Risk analysis for remediation of contaminated sites: the geostatistical approach

The assessment of the risks associated with contamination by elevated levels of pollutants is a major issue in most parts of the world. The risk arises from the presence of a pollutant and from the uncertainty associated with estimating its concentration, extent and trajectory. The uncertainty in the assessment comes from the difficulty of measuring the pollutant concentration values accurately at any given location and the impossibility of measuring it at all locations within a study zone. Estimations tend to give smoothed versions of reality, with the smoothing effect being inversely proportional to the amount of data. If risk is a measure of the probability of pollutant concentrations exceeding specified thresholds, then the variability is the key feature in risk assessment and risk analysis. For this reason, geostatistical simulations provide an appropriate way of quantifying risk by simulating possible “realities” and determining how many of these realities exceed the contamination thresholds, and, finally, provides a means of visualizing risk and the geological causes of risk. This study concerns multivariate simulations of organic and inorganic pollutants measured in terrain samples to assess the uncertainty for the risk analysis of a contaminated site, an industrial site in northern Italy that has to be remediated. The main geostatistical tools are used to model the local uncertainty of pollutant concentrations, which prevail at any unsampled site, in particular by means of stochastic simulation. These models of uncertainty have been used in the decision-making processes to identify the areas targeted for remediation.     

Regionalisation of the “intensity-duration-frequency” curves in Northern Algeria

The flood events observed during last years in the urban areas are subject of main interest for quantification of the hydro-climatic risks and climatic change to the regional scales. The establishment of a statistical relationship between the intensities of intense rains and the recurrence of these events allows us to determine the dimensions of the works according to a previously defined level of risk. They constitute today a leading tool for various users. This work concerns the study of the maximum annual rains, recorded at 49 stations in the northern Algeria. The objectives of this work are to determine the estimators who are the “intensity-duration-frequency” curves and to extract from these whole of information the b Montana climatic parameter to be regionalized for the calculating the river flow and for the dimensioning of the networks of cleansing in the event of insufficiency of data. Different durations going from 15 min to 24 h are studied. We utilised the collocated co-kriging as multivariate estimation method for interpolation in order to yield the space distribution maps of b Montana climatic parameter, with the benefit of using spatially correlated secondary variables, such as the digital elevation model and the distance from the coastline that are known at any localisation. All features led to choose the digital elevation model as covariate for interpolating b Montana values, yielding a better regionalisation of the studied climatic parameter. The geostatistical handling of b Montana values strictly related to auxiliary variables that constitute physical factors overcomes the data shortage in planning, managing and preventing the rain flood risk.     

Intrinsic vulnerability assessment of Saturnia thermal aquifer by means of three parametric methods: SINTACS,GODS and COP

Three different parametric methods for the evaluation of intrinsic vulnerability to pollution have been applied in a hydrothermal carbonate aquifer located in central-northern Italy and the results obtained were compared with each other. The study area, large, approximately 152 km², lies in an area of the northern Apennines. The investigated aquifer feeds the hot thermal springs of Saturnia. The vulnerability assessment methods used are: SINTACS, GODS and COP. The vulnerability maps obtained were first individually examined, and then they were compared with each other by means of spatial analysis. These maps show similar results for the estimation of the vulnerability just in some areas. SINTACS yields areas potentially vulnerable to pollution along the Albegna River and its major tributaries in the northern part of the study area. The GODS index map reflects the great importance that this method gives to the lithological characteristics of the unsaturated zone in the subdivision of areas with different vulnerability. GODS and COP methods agree in classifying low vulnerability in the most part of central-southern study area, where the aquifer is confined by the Pliocene clay deposits. Based on the conceptual model of groundwater flow developed for the aquifer under investigation, COP seems the most appropriate method among those applied in this work, in particular with regard to the assessment of the vulnerability of the recharge area of thermal groundwater. Located in the northern part of the study area, where karst carbonate formations of the Tuscan Nappe outcrop, this recharge area is classified by the COP method as highly vulnerable to pollution.     

Numerically enhanced conceptual modelling (NECoM) applied to the Malta Mean Sea Level Aquifer

Conventional hydrogeological practice is to formulate a conceptual model, which is often the basis of a numerical model. The numerical model is then used to test groundwater management strategies. A workflow is proposed, employing the numerically enhanced conceptual model (NECoM) of the Mean Sea Level Aquifer (MSLA) on the island of Malta. The Malta MSLA is overexploited and under threat of salinization. Data (heads, chloride concentrations, electrical conductivity logs, tidal tests and qualitative analyses) were assimilated into a fast-running numerical model. Simultaneously, strategies for optimal acquisition of further data were examined through the modelling process. The model was delivered through the Energy and Water Agency, with suggestions for flexible model deployment. These workflows will, hopefully, spawn model improvements through further revision of the base concepts. The model allows the agency to make predictions, which have uncertainties that are quantified and reduced through data assimilation as new data become available. Contemplated management plans can therefore be properly assessed before implementation. The proposed NECoM approach can be generalized since it bases model usage on the premise that modelling should make maximum use of existing data by assimilating its information content, thereby highlighting the uncertainties of decision-critical predictions that remain because of data insufficiency. Thus, the presently disjointed process of modelling on the one hand, and data acquisition on the other, can be better aligned. Conceptual and numerical model development become parallel, rather than sequential, activities. Together, they enable predictions of future system behaviour for which bias is reduced and uncertainties quantified.

     

Geological and hydrogeological reconstruction of the main aquifers of the Maltese islands

Hydrogeology Journal - Geological and hydrogeological conceptualizations of the five main aquifers of Malta were performed by means of characterization of the groundwater bodies’ geometries...