جستجوی مقالات مرتبط با کلیدواژه "روابط تجربی" در نشریات گروه "آبخیزداری، بیابان، محیط زیست، مرتع"

One of the landscape management approaches is the construction of bridges along the rivers. On the other hand, the bridge scouring is a serious damage to river engineering as the main source of water and sustaining planet life. Accordingly, in this research, using field data, the accuracy of empirical methods, genetic algorithm (GA), least squares support vector machine (LSSVM), and combined method were compared in estimating scour depth of simple bridge piers. In the GA method, a number of empirical relationships were modified and the results of these modified relationships were compared with the measured scour values. In the LSSVM method, through the input of different independent parameters, model training was performed, and scour depth was predicted. In the combined method, using the LSSVM model from combining the results of different individual relations, the scour depth of the bridge piers was estimated. The results showed that modified relationships by genetic algorithm and LSSVM model have higher accuracy than empirical methods. Also, if only the parameters used in the empirical relationships are included as input parameters to the LSSVM model, the modified relationships have less error than the LSSVM model. The statistical evaluation criteria of RMSE, E, R2, and NSE for the best state of the combined method were 0.4 m, 49%, 0.88, and 0.58 respectively in the training stage and 0.52 m, 50%, 0.7, and 0.38 respectively in the test stage. In general, the combined method estimates scouring depth with higher accuracy than other methods.

Estimation of sediment bed load is one of the most important issues in river engineering. Accordingly, several methods and relations have been proposed to estimate the bed load in streams for the past decades. The present research aimed to select the most accurate method to estimate bed load through the testing of various relations to estimate the bed load of the Hablehroud River. The hydraulic and geometric specifications of the Hablehroud River at Bankouh hydrometry station were measured on specific dates by the expert team. The bed load rate was calculated by four different relations in Bankouh hydrometry station from 2011 to 2017. Resultant data showed that the Toffaletti method with RMSE, MAE, and R2 of 20.07, 10.86, and 83 estimates more accurate in comparison with other methods. The sensitivity analysis of the Toffaletti equation revealed that the bed load depends greatly on the velocity of the river flow. Such a method is firmly recommended to use in the mountainous region.

Hydraulic conductivity is an important parameter for the control of water flow through porous media. Hence, accurate estimation of the parameter is important for evaluating of flow exchange between surface water and groundwater. In this study, 12 empirical formulae based on grain-size and 4 infiltration equations were used for estimating hydraulic conductivity on 3 sites in Jarmeh flood spreading system, Khuzestan Province. Results were evaluated using measured hydraulic conductivity by double rings infiltrometer. The results of the empirical formulae showed that 9 formulae were overestimated or underestimated and 3 formulae were close to measured values. Hazen formula give the largest overestimation and Slitcher formula give the largest underestimation and Shepherd formula is the best one. Generally, in order that the empirical formulae to be applicable, the C coefficients should be calibrated. The results of the infiltration equations showed that all of 4 equations were successfully estimated hydraulic conductivity and there are no significant differences between them. Among the equations, Kastiakov and Green-Ampt were the best of them.

Estimated time of concentration is one of the most important topics in the study of watershed physiographic and hydrology and relatively accurate estimates of that effects on other hydrologic parameters, including peak flood discharge. Despite numerous empirical formulas and widespread application in Iran, up to now a study hasn’t been done about the best relationship and important physiographic parameters and the effectiveness of theirs increasing or decreasing of concentration time, in Gheshlagh Dam basin. So in this study, in addition to study the sixteen relationship of concentration time that have extensive application in our country, a method was presented for the path coefficient analysis of important physiographic parameters of concentration time. In this regard, first Using real-time concentration of trace amounts of dissolved salts, the accuracy of concentration time was assessed by RMSE and MRE statistics methods and the best empirical equations was selected. Then using the Path Analysis method, direct and indirect impact of ten important parameters of basin on concentration time was determined. The results showed that in Gheshlagh Dam basin between investigated relationships, California and Bransly Williams formulas are the best equations for estimate time of concentration (mean error relative to 41.1 and 43.5 percent). Also Chaw and Janson kroos have mean and acceptable result (mean error relative fewer than 57%). The path analysis results also showed that the stream length parameter have the most positive effect (1.10) the area of basin have the most negative effect (-0.257) on time of concentration.

Studies of river engineering and River cross structures design such as bridges, diversion dams, Water Intake, etc. have closely related with the accurate calculation of depth, flow velocity and it has estimated moment of maximum flood discharge. The Estimated of flow velocity is important in hydraulic and hydrology studies .where no enough measured data is available, empirical approaches are usually applied to estimate flow velocity and maximum flood discharge. The most of these methods have been proposed for a certain area with specific physical and climatic conditions .to use these methods in other areas with different conditions ,evaluation and analysis of sensitivity of their parameters seems to be necessary. In this research ,new simple and efficient method is used to carry on sensitivity analysis of 2 flow velocity estimation methods including Manning and chezy that both of them are the most famous flow velocity existing. The results show chezy empirical equation is more sensitive Manning equation in estimating flow velocity. At the Manning equation, Model sensitivity is more to the less roughness values and when the energy line slope value (surface water) is high, flow velocity sensitive is increases. In other word, small changes in high slope, the flow velocity has changed dramatically. Sensitivity of Output’s model to hydraulic radius parameter is higher than while the area of catchment increases. Results show that roughness coefficient (c) in chezy equation is the most sensitive parameter and it need to more attention and correction.