1,721,005 research outputs found
Groundwater vulnerability or groundwater pollution risk?
No full textThis short note presents the complexity behind the definition of groundwater vulnerability and the vulnerability assessment methods. Although intrinsic and specific vulnerability are unanimously accepted concepts, and risk assessments are widely performed to protect groundwater from contamination, the development of new techniques to estimate groundwater vulnerability raised questions on whether a vulnerability or a risk is indeed assessed
TIME-DEPENDENT METHODS TO EVALUATE THE EFFECTS OF URBAN SPRAWL ON GROUNDWATER QUALITY
Full text linkAs groundwater resources are becoming more vulnerable due to the increasing number of contamination sources in developed and developing countries (such as urbanization and agricultural activities), practical actions, strategies and solutions to protect the resource are widely required. The most efficient tool, which helps supporting land use development, while protecting groundwater from contamination, is represented by groundwater vulnerability assessment. European Directives require member states, for the protection of groundwater quality, to assess the current groundwater quality status, detect changes or trends in groundwater quality, assess the threat of deterioration and predict future changes in groundwater quality. In order to cope with the EU requirements, this study focuses on the development of a time-dependent approach, which could take into account both the current groundwater quality status and its changes, assessing groundwater vulnerability to nitrate contamination in the Po Plain area of Lombardy Region, through a Bayesian spatial statistical method (Weights of Evidence). In addition, an innovative dataset to delineate urban areas with satellite scatterometer data (QuikSCAT-DSM) is explored. To evaluate its reliability in groundwater vulnerability assessments, QuikSCAT-DSM dataset is compared with population density and land use derived from aerial images. Results showed that: a) urbanization prevails on agricultural activities in causing the degradation of groundwater quality; b) QuikSCAT-DSM data is a reliable variable to represent urban nitrate sources, with the advantages of a worldwide coverage, a continuous data collection and an adequate resolution; c) the time-dependent approach allows to identify areas both affected by nitrate contamination and characterized by an upward concentration trend of contamination; d) the time-dependent approach allows to determine what could happen to groundwater resources if land use policies are maintained or new ones will be proposed and/or if natural factors are changing under climatic or anthropogenic stresses
Effects of urban changes on groundwater vulnerability, a case study in Lombardy (Italy)
No full textUrban sprawl is one of the most important types of land-use changes currently affecting Europe with important impacts on groundwater quality. The area of the Po Plain in northern Italy is one of the most populated areas in Europe and can be considered as a representative area to study urban sprawl impacts on groundwater quality. The identification of areas where groundwater is characterized by a degradation of the water quality is required by two European Union Directives (2000/60/EC and 2006/118/EC).
Here, we present a time-dependent groundwater vulnerability assessment of the Po Plain area of Lombardy region, concerning the period 2001–2011.
Three different variables have been selected, and compared to each other, in order to investigate the evolution of urban nitrate non-point sources: urbanization derived from satellite scatterometer data (QuikSCAT-DSM data), population density changes calculated using two successive national censuses (database ISTAT) and land-use changes derived from photo-interpretation of aerial imageries (database DUSAF).
Four other variables, considered not being time-dependent for the purpose of this study, have been identified to represent the geological and hydrogeological conditions of the study area: soil protective capacity, groundwater depth, groundwater velocity and hydraulic conductivity of the vadose zone.
Groundwater vulnerability is assessed through the spatial statistical method Weights of Evidence (WofE). WofE enables observations of the individual role and the combined effect of both urban change and geological factors considered in the analysis in relation to the change of nitrate concentration in the decade 2001–2011. Time-dependent groundwater vulnerability maps for the study area have been produced and compared
Urban impacts on air quality observed with remote sensing and ground station data from the PO plain field campaign
No full textThe Po Plain area is one of the most urbanized and polluted regions in Europe, with the city of Milan being a major “hot spot” of nitrogen dioxide (NO2) in the world. The Po Plain Experiment Field Campaign has been carried out to identify and understand impacts of urban characteristics on the environment across the Po Plain in Northern Italy. Air quality is investigated with both remote sensing and ground station data. Preliminary results show a moderate correlation between satellite observations and ground-based measurements, highlighting the close relationship between the urban pattern and the distribution of NO2 all over the region
Introducing the climate component into landslide susceptibility mapping
