This paper presents the results of experimental tests on the intrusion of contaminant through pipe cracks in water distribution network resulting from low/negative pressures. The tests were carried out on a looped distribution network at the University of Enna and were performed first producing a pressure transient that causes negative pressures then reproducing intermittent supply. A soluble contaminant was added to the water volume in the network through a pipe crack. Sampling of water volume was carried out in two nodes of the network and the contaminant concentrations were measured. It was showed that: the contaminant was drawn in and transported, in the first set of tests; the contaminant was carried through the network to the point-of-use when the pipes become completely full and the distribution system was in steady state conditions, in the second, and that the concentrations was higher than in the first set of tests

In complex networks characterized by the presence of private tanks, water managers usually apply intermittent distribution, thus reducing the water volumes supplied to the users, or use Pressure Reduction Valves (PRV) for controlling pressure in the network. The application of Pump As Turbines (PATs) appears as an alternative and sustainable solution to either control network pressure as well as to produce energy. In the present paper, the hydrodynamic model, already presented by De Marchis et al. (2011) was further developed introducing the dynamic analysis of PATs. The model was applied to a district of Palermo network (Italy) characterized by intermittent distribution and by inequities among the user in term of water supply

This study presents a methodology based on Linear Programming for determining the optimal pump schedule on a 24-hour basis, considering as decision variables the continuous pump flow rates which are subsequently transformed into a discrete schedule. The methodology was applied on a case study derived from the benchmark Anytown network. To evaluate the LP reliability, a comparison was made with solutions generated by a Hybrid Discrete Dynamically Dimensioned Search (HD-DDS) algorithm. The cost associated with the result derived from the LP initial solution was shown to be lower than that obtained with repeated HD-DDS runs with differing random seeds

Climate change and modification of the urban environment increase the frequency and the negative effects of flooding, increasing the interest of researchers and practitioners in this topic. Usually, flood frequency analysis in urban areas is indirectly carried out by adopting advanced hydraulic models to simulate long historical rainfall series or design storms. However, their results are affected by a level of uncertainty which has been extensively investigated in recent years. A major source of uncertainty inherent to hydraulic model results is linked to the imperfect knowledge of the rainfall input data both in time and space. Several studies show that hydrological modelling in urban areas requires rainfall data with fine resolution in time and space. The present paper analyses the effect of rainfall knowledge on urban flood modelling results. A mathematical model of urban flooding propagation was applied to a real case study and the maximum efficiency conditions for the model and the uncertainty affecting the results were evaluated by means of generalised likelihood uncertainty estimation (GLUE) analysis. The added value provided by the adoption of finer temporal and spatial resolution of the rainfall was assessed.

Flooding damage appraisal can been obtained by interpolating real damage data caused by historical flooding events or accounting the effects of a flood in terms of the depreciation of assets. Most often, the expected damage is evaluated by means of damage functions describing the relationship occurring between the damage and hydraulic characteristics of flood. The present paper aims to evaluate the uncertainty linked to the choice of the depth-damage function adopted in the flood damage analysis. Several possible depth-damage function formulations were selected in literature and applied to historical flooding events monitored in the “Centro Storico” catchment in Palermo (Italy)