Marco Masetti

Reliability of groundwater vulnerability maps obtained through statistical methods

Statistical methods are widely used in environmental studies to evaluate natural hazards. Within groundwater vulnerability in particular, statistical methods are used to support decisions about environmental planning and management. The production of vulnerability maps obtained by statistical methods can greatly help decision making. One of the key points in all of these studies is the validation of the model outputs, which is performed through the application of various techniques to analyze the quality and reliability of the final results and to evaluate the model having the best performance. In this study, a groundwater vulnerability assessment to nitrate contamination was performed for the shallow aquifer located in the Province of Milan (Italy). The Weights of Evidence modeling technique was used to generate six model outputs, each one with a different number of input predictive factors. Considering that a vulnerability map is meaningful and useful only if it represents the study area through a limited number of classes with different degrees of vulnerability, the spatial agreement of different reclassified maps has been evaluated through the kappa statistics and a series of validation procedures has been proposed and applied to evaluate the reliability of the reclassified maps. Results show that performance is not directly related to the number of input predictor factors and that is possible to identify, among apparently similar maps, those best representing groundwater vulnerability in the study area. Thus, vulnerability maps generated using statistical modeling techniques have to be carefully handled before they are disseminated. Indeed, the results may appear to be excellent and final maps may perform quite well when, in fact, the depicted spatial distribution of vulnerability is greatly different from the actual one. For this reason, it is necessary to carefully evaluate the obtained results using multiple statistical techniques that are capable of providing quantitative insight into the analysis of the results. This evaluation should be done at least to reduce the questionability of the results and so to limit the number of potential choices.

Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment

Statistical techniques can be used in groundwater pollution problems to determine the relationships among observed contamination (impacted wells representing an occurrence of what has to be predicted), environmental factors that may influence it and the potential contamination sources. Determination of a threshold concentration to discriminate between impacted or non impacted wells represents a key issue in the application of these techniques. In this work the effects on groundwater vulnerability assessment by statistical methods due to the use of different threshold values have been evaluated. The study area (Province of Milan, northern Italy) is about 2000 km(2) and groundwater nitrate concentration is constantly monitored by a net of about 300 wells. Along with different predictor factors three different threshold values of nitrate concentration have been considered to perform the vulnerability assessment of the shallow unconfined aquifer. The likelihood ratio model has been chosen to analyze the spatial distribution of the vulnerable areas. The reliability of the three final vulnerability maps has been tested showing that all maps identify a general positive trend relating mean nitrate concentration in the wells and vulnerability classes the same wells belong to. Then using the kappa coefficient the influence of the different threshold values has been evaluated comparing the spatial distribution of the resulting vulnerability classes in each map. The use of different threshold does not determine different vulnerability assessment if results are analyzed on a broad scale, even if the smaller threshold value gives the poorest performance in terms of reliability. On the contrary, the spatial distribution of a detailed vulnerability assessment is strongly influenced by the selected threshold used to identify the occurrences, suggesting that there is a strong relationship among the number of identified occurrences, the scale of the maps representing the predictor factors and the model efficiency in discriminating different vulnerable areas.

A Comparison of Data-Driven Groundwater Vulnerability Assessment Methods

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

Rainfall, infiltration, and groundwater flow in a terraced slope of Valtellina (Northern Italy): field data and modelling

The aim of this work was to understand and reproduce the hydrological dynamics of a slope that is terraced by dry retaining walls. This approach will help to assess the influence of temporary groundwater perched tables, which can form at the area of contact between the backfill of the wall and the bedrock, on the wall’s stability. The study area is located in Valtellina (Northern Italy) near the village of Tresenda, which was affected by three debris flows that caused 18 casualties in 1983. In 2002, another event of the same type affected this area, but that event only caused the interruption of a major transport road. Direct observations of one of the three flows in 1983 and the reconstruction of 2002 indicated that the most probable triggering cause was the collapse of a dry retaining wall after its backfill was saturated. After field work was conducted to discover the principal hydrological and hydrogeological characteristics of the slope, numerical modelling was performed to determine under what conditions the soil will saturate, and therefore, when the collapse of a dry retaining wall might occur. First, a study of the interaction between pluviometric events and groundwater behaviour was conducted; then, modelling was performed using finite element analysis software that permits the calculation of groundwater flow both for completely and partially saturated conditions. The model was calibrated and validated using the hydrographs of the groundwater table recorded on site. It can be used as a predictive instrument for rainfall events of a given duration and return period.

