Fast geomorphic transients may involve complex scenarios of sediment transport, occurring near the bottom as bed load (i.e., saltating, sliding, and rolling) or as suspended load in the upper portion of the flow. The two sediment transport modalities may even coexist or alternate each other during the same event, especially when the shear stress varies considerably. Modeling these processes is therefore a challenging task, for which the usual representation of the flow as a mixture may result in being unsatisfactory. In the present paper, a new two-phase depth-averaged model is presented that accounts for variable sediment concentration in both bed and suspended loads. Distinct phase velocities are considered for bed load, whereas the slip velocity between the two phases is neglected in the suspended load. It is shown that the resulting two-phase model is hyperbolic, and the analytical expression of the eigenvalues is provided. The entrainment/deposition of sediment between the bottom and the bed load layer is based on a modified van Rijn transport parameter, whereas for the suspended sediment a first-order exchange law is considered. A numerical finite-volume method is used for the simulation of three dam break experiments found in the literature, which are effectively reproduced in terms of both free surface elevation and bottom deformation, confirming the key role played by the solid concentration variability even for two-phase models

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The sustainable management of water supply networks requires the control of physical pipe leakages, such as those due to junction obsolescence or pipe creeping. These leakages usually increase with the operating pressure, and their discharge is commonly assumed to scale with the power of the pressure. The same functional form is also employed to evaluate leakage occurring in the portion of the network downstream a node. The parameters involved in these relationships may be estimated from field experimental data. However, a sensible fluctuation in their values is observed, and therefore the definition of a suitable leakage law represents a major source of uncertainty in water network modeling. In the present paper, the estimation of the leakage law parameters is carried out simultaneously to the hourly demand pattern. To this aim, a hydraulic network model coupled to a genetic algorithm is employed to minimize the deviation between predicted and measured time series of pressure and flow at a small number of sites of the network.A field test case is analyzed to show the effectiveness of the proposed procedure. NOTATIONc parameter of leakage law [m 3Àγ /s] C d per-capita hourly water demand [m 3 /s/inhab.] d data vector [dimensions may vary] D node outflow [m 3 /s] G(·) symbolic operator of a generic mathematical model [dimensions may vary] L leak discharge [m 3 /s] m number of parameters [-] M parameter vector for G model [dimensions may vary] N 1 exponent of leakage law [-] n h number of hours in the time pattern [-] n mP total number of pressure stations [-] n mQ total number of flow stations [-] n u,i number of users supplied by i-th node [-] OF objective function [-] P node pressure head [m] P cross crossover probability [-] Q volumetric flow [m 3 /s] γ exponent of leakage law [-] SUPERSCRIPT k hour index SUBSCRIPTS 1 pertaining to network zone 1 2 pertaining to network zone 2 C computed i node index M measured 35

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