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This paper describes a mathematical model which solves the 1D unsteady flow over a mobile bed. The model is based on the Richtmyer second-order explicit scheme. Comparison of the model results with the experimental fume data for alluvial steady flow (aggradation due to overloading) and unsteady flow shows that, by using the two-step method of Richtmyer, one can solve the equations, governing the phenomenon, in a coupled method with the desired accuracy. Firstly, the Badalan reach located at the Aland River is considered. Variations of flow rate, water level and bed level profiles due to flood hydrographs are assessed. Secondly, bed load discharge data were collected from the Aland River and a variety of bed load discharge formulae were compared with measured data. Results show that, by using the grain size of the bed surface layer to predict the bed load discharge, a larger relative error will occur compared to the other two cases and a proper choice of grain size has the main role in reduction of the relative error of bed load discharge estimation in gravel bed rivers. The applicability of formulae varies depending on flow rate, and should be split into low and high flow transport formulae. [ABSTRACT FROM AUTHOR]

Heuristic search techniques are highly flexible, though they represent computationally intensive optimization methods that may require thousands of evaluations of expensive objective functions. This paper integrates MODSIM, a generalized river basin network flow model, a particle swarm optimization (PSO) algorithm and artificial neural networks into a modeling framework for optimum water allocations at basin scale. MODSIM is called in the PSO model to simulate a river basin system operation and to evaluate the fitness of each set of selected design and operational variables with respect to the model's objective function, which is the minimization of the system's design and operational cost. Since the direct incorporation of MODSIM into a PSO algorithm is computationally prohibitive, an ANN model as a meta-model is trained to approximate the MODSIM modeling tool. The resulting model is used in the problem of optimal design and operation of the upstream Sirvan river basin in Iran as a case study. The computational efficiency of the model makes it possible to analyze the model performance through changing its parameters so that better solutions are obtained compared to those of the original PSO-MODSIM model. [ABSTRACT FROM AUTHOR]