The significant increase in urbanization has resulted in greater use of the subsurface in urban planning and, therefore, increased interaction between groundwater and underground infrastructure. Numerical models are the primary tool adopted to manage the resulting problems; however, their construction is time- and cost-consuming. Groundwater-level time-series analysis can be a complementary method, as this data-driven approach does not require an extensive understanding of the geological and boundary conditions, even if providing insights into the hydrogeologic behaviour. Thus, a data-driven approach was adopted to analyse groundwater time-series of the shallow aquifer, occupied by several underground structures, beneath Milan city (Northern Italy). Statistical (Mann-Kendall and Sen’s slope estimator, autocorrelation and cross-correlation, hierarchical cluster analysis) and geospatial techniques were used to detect the potential variables influencing the groundwater levels of 95 monitoring wells, covering the period 2005–2019. A general rising trend of the water table was identified, with local hydrogeologic differences in the western and southernmost areas. Based on time-series analysis results, four management areas have been identified. These areas could act as future geographic units with specific groundwater management strategies. In particular, subsurface public car parks can be classified with respect to groundwater flooding as (1) not submerged, (2) possibly critical, or (3) submerged at different groundwater conditions. According to these outcomes, targeted guidelines for constructing new car parks have been elaborated for each management area. The methodology proved to be efficient in improving the urban conceptual model and helping stakeholders design the planned underground development, considering groundwater aspects.
As groundwater quality monitoring networks have been expanded over the last decades, significant time series are now available. Therefore, a scientific effort is needed to explore innovative techniques for groundwater quality time series exploitation. In this work, time series exploratory analysis and time series cluster analysis are applied to groundwater contamination data with the aim of developing data-driven monitoring strategies. The study area is an urban area characterized by several superimposing historical contamination sources and a complex hydrogeological setting. A multivariate time series cluster analysis was performed on PCE and TCE concentrations data over a 10 years time span. The time series clustering was performed based on the Dynamic Time Warping method. The results of the clustering identified 3 clusters associated with diffuse background contamination and 7 clusters associated with local hotspots, characterized by specific time profiles. Similarly, a univariate time series cluster analysis was applied to Cr(VI) data, identifying 3 background clusters and 7 hotspots, including 4 singletons. The clustering outputs provided the basis for the implementation of data-driven monitoring strategies and early warning systems. For the clusters associated with diffuse background contaminations and those with constant trends, trigger levels were calculated with the 95° percentile, constituting future threshold values for early warnings. For the clusters with pluriannual trends, either oscillatory or monotonous, specific monitoring strategies were proposed based on trends’ directions. Results show that the spatio-temporal overview of the data variability obtained from the time series cluster analysis helped to extract relevant information from the data while neglecting measurements noise and uncertainty, supporting the implementation of a more efficient groundwater quality monitoring.
The recent rapid increase in urbanization has led to the inclusion of underground spaces in urban planning policies. Among the main subsurface resources, a strong interaction between underground infrastructures and groundwater has emerged in many urban areas in the last few decades. Thus, listing the underground infrastructures is necessary to structure an urban conceptual model for groundwater management needs. Starting from a municipal cartography (Open Data), thus making the procedure replicable, a GIS methodology was proposed to gather all the underground infrastructures into an updatable 3D geodatabase (GDB) for the metropolitan city of Milan (Northern Italy). The underground volumes occupied by three categories of infrastructures were included in the GDB: (a) private car parks, (b) public car parks and (c) subway lines and stations. The application of the GDB allowed estimating the volumes lying below groundwater table in four periods, detected as groundwater minimums or maximums from the piezometric trend reconstructions. Due to groundwater rising or local hydrogeological conditions, the shallowest, non-waterproofed underground infrastructures were flooded in some periods considered. This was evaluated in a specific pilot area and qualitatively confirmed by local press and photographic documentation reviews. The methodology emerged as efficient for urban planning, particularly for urban conceptual models and groundwater management plans definition.
