جستجوی مقالات مرتبط با کلیدواژه « Karaj Dam » در نشریات گروه « کشاورزی »

Karaj dam basin in Alborz province is prone to destructive floods given to its special topographic and anthropogenic conditions. The purpose of this study is to determine the areas with flood susceptibility potential and prioritize the factors affecting it using the maximum entropy method. 14 factors affecting flood potential selection and linear testing Factors were analyzed by variance inflation factor. Out of a total of 47 flood points, 70 percent were randomly classified as training data and 30 percent as validation data. The Jackknife test was also used to determine the important factors. The ROC curve was used to predict the model. The results showed that there is no alignment between the factors used and therefore all factors were used in the modeling process. The results showed that according to the Jackknife test, DEM, distance from the stream and rainfall were the most important factors affecting the susceptibility of floods, respectively. Based on the area under the curve and ROC diagram, the accuracy of the model prediction was higher in the higher training sector (0.925) and good in the accreditation sector (0.717). According to the final flood susceptibility map, 22.41 percent of the study area has a moderate to high flood susceptibility potential.

Area-Reduction method is one of the experimental methods to determine sediment distribution in dam reservoirs. In this method reservoir on the base of geometrically are divided into four types, and sediment distribution in each reservoir type are on the base of the parameter that is given in each reservoir type. Results and researches were shown that in many cases; determining the type of reservoir with the Borland and Miller method didn’t lead to high accuracy. So, determining the optimized coefficient for Area-Reduction method can increase accuracy of sediment distribution prediction in this method. In this study initially a computer model based on Area-Reduction method was provided by using MATLAB software, then optimize model was prepared by using Ant Colony algorithm and this two models were combined. Best coefficients of Area-Reduction method for Karaj Dam were achieved by using this model. Results were shown that there was a significant increase in accuracy of sediment prediction using optimal parameters. Using the optimal parameters, values of objective function reduced up to 68.41%.

Dam construction on rivers can lead to sedimentation in reservoirs causing a lot of problems. Forecasting the amount and distribution of sedimentation is very important for the designers of the dam. The area reduction method is one of the experimental models to study the sedimentation in reservoirs. The parameters used in area reduction method have been obtained by Borland and Miller according to the study on 30 dams in America. It is necessary to obtain the optimal values of these parameters for the reservoir sedimentation in other areas. In this study, some models has been developed based on harmony search algorithm (HS) and its various improved algorithms such as IHS, GHS and SAHS in combination with area reduction methods for calculating optimal values of area reduction parameters. At first the accuracy of the developed models has been evaluated using standard functions and then Karaj reservoir sediment is estimated using developed model. Statistical comparisons of different improved methods and area reduction method with the actual sediment deposits in Karaj dam indicate high performance of developed models. Among these methods, the rate of error 90 percent has been reduced by combination of SAHS and HIS with area reduction method.

The phenomenon of sedimentation in dam reservoirs is the most important threatening factor in huge investment of capitals in hydraulic projects. Uncertainty analysis for each phenomenon shows the real view of its parameters and creates real understanding of the effective factors on the phenomenon. In this research, to estimate the volume of sediments in reservoir, using hydrometric and sediment data of Karaj River from 1961 to 2003, factors affecting sediment transportation and a model considering non-uniform sediment sizes. Then by using Monte Carlo simulation method and statistical input parameters, effective factors on sediment volume in reservoir, random input parameters and Latin square sampling method, some samples were obtained. At the end, the uncertainty of each parameter was introduced using statistical characteristics. The Results from uncertainty of annual sediment of reservoirs, expressed as coefficient of variations, was introduced as 56% Sensitivity analysis showed that annual mean flow rate and sediment rate were the most important factors in estimation of reservoir sediment volume.