JWSS - Journal of Water and Soil Science

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Development of precise and simple methods in flood simulation has greatly reduced financial damage and life loss. Various methods and procedures have been implemented based on Saint-Venant's one-dimensional equation governing unsteady flows. To simplify the solution for these flows, analytical and numerical methods have been used. In the present study, a new method that provides the optimal outcome is introduced using non-linear programming. Penalty function has also been used to convert nonlinear programming (NLP) constrained problems into unconstrained optimal issues. To verify the accuracy of decision variables, the study covered 60 cross-sections of Gharasu River and 25-year flood hydrographs. After determining the model correctness, the 50 and 100-year flood hydrograph were routed in 18 Kilometers. The results were statistically compared with hydraulic and Muskingum hydrological methods. To sum up the routed hydrographs introduced by NLP method were very close to the hydrographs produced by dynamic wave method. The R2 of calculated discharge of routed hydrograph by NLP and dynamic wave method were 0.948, 0.990, and 0.989, respectively, with the return period of 25, 50 and 100-year flood being 0.989. It can be concluded that NLP method is more accurate than Muskingum method, especially when predicting the peak discharge of flood hydrograph.

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Stage – discharge relationship is mainly developed from measured data in any hydrometry station. Measured data usually obtain in low to medium flow discharge, because in most cases it is very difficult to measure the flow discharge during flood. Therefore, the stage–discharge is extrapolated beyond the measured data to compute the flood which may estimate low or higher value. This is because during the high flow, the bed form is developed which causes the flow resistance to change. In order to establish a better stage – discharge relation, it is important to apply methods which consider the bed form resistance. In this study an attempt has been made to determine the best method for developing such relationship. To reach the goal, the required data such as river cross section, discharge and related stage and bed material gradation from Ghorbaghestan hydrometry station were measured for two years. Then a computer program was developed. Using this program and applying the measured data, the stage – discharge relationships were computed by five different methods. From the statistical comparison of the results of these methods with measured data, it was found that Shen, Brownlie, Engelund and White’s method overestimate the flow discharge. The best method was found to be the Einstein – Barbarossa’s method that provided the minimum absolute mean errors 0.31 and 1.468 m3/s and minimum root mean square error 0.112 and 0.466 m3/s for the two study years, respectively