Purpose In soils from serpentinitic areas the natural background of Ni and Cr is so high that the assessment of contamination by comparing metal concentrations with some fixed thresholds may give unreliable results. We therefore sought a quantitative relation between serpentines and Ni and Cr concentrations in uncontaminated soils, evaluated if the approach may help in establishing a baseline, and discussed if additional anthropogenic inputs of Ni and Cr can be realistically individuated in these areas. Materials and methods We analysed the total, acidextractable and exchangeable concentrations of Ni and the total and acid-extractable concentrations of Cr in 66 soil horizons, belonging to 19 poorly developed and uncontaminated Alpine soils. The soils had different amounts of serpentines, depending on the abundance of these minerals in the parent material. We calculated an index of abundance of serpentines in the clay fraction by XRD and related total metal contents to the mineralogical index. We then tested the regressions on potentially contaminated soils, developed on the alluvial plain of the same watershed. Results and discussion We found extremely high total concentrations of Ni (up to 1,887 mg kg -1 ) and Cr (up to 2,218 mg kg -1 ) in the uncontaminated soils, but only a small proportion was extractable. Total Ni and Cr contents were significantly related to serpentine abundance (r 2 =0.86 and 0.74, respectively). The regressions indicated that even small amounts of serpentines induced metal contents above 200 mg kg -1 , and the 95% confidence limits were 75 and 111 mg kg -1 of Ni and Cr, respectively. When the regressions were tested on the potentially contaminated soils, a good estimate was obtained for Cr, while the Ni concentration was overestimated, probably because of some leaching of this element. Conclusions The concentrations of Ni and Cr that can be expected in soils because of the presence of small amounts of serpentines are comparable to the amounts accumulated in the soil because of diffuse contamination and potentially contaminated soils had metal concentrations falling in the range expected from the presence of natural sources. Only in the case of very severe contamination events, the identification of anthropogenic sources adding to the natural background would be feasible.

A generic water system consists of a series of works that allow the collection, conveyance, storage and finally the distribution of water in quantities and qualities such as to satisfy the needs of end users. In places characterized by high altitude differences between the intake works and inhabited centres, the potential energy of the water is very high. This energy is attributable to high pressures, which could compromise the functionality of the pipelines; it is therefore necessary to dissipate part of this energy. A common alternative to dissipation is the possibility of exploiting this energy by inserting a hydraulic turbine. The present study aims to evaluate the results obtained from a stochastic approach for the solution of the multi-objective optimization problem of PATs (Pumps As Turbines) in water systems. To this end, the Bayesian Monte Carlo optimisation method was chosen for the optimization of three objective functions relating to pressure, energy produced and plant costs. The case study chosen is the Net 3 literature network available in the EPANET software manual. The same problem was addressed using the NSGA-III (Nondominated Sorting Genetic Algorithm) to allow comparison of the results, since the latter is more commonly used. The two methods have different peculiarities and therefore perform better in different contexts.

In recent years, there has been a need to seek adequate preventive measures to deal with contamination in water distribution networks that may be related to the accidental contamination and the deliberate injection of toxic agents. Therefore, it is very important to create a sensor system that detects contamination events in real time, maintains the reliability and efficiency of measurements, and limits the cost of the instrumentation. To this aim, two problems have to be faced: practical difficulties connected to the experimental verification of the optimal sensor configuration efficiency on real operating systems and challenges related to the reliability of the network modelling approaches, which usually neglect the dispersion and diffusion phenomena. The present study applies a numerical optimization approach using the NSGA-II genetic algorithm that was coupled with a new diffusive-dispersive hydraulic simulator. The results are compared with those of an experimental campaign on a laboratory network (Enna, Italy) equipped with a real-time water quality monitoring system and those of a full-scale real distribution network (Zandvoort, Netherlands). The results showed the importance of diffusive processes when flow velocity in the network is low. Neglecting diffusion can negatively influence the water quality sensor positioning, leading to inefficient monitoring networks.

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Urban looped water distribution systems are highly vulnerable to water quality issues. They could be subject to contamination events (accidental or deliberate), compromising the water quality inside them and causing damage to the users’ health. An efficient monitoring system must be developed to prevent this, supported by a suitable model for assessing water quality. Currently, several studies use advective–reactive models to analyse water quality, neglecting diffusive transport, which is claimed to be irrelevant in turbulent flows. Although this may be true in simple systems, such as linear transport pipes, the presence of laminar flows in looped systems may be significant, especially at night and in the peripheral parts of the network. In this paper, a numerical optimisation approach has been compared with the results of an experimental campaign using three different numerical models as inputs (EPANET advective model, the AZRED model in which diffusion–dispersion equations have been implemented, and a new diffusive–dispersive model in dynamic conditions using the random walk method, EPANET-DD). The optimisation problem was formulated using the Monte Carlo method. The results demonstrated a significant difference in sensor placement based on the numerical model.

The EPANET model is commonly used to model hydraulic behaviour and water quality within water distribution networks. The standard version of the model solves the advective transport equation by solving a mass balance of the fundamental plug flow substance that considers the advective transport and kinetic reaction processes. Over the years, several versions of the model have been developed, which have made it possible to improve the modelling of water quality through the introduction of additional terms within the transport equation to solve the problem of dispersive transport (EPANET-AZRED) and to consider multiple interacting species in the mass flow and on the pipe walls (EPANET multi-species extension). The present study proposes a novel integration of the EPANET-DD (dynamic-dispersion) model, which enables the advective–diffusive–dispersive transport equation in dynamic flow conditions to be solved in the two-dimensional case, through the classical random walk method, implementing the diffusion and dispersion equations proposed by Romero-Gomez and Choi (2011). The model was applied to the University of Enna “KORE” laboratory network to verify its effectiveness in modelling diffusive–dispersive transport mechanisms in the presence of variable flow regimes. The results showed that the EPANET-DD model could better represent the actual data than previously developed versions of the EPANET model.

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