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Urbanization, worldwide, led to progressive increase in the use of the subsurface. Therefore, interactions between groundwater and underground infrastructures (UIs) (i.e. subway lines, public and private car parks) come to attention. As a results, episodes of infiltrations and corrosion can occur for these subsurface elements. In this sense, numerical models are widely applied to manage these issues. Infiltration episodes were documented over the years also for the city of Milan. In the framework of a further subsurface development to be achieved by 2030, the Plan of Government of the Territory has already defined the construction of new UIs. Hence, proper tools must be adopted to support stakeholders in urban planning, also considering these hydrogeologic aspects. Thus, a steady-state numerical model, calibrated against a groundwater maximum condition, was developed for the western portion of Milan metropolitan city to simulate the UIs (i.e. subway lines and public car parks) and quantify their infiltrations. MODFLOW-USG was used, combining the Wall (HFB) and DRN packages to model the UIs. Model cells range from 100 up to 6.25 meters close to the UIs. A total of 18 layers modelled 100 – 120 meters of depth, with the UIs falling inside the first 8 layers (25 meters of depth). Different scenarios were simulated to cope with the wall conductance uncertainty of non-waterproofed subway lines, testing respectively: intact walls, a progressive saturation over time (i.e. a prolonged interaction with groundwater), and leaky walls. Results pointed out those UIs suffering major groundwater infiltrations that were historically identified as critical in previous studies (i.e. submerged by the water table). Particularly, this occurred for the western branch of subway line M1 (i.e. Bisceglie station), and for the surroundings of Sant’Agostino (subway line M2), showing a maximum infiltration of 5.29 L/d. The use of MODFLOW-USG was pivotal, as the HFB package was used to simulate n

Over the past few decades, groundwater quality monitoring networks have grown, and considerable time series of quality data are currently available. Hence, a research effort is required to investigate novel methods for exploiting groundwater quality time series. In this work, time series of groundwater pollution data are exploited with the aim of developing data-driven monitoring strategies, and early warning systems to support groundwater resource management for drinking water purposes. The research area is Brescia municipality (N Italy): an urban area with a complex hydrogeological context and numerous superimposing historical pollution sources. The dataset, provided by A2A Ciclo Idrico Spa, consisted in concentrations of Tetrachloroethylene (PCE), Trichloroethylene (TCE) and Cr(VI) on raw water before any potabilization treatment, from 2009 to 2020 for 68 wells and 16 springs. Time series exploratory analysis and time series cluster analysis were performed on groundwater pollution data, to identify groups of wells with homogeneous responses to anthropogenic inputs and highlight critical situations. The exploratory analysis was performed through Mann-Kendall test and Sen's slope estimator for the trend identification and quantification. A multivariate time-series clustering was performed on PCE and TCE, with the Dynamic Time Warping method. The clustering revealed 3 clusters linked to diffuse background contamination and 7 clusters linked to discrete hotspots, distinguished by distinct time profiles. Similarly, Cr(VI) data were subjected to a univariate time series cluster analysis, which revealed 3 background clusters and 7 hotspots, including 4 singletons. Based on the clustering outputs, data-driven monitoring strategies and early warning systems were designed for each group of wells. For the clusters associated with diffuse background contaminations and those with constant trends, the 95th percentile was used to calculate trigger levels, which represent future

Over the past 30 years, groundwater (GW) age derivation has attracted attention in researchers and professionals to overcome quality-related challenges in the management of aquifer systems. GW ages can be determined following either hydraulic-based techniques or isotope-based approaches. By the term age modelling, instead, reference is made to developed methods that qualitatively couple hydrodynamics with isotope-based ages in order to reduce the uncertainties involved. Here we present an age modelling application to the shallow alluvial aquifer in the Po River Basin. We used the 3H/3Hetri method to assess the aquifer renewability in a portion of the plain where the extremely variable recharge contributions and the intrinsic variability in aquifer geometry, make sometimes water management arduous. Results from 44 wells showed 3H activities ranging from 0.52 to 5.02 T.U.. To use 3He for age computations, the fraction produced by 3H decay (3Hetri) must be separated by other sources: dissolved He in solubility equilibrium with the atmosphere (Heeq), excess air trapped at the vadose zone (Heea) or 3He produced from 6Li (3Herad). The 3He/4He ratios normalized to that of the atmosphere range from 0.30 to 3.25 revealing the dominant presence of 3Hetri with a minor contribution of Herad. The slight Herad contribution to the Hetot identifies older GWs, reaching values of 60±20yr, detected near the piedmont and in the higher plain. The downstream middle plain, instead, revealed younger ages of about 24±2yr. Chronometers also unraveled mixing processes, detailing older GWs in the higher plain as the result of a young component containing 3H and another older than 70 years mostly 3H-free. In the middle plain, oppositely, mixing counts at least two components where the youngest portraits shorter flowpaths able to lower background aquifer age values, particularly where return flow due to intensive irrigation occurs, thus acting as a young recharge component to the aquifer. The ag

In recent years, a strong interaction between groundwater and underground infrastructures has emerged, determined by a significant employment of subsurface in urban planning. Numerical models are essential to manage this problem, but their construction is time and cost consuming. Groundwater time-series analysis can represent a valid complementary approach, as an extensive approximation of the geological and boundary conditions is not required, even if providing insights into the hydrogeologic system. Thus, for Milan city, in order to identify the potential variables affecting the water table levels of 95 monitoring wells (MWs) of the shallow aquifer, occupied by numerous underground infrastructures, data-driven techniques were adopted to analyse groundwater time-series. The study covered the period 2005-2019. Four management areas (MAs), possibly representing future territorial units with specific groundwater management policies, have been identified. As for underground infrastructures, public car parks have been classified in a) not submerged, b) at risk or, c) submerged at different groundwater conditions, allowing to propose for each MA targeted guidelines for constructing new car parks. This approach enabled to improve the urban conceptual model and could help the stakeholders in designing a futureurban underground development, also considering groundwater aspects.

Since the beginning of the 1990s, following an intense phase of industrial dismantling, the area of the current metropolitan city of Milan (440 Km2) has been subject to the rise of groundwater level that has generated problems of interference with the underground infrastructures (parkings, metropolitan lines, etc.). The growth in the use of three-dimensional models for groundwater flow, combined with an exhaustive database of the underground employment by the infrastructures, allows today to be able to predict and to manage the effects of changes in the hydrogeological system on the anthropized one. This work aims at better understanding the interactions between the underground infrastructures and the groundwater flow.