larger areas with lower elevations are involved in the recharge process.

The identification of recharge areas in karst aquifers allows us to perform sustainable management of these groundwater resources. Stable isotopes (δ¹⁸O and δ²H) have been largely used to provide information about recharge elevation in many mountainous regions. In this paper, an improved version of a recent “isotope-driven model”, for the identification of recharge areas, was applied to Capodacqua di Spigno Spring (south of the Latium region). The model upgrade consists of a preliminary check procedure to estimate the degree of influence of the rainfall’s isotopic variability on the spring water. This additional procedure gives us an indication of the reliability of the model and its applicability conditions. Moreover, the dataset of the spring was updated to analyze the degree of reliability of the isotope-driven model. The purpose of this study was to combine the previously mentioned isotope-driven model with hydrogeological tools. A quantitative study of the basin, based on the estimation of the average monthly infiltration volume, was performed by using the inverse hydrogeological water budget. In this way, the qualitative model for the recharge areas’ estimation was validated by a quantitative hydrogeological tool. Both models show that, for karst mountain basins, the recharge areas decrease as the average recharge elevations increase, including areas at high altitudes.

In the last decades, climate change has led to increasingly frequent drought events within the Mediterranean area, creating an urgent need of a more sustainable management of groundwater resources exploited for drinking and agricultural purposes. One of the most challenging issues is to provide reliable simulations and forecasts of karst spring discharges, whose reduced information, as well as the hydrological processes involving their feeding aquifers, is often a big issue for water service managers and researchers. In order to plan a sustainable water resource exploitation that could face future shortages, the groundwater availability should be assessed by continuously monitoring spring discharge during the hydrological year, using collected data to better understand the past behaviour and, possibly, forecast the future one in case of severe droughts. The aim of this paper is to understand the factors that govern different spring discharge patterns according to rainfall inputs and to present a model, based on artificial neural network (ANN) data training and cross-correlation analyses, to evaluate the discharge of some karst spring in the Umbria region (Central Italy). The model used is a fully connected neural network (FCNN) and has been used both for filling gaps in the spring discharge time series and for simulating the response of six springs to rainfall seasonal patterns from a 20-year continuous daily record, collected and provided by the Regional Environmental Protection Agency (ARPA) of the Umbria region.

Bracciano Lake is one of the major water bodies of Lazio region and the eighth lake in Italy by area. Similarly to other water bodies located on the Tyrrhenian side of the Italian Peninsula, Bracciano Lake has a volcanic origin. This water body is a strategic resource for both the emergency and ordinary water supply of Rome megacity, thanks to the short distance (about 30 km). During the last years, the concurrence of climate change and anthropogenic activities led to important water level drops of the lake: the last and worst in 2017, when the lake faced the most important water crisis of its entire history, with a critical impact on the ecological system and the consequent interruption of water supply. This paper, using the inverse hydrogeological water budget (HWB) method in a GIS environment, aims to define the water budget of Bracciano Lake on a 15-year time series (2008–2022), providing a framework of climate change and human impacts on lake water levels. The outputs have been used for the simulation of lake water levels during the same period, with a focus on the drought of 2017. The variation between simulated and observed level is, on average, 2 cm and in any case never more than 28 cm. Results show the fragile balance between inputs and outputs, highlighting the need for sustainable management of both surface water and groundwater withdrawals from the surrounding aquifer.

This paper presents the results of a groundwater quality assessment carried out in the karst coastal region of the West Aurunci Mountains (Central Italy). 55 spring and 18 well water samples, collected from 2016 to 2018, were analysed to study the main processes controlling the hydrogeochemical evolution and groundwater quality properties. In the study area, groundwater samples are mostly characterized by a Ca-HCO₃ facies, indicating that the groundwater hydrogeochemical evolution is mainly controlled by the carbonate mineral dissolution/precipitation. The cationic and anionic concentrations confirm that groundwater samples belong to the order of Ca2+>Mg2+>Na+>K+ and HCO3−>Cl−>SO42−, respectively. Well water samples show, over time, an increasing mineralization with respect to the spring water samples. In more detail, the enrichment of Ca²⁺, Na⁺, and Cl^- in well water samples is mainly due to the dissolution of calcite, dolomite, and halite minerals and secondly to a probable ion exchange related to seawater intrusion. Seawater intrusion, probably affecting the chemical composition of well water samples, was studied using ionic ratios, graphical approaches, and specific indices, such as the BEX index. Results suggest that carbonate weathering, ion exchange, and seawater intrusion in this karst coastal region are the major factors controlling groundwater geochemistry. This study shows that groundwater quality assessment, based on hydrogeochemical investigation techniques, has been a useful tool to characterize and model carbonate aquifers in Central Italy, with the aim of achieving proper management and protection of these important water resources.