Cite this paper:
EL ALAOUI EL FELS Abdelhafid, ALAA Noureddine, BACHNOU Ali. Use of genetic algorithm in new approach to modeling of flood routing[J]. HaiyangYuHuZhao, 2019, 37(1): 72-78

Use of genetic algorithm in new approach to modeling of flood routing

EL ALAOUI EL FELS Abdelhafid1, ALAA Noureddine2, BACHNOU Ali1
1 Laboratory of Geosciences and Environnement, Department of Earth Sciences, Faculty of Science and Technics Gueliz, (P. B. 549), Cadi Ayyad University, Marrakech, Morocco;
2 Laboratory Applied Mathematics and Informatics, Department of Math and Informatics, Faculty of Science and Technics Gueliz, (P. B. 549), Cadi Ayyad University, Marrakech, Morocco
Abstract:
The hydrological models and simplified methods of Saint-venant equations are used extensively in hydrological modeling, in particular for the simulation of the flood routing. These models require specific and extensive data that usually makes the study of flood propagation an arduous practice. We present in this work a new model, based on a transfer function, this function is a function of parametric probability density, having a physical meaning with respect to the propagation of a hydrological signal. The inversion of the model is carried out by an optimization technique called Genetic Algorithm. It consists of evolving a population of parameters based primarily on genetic recombination operators and natural selection to find the minimum of an objective function that measures the distance between observed and simulated data. The precision of the simulations of the proposed model is compared with the response of the Hayami model and the applicability of the model is tested on a real case, the N'Fis basin river, located in the High Atlas Occidental, which presents elements that appear favorable to the study of the propagation. The results obtained are very satisfactory and the simulation of the proposed model is very close to the response of the Hayami model.
Key words:    Genetic Algorithm|flood routing|Hayami model|simulation|propagation   
Received: 2017-11-11   Revised: 2018-02-22
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