Flood routing as an important part of food management is a technique for predicting the fow in downstream of a river channel or reservoir. Lumped, semi-distributed and distributed models have been devised in this regard. The convex and Att-Kin models are capable of simulating foods in single branches, while in reality, rivers and channels are multiple infows. The convex and modifed Att-Kin models as the simplest lumped models in terms of the storage equation were developed based on an equivalent infow for routing the multiple infows rivers in the present study. The genetic algorithm, a quite robust algorithm, was used for parameter estimation of the extended models. The ability of the extended models in simulating the outfow hydrograph of multiple infows systems was tested on two multiple infows case studies. The results of extended models were compared with the equivalent Muskingum infow model. Comparison of the extended models with the Muskingum model showed that the extended models with one parameter less than the Muskingum model could be suitable for use in food routing of multiple infows systems. The efect of infow hydrographs at diferent time steps was investigated by the principal component analysis (PCA) and reliability analysis. The results showed that the outfow hydrograph of the case study was precisely simulated and predicted by the gene expression programming (GEP) and multilayer perceptron (MLP) models. The PCA and reliability analysis results were adopted for the lumped, GEP and MLP models. The outfow hydrograph was precisely simulated and predicted by the GEP and MLP models, while the precision of lumped models (extended convex, extended modifed Att-Kin and Muskingum models) was not increased.
Simple flooding algorithms are widely used in ad hoc sensor networks either for information dissemination or as building blocks of more sophisticated routing protocols. In this paper a percolation driven probabilistic flooding algorithm is proposed, which provides large message delivery ratio with small number of sent messages, compared to traditional flooding. To control the number of sent messages the proposed algorithm uses locally available information only, thus induces negligible overhead on network traffic. The performance of the algorithm is analyzed and the theoretical results are verified through simulation examples.
In this paper, the conservative properties of the Muskingum equation, commonly applied to solve river flood routing, are analysed. The aim of this analysis is to explain the causes of the mass balance error, which is observed in the numerical solutions of its non-linear form. The linear Muskingum model has been considered as a semi-discrete form of the kinematic wave equation and therefore it was possible to derive its two non-linear forms. Both forms were derived directly from the kinematic wave equation. It appeared that depending on the assumed conservative form of the Muskingum equation, this model satisfies either the global mass conservation law or the global momentum conservation law. Both laws are satisfied simultaneously by the linear equation only. The mass balance error can be eliminated from the numerical solution on condition that the non-linear Muskingum equation is written in the proper conservative form.
In contrast to direct downstream routing of flood flows, the complementary problem of reverse upstream routing is ill-posed and the calculations are subject to instability. However, the reverse routing procedure is useful both in irrigation management and in the control of flash floods by upstream reservoirs. Systematic study of reverse routing in uniform channels reveals a number of features that could prove of value in optimising such procedures.
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