No full textIntense rainfall and snowmelt are commonly recognized predisposing and triggering factors for shallow landslides, especially in mountainous environments. Due to climate change, their frequency and magnitude could vary, thus modifying soils response. Therefore, their inclusion in planning instruments becomes fundamental. The aim of our study was to derive a susceptibility model adaptable to climate changes, through the inclusion of variables summarizing intense rainfall and snowmelt processes. We selected the territory of the Mont-Emilius and Mont-Cervin Mountain Communities (northern Italy) as study area. To define the summary variables, we investigated the relationships between landslide occurrences and meteorological events (reference period 1991-2020). For landslide susceptibility mapping, we set up a Generalized Additive Model. For model training, we extracted from the local inventory 298 dated landslide points and we selected 300 random non-landslide points. We defined a reference model analyzing the statistiscal significance of the variables (relief, NDVI, land cover and geology predictors). Similarly, we optimized a model including the climate variables, checking also their smooth functions to ensure physical plausibility. Finally, we validated the optimized model through a k-fold cross-validation. We evaluated all models through contingency tables and area under the receiver operating characteristic curve (AUROC). Also, we investigated variable importance through the decrease in explained variance. The climate variables that resulted statistically and physically significant are the effective annual number of rainfall events with intensity-duration characteristics above a defined threshold (EATean) and the average number of melting events occurring in a hydrological year (MEn). In the optimized model, together they accounted for 5% of the model deviance. The optimized model showed a true positives rate and an AUROC higher than the reference model (2.4% and 0.8%, respectively). The introduction of the meteorological variables caused a transition of vulnerability class in 11.0% of the modelling area. The k-fold validation confirmed the statistical and physical significance of the meteorological variables in 74% (EATean) and 93% (MEn) of the fitted models. Our findings stress the utility of these variables in improving the performance of susceptibility models and making them adaptable to climate changes
Influence of air pollution on rainfall chemistry and impacts on groundwater quality in the Milan urban area, Italy
No full textUse of scatterometer data in groundwater vulnerability assessment
No full textLombardy in Italy has been selected as a case study to evaluate the capability of the QuikSCAT - Dense Sampling Method (QSCAT-DSM) data in delineating urban extent, estimating rate of urban changes, and assessing aquifer vulnerability, in particular to investigate the relationship between land-use changes and groundwater contamination. QSCAT-DSM data represent an innovative approach to delineate urban and interurban areas with satellite scatterometer data. Radar backscatter acquired by the SeaWinds scatterometer aboard the QSCAT satellite together with the DSM are used to identify and map surface features at a posting scale of about 1 km2. Through the spatial statistical methods Weight of Evidence (WofE), both urban changes given by QSCAT-DSM data and population changes in the decade of the 2000's have been correlated to nitrate concentration trend in groundwater in the same time period. Both analyses based on urban change and on population change lead to the same result: urban nitrate sources in Lombardy increase the level of nitrate concentration in groundwater, indicating a degradation of the water quality. Moreover, QSCAT-DSM data proved to be a reliable tool for evaluating urban changes continuously without a temporal or spatial gap, and to be a strategic variable allowing the assessment of groundwater vulnerability consistently throughout the decadal time scale
From 2D geological maps to 3D models: A case-study in the Central Alps (Lombardy, Italy)
No full textThe effects of an infiltration basin on groundwater: quantitative aspects (River Arno - Lonate Pozzolo, VA)
No full textThe Last Glaciation in Valchiavenna (Italian Alps): maximum ice elevation data and recessional glacial deposits and landforms
Full text linkThis work presents the first extensive, 1:10,000-scale field survey data concerning glacial deposits and glacigenic landforms in the Valchiavenna territory, which has an area of 578 km2. Valchiavenna is an inner Alpine valley in Northern Italy between the Lepontine and Western Rhaetian Alps. A comprehensive 1:25,000 map of deposits and landforms from the last glaciation to the present is provided, describing i) glacial trimline evidence and associated features, such as moraine ridges, erratic boulders, ice- moulded bedrock surfaces and kame terraces; ii) glacial, ice-contact, lacustrine/peat and gravity-reworked till deposits; iii) other supraglacial, marginoglacial and subglacial landforms; and iv) erratics in glacial deposits. Establishing an absolute chronology of glacier dynamics was not the objective of this work. However, a relative chronology was inferred from sedimentological and geomorphological evidence: this allowed the description of the general behaviour of glaciers in the area during and after the Last Glacial Maximum (LGM). The palaeogeography at the LGM and the palaeo-ice-flow pattern were reconstructed on the basis of field data; this data confirmed that the valleys were almost completely filled by glacier ice, covering about 88% of the study area, with only the most elevated ridges and a few nunataks emerging above the ice surface, and allowed the identification of different source areas for the erratics found on opposite sides of the main valley. The observation of stratigraphical and geomorphological relationships between glacial deposits and landforms made it possible to propose a relative chronology of glacial advances and to outline the general glacial dynamics of the area. Both at the LGM and during the deglaciation after the LGM, the valley glacier inserted offshoots in tributary valleys, thus generally blocking the advance of local glaciers. With the gradual melting of the valley glacier during the deglaciation after the LGM, tributary glaciers could deposit tills on areas previously covered by valley glacier ice and at lower altitudes than the older lateral moraines. The main outcome of this work is a rich and homogeneous database of glacial deposits and glacigenic landforms that will be useful for further local and regional studies. It can guide the planning of geochronological dating and represents a fundamental step in the identification of glacial stadials and ice mass modelling. It can also support biogeography studies and the evaluation of the effects of climate change, slope dynamics modelling and hazard prediction
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