The town of Mantua is a good example of an urban area with an intricate surface water system leading to complex groundwater/surface-water interactions. In this context, the Site of National Interest (SIN) “Laghi di Mantova e Polo Chimico”, is characterized by intense pumping activity by means of industrial wells and hydraulic barriers. In order to establish the interactions between groundwater and the surface water system, evaluating their relation with the pumping activities, a transient groundwater numerical model was developed (January 2016 - December 2018) using MODFLOW-2005 and the Streamflow-Routing (SFR2) package, following a participatory approach. Results show how, depending on the minimum/ maximum groundwater conditions and the discharge values of the surface channels, the relation between groundwater/surface-waters can vary during the year, also affecting the operation of the hydraulic barriers. The stakeholders could use the calibrated model in the future to ensure optimal management of the pumping activities within the SIN.
<p>Groundwater is a key resource to fulfil human drinking needs worldwide. Therefore, guaranteeing a safe and constant supply of drinking water to the public has been an important focus at European level. Recently, the EU approach to drinking water monitoring radically changed, moving from the simple water quality monitoring, toward a more comprehensive risk assessment, involving the whole supply chain from collection to distribution. Particularly, EU Directives 2015/1787 and 2020/2184 endorsed the Water Safety Plan (WSP) system which requires a detailed assessment of every possible dangerous event.</p><p>Groundwater extraction constitutes the first step of the supply chain, and therefore the most vital. In this work, an approach to assess groundwater wells vulnerability in the scope of WSP is proposed, considering natural and anthropogenic hazards, through a hydrogeological, hydrochemical and hydrodynamical characterization. The study area is the Lake Iseo morainic amphitheatre (ca. 180 km<sup>2</sup>) in the Brescia province, Northern Italy. Particularly, 17 wells have been analyzed, serving 4 municipalities.</p><p>Two main dangerous events have been considered as possible hazard for the collected groundwater: a) anthropogenic impact from the surface, related to the land use, and b) natural contamination by reduced species consequent to the degradation of natural organic matter.</p><p>Groundwater extraction vulnerability to these two dangerous events has been assessed, considering several hydrogeological aspects: a) the kind of the exploited aquifer (shallow, confined, semiconfined), b) groundwater depth for the shallow aquifers, c) permeability of the vadose zone for the shallow aquifers and d) red-ox conditions of the collected groundwater.</p><p>To assess these parameters, lithostratigraphic, chemical and piezometric data were analyzed, reaching a deep understanding of the system by characterizing the different exploited groundwater bodies from a hydrogeological, hydrochemical and hydrodynamic point of view.</p><p>Hydrogeological sections were elaborated, covering the whole amphitheater, 7 in the N-S direction and 7 in the W-E direction. The interpretation of these sections allowed to identify the distribution of the main aquifer bodies and the relationships between the various hydrogeological units. To evaluate the red-ox conditions and perform groundwater quality characterization, chemical data were analyzed, including major ions and red-ox sensitive species, through boxplot and statistical analysis. Furthermore, piezometric levels were analyzed to identify groundwater depth, flow directions and watersheds. Of the 17 wells, one resulted to be confined with reducing conditions. Among the remaining, 7 are semiconfined while 9 are shallow, with oxidizing conditions in both cases. Concerning groundwater depth, 13 present values above 40 m, 2 between 20 m and 40 m, and 1 below 20 m. As regards the vadose zone permeability, 9 present high permeability, 7 medium. Totally, in terms of vulnerability to anthropic impacts, one well has low vulnerability, 9 medium and 6 high, while in terms of vulnerability to natural contamination one well has high vulnerability and the remaining low.</p><p>This approach allowed a deep understanding of the system and constitutes a reproducible methodology to assess groundwater wells vulnerability to natural and anthropogenic contaminations.</p><p>Funding: this work was supported and carried out in cooperation with Acque Bresciane, water supplier.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.