Aquifer nitrate vulnerability assessment using positive and negative weights of evidence methods, Milan, Italy

Statistical methods are extensively used by hydrogeologists for assessing groundwater vulnerability. Several of these methods require to express the response variable as binary and to select a threshold distinguishing between positive and negative indicators of contamination that are usually identified as occurrences and non-occurrences, respectively. In this study, both occurrences and non-occurrences were alternately used as training points (TPs) in the weights of evidence (WofE) for assessing groundwater vulnerability to nitrate contamination of a shallow, unconfined, porous aquifer. This was done to better understand the individual role and the combined effect of explanatory variables in both protecting and exposing groundwater from and to nitrate contamination in the study area. The idea behind this approach is that, for a given aquifer, each explanatory variable should have an unequivocal effect on the physical process of groundwater contamination. As part of this study, a procedure for multi-class generalization was developed. Results showed that an evidential theme, even if it appears to be a statistically significant predictor of occurrences, can show an equivocal spatial relationship with the positive and the negative indicators of contamination due to the presence of a sampling bias between the TPs and the evidential theme. It was demonstrated that, if sampling bias is not recognized and corrected, the use of such evidential theme in the analysis could lead to obtain unreliable groundwater vulnerability maps. In order to deal with this issue, a quantitative methodology to correct the effects of sampling bias was successfully tested. Indeed, once the spatial relationships between the different type of TPs and the considered evidential themes were corrected for the effects of sampling bias, the WofE method was found to be a reliable modeling technique for assessing groundwater vulnerability and proved to be capable of identifying areas characterized by different degrees of vulnerability.

Impact of a Storm-Water Infiltration Basin on the Recharge Dynamics in a Highly Permeable Aquifer

Infiltration basins are increasingly used worldwide to both mitigate flood risk in urban areas and artificially recharge shallow aquifers. Understanding recharge dynamics controlling the quantity and quality of infiltrating water is required to correctly design and maintain these facilities. In this paper, we focus on quantitative aspects and analyze in detail the temporal evolution of infiltration rates in basins overlying highly permeable aquifers. In these settings, recharge is a complex process due to high recharge rate and volume, undetected soil hydraulic heterogeneity and topsoil clogging. A 16-ha infiltration basin in Northern Italy has been intensively characterized and monitored for over four years. Field and laboratory tests were performed to characterize soil hydraulic properties. An unsaturated-saturated numerical model was implemented to obtain additional quantitative information supporting experimental data. Results show a strong impact of the infiltration basin on natural recharge patterns. When properly maintained (no clogging of topsoil), estimated infiltration rates from the bottom of the basin are about fifty times higher than recharge under natural conditions in the same area. When the infiltration basin is not properly maintained, bioclogging progressively diminishes the infiltration capacity of the basin, which turns to have no impact on aquifer recharge. Recharge patterns are highly erratic and difficult to predict. We observed natural recharge rates of the order of 1 m/h and a poor correlation between recharge times and maximum intensity of rainfall events. Due to the complex behavior of the recharge, the numerical model (based on the classical Richards equation) is able to explain many but not all the observed recharge events. Macropores flow and Lisse effects on piezometric measurements may be responsible for the disagreement between model predictions and observations.

A versatile method for groundwater vulnerability projections in future scenarios

Water scarcity and associated risks are serious societal problems. A major challenge for the future will be to ensure the short-term and long-term provision of accessible and safe freshwater to meet the needs of the rapidly growing human population and changes in land cover and land use, where conservation and protection play a key role. Through a Bayesian spatial statistical method, a time-dependent approach for groundwater vulnerability assessment is developed to account for both the recent status of groundwater contamination and its evolution, as required by the European Union (Groundwater Directive, 2006/118/EC). This approach combines natural and anthropogenic factors to identify areas with a critical combination of high levels and increasing trends of nitrate concentrations, together with a quantitative evaluation of how different future scenarios would impact the quality of groundwater resources in a given area. In particular, the proposed approach can determine potential impacts on groundwater resources if policies are maintained at the status quo or if new measures are implemented for safeguarding groundwater quality, as natural factors are changing under climatic or anthropogenic stresses.

Using statistical analyses for improving rating methods for groundwater vulnerability in contamination maps

With the aim of developing procedures coping with the disadvantages and emphasising the advantages of existing rating methods and the use of statistical methods for assessing groundwater vulnerability, we propose to combine the two approaches to perform a groundwater vulnerability assessment in a study area in Italy. In the case study, located in an area of northern Italy with both urban and agricultural sectors, keeping the structure of the DRASTIC rating method, we used a spatial statistical approach to calibrate weights and ratings of a series of variables, potentially affecting groundwater vulnerability. In order to verify the effectiveness of these procedures, the results were compared to a non-modified approach and to the map resulting from the “Time–Input” method, highlighting the advantages that can be obtained, and defining the general limit of these applications. The revised method shows a more realistic distribution of vulnerability classes in accordance with the distribution of wells impacted by high nitrate concentration, demonstrating the importance of taking into account the specific hydrogeological conditions of the area.

Use of scatterometer data in groundwater vulnerability assessment

Lombardy 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 Korea to Catania: a busy September for IAH Italy

Si è appena concluso Il 45° Congresso internazionale IAH del 2018, che si è tenuto a Daejeon, in Korea, dal 9 al 14 settembre. Il Congresso era articolato in nove main topics sul tema: “Groundwater and Life: Science & Technology into Action”, e nel dettaglio: • T1 Groundwater and Life: Progress towards the Solution of Critical Problems; • T2 Spotlight on Modeling, Emerging Technologies and Their Applications; • T3 Global/Regional Environmental Changes and Their Consequences; • T4 Strategies to Assure the Sustainability of Groundwater Resources; • T5 Groundwater Quality and Contamination; • T6 Groundwater and Surface Water: an Integrated View; • T7 Advances in Karst and Fractured-rock Hydrogeology; • T8 Coastal Zone Management and Water Resources; • T9 Groundwater and Energy. I partecipanti sono stati numerosi (702), provenienti da 63 diverse nazioni e prevalentemente dalla Korea (469) e dal resto dell’Asia, ma con una discreta rappresentanza europea, con l’Italia seconda subito dietro alla Germania come numero di partecipanti (16). Gli abstract presentati sono stati 550 di cui 13 italiani (sesto paese insieme al Canada e davanti agli Stati Uniti). Il congresso IAH ha offerto molti motivi di richiamo: tra le 10 keynote lectures, tutte con un ottimo successo di pubblico, di rilievo quelle di Frank Schwartz e Makoto Taniguchi, ma anche le altre hanno offerto spunti interessanti, rivelando in taluni casi contesti idrogeologici molto diversi dai nostri, ma la cui gestione può essere un modello a scala globale. L’organizzazione delle sessioni orali nelle varie sale del DCC (Daejeon Convention Center) è stata impeccabile, avvalendosi anche dell’alta tecnologia coreana, e le sessioni poster ben organizzate. Il terzo giorno del Congresso è stato dedicato ai field trips, che avevano come oggetto l’illustrazione di casi di studio stimolanti dal punto di vista scientifico e naturalistico (es. il karst e i parchi geologici) nonché tecnico (es. visite a impianti geotermici, idroelettrici e nucleari, a dighe, e discariche). Il gruppo degli idrogeologi italiani è stato accolto prima del convegno a Seoul con una cena in un ristorante tipico coreano (Fig. 1) dall’addetto scientifico dell’Ambasciata d’ Italia, prof. Francesco Canganella, che aveva in precedenza stabilito un contatto con il Kigam (Korea Institute of Geoscience and Mineral Resources), grazie al quale IAH Italia ha potuto interagire e organizzare congiuntamente la sessione bilaterale Korea Italia sul “Monitoring and management of coastal aquifers”. Questa sessione (Fig. 2), convenors Marco Masetti e Heesung Yoon, responsabile per l’idrogeologia del Kigam, visto il cospicuo numero di interventi (11, di cui 5 coreani e 6 italiani) è stata suddivisa in due sotto-sessioni e ha avuto un grande successo, Fig.1: The Italian delegation and the scientific officer of the Italian Embassy, prof. Francesco Canganella, at the dinner in the typical Korean restaurant in Seoul.