Bahram Mir Derikvand; Alireza Sepahvand; Hossein Zeinivand
Abstract
In recent years, extensive practices have been done on flood control, erosion and sediment in the fields of research and implementation of watershed management. Therefore, the purpose of this study was to assess the effects of watershed management practices on the characteristics of runoff and suspended ...
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In recent years, extensive practices have been done on flood control, erosion and sediment in the fields of research and implementation of watershed management. Therefore, the purpose of this study was to assess the effects of watershed management practices on the characteristics of runoff and suspended sediment load in two subwatersheds in Ghaleh Gol watershed in Lorestan province, Iran. In this research, for comparing the effect of watershed management practices (WMP) on discharge and suspended sediment load (SSL) from both subwatersheds, the flow velocity was measured and the SSL was sampled directly from the beginning of the rainfall events until the end of them. Results showed that in all measurements, the discharge and suspended sediment load of the southern subwatershed with watershed management practices was higher than the northern subwatershed without such practices. According to the results of ANOVA test, it was found that the difference between discharge peak (P=0.691) and suspended sediment load peak (P=0.840) was not significant in two subwatersheds. Also, according to the results, the difference between specific discharge and specific SSL was not significant (P>0.05). Based on these results, it was found that the implementation of WMP in the study area apparently has no the required performance to reduce the discharge and SSL, and the WMP have lost their performance before the end of their useful life. Therefore, in order to increase the performance of mechanical watershed management practices (MWMP), the biological and biomechanical practices has to be performed simultaneously.
Aliakbar Nazari Samani; Aryan Salvati
Abstract
Having knowledge on the quantitative amount of watershed sediment yield is one of the most basic information to deal with soil erosion and conservation as well as design of dams. In Iran, the estimation of suspended sediment load is often based on measurement curve methods. Since sediment discharge data ...
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Having knowledge on the quantitative amount of watershed sediment yield is one of the most basic information to deal with soil erosion and conservation as well as design of dams. In Iran, the estimation of suspended sediment load is often based on measurement curve methods. Since sediment discharge data are random and discontinuous, in practice, their internalization and extrapolation is associated with many errors. This review is to evaluate the number of data available to estimate daily sediment load with Loadest regression models. Therefore, daily discharge data of Ghazaghli station in Gorganrood forest watershed were used. So that different percentages of available data were accidentally deleted and the amount of sediment load was estimated by 11 methods. According to the evaluation results (Taylor diagram), model number 2 has the best accuracy and in the absence of up to 50% of the daily sediment data, the correlation coefficient of more than 0/5 in the annual sediment estimation and only for the first year And in the rest of the years under study the correlation coefficient is unacceptable. Therefore, the use of sediment measurement curve methods with the data available at the level of Iranian stations, if the number of data available to construct the measurement curve is less than 185 will be associated with very little accuracy. Also, the higher the amount of available data belonging to the periods of low sediment transport (autumn and dry years), the lower the efficiency of the Loadest method will be.
aboalhasan fathabadi; Ali Salajegheh; hamid pezeshk; Aliakbar Nazari Samani; hamed rouhani
Abstract
In order to manage and implement conservational activities in watershed successfully, it is necessary to determine the sediment sources. In recent years, sediment fingerpering techniques have been used for estimating sediment sources contribution. With respect to small source samples, having many answer ...
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In order to manage and implement conservational activities in watershed successfully, it is necessary to determine the sediment sources. In recent years, sediment fingerpering techniques have been used for estimating sediment sources contribution. With respect to small source samples, having many answer as a result of over fitting, there are some uncertainties in estimated sources contribution. In this study, the uncertainty associated with the multivariate mixing model was estimated using Monte Carlo simulation and GLUE approach in Zidasht-Fashandak sub- watershed. The sediment and source samples were taken in the study area and then, 54 geochemistry and three organic characteristics were measured. 17 elements were also selected as optimum tracer composition using Kruskal–Wallis H-test and multivariate discriminate analysis. Meanwhile, sources contribution were estimated using multivariate mixing models. Results showed higher contribution of sub-surface sources than the surface resources. Also, the distance between lower and upper limits for all sources and resolutely uncertainty bands were high.
Hamide Afkhami; mohammad dastorani; farzaneh fotouhi firuzabadi
Abstract
Due to the nature of the sediment data, selection of appropriate methods for processing the data before entering them to the artificial intelligence models can enhance the reliability of simulations results. In this study, the effects of sediment data processing procedures on ANN and ANFIS models outputs ...
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Due to the nature of the sediment data, selection of appropriate methods for processing the data before entering them to the artificial intelligence models can enhance the reliability of simulations results. In this study, the effects of sediment data processing procedures on ANN and ANFIS models outputs in 7 Dez Basin stations were evaluated. Accordingly, three scenarios were considered: In the first scenario, original data was used without exerting any processing technique; in the second scenario, the data was normalized; and in the third scenario, logarithm of data were used according to logarithmic distribution governing. The simulation results showed that using data logarithm leads to higher performance and lower error, especially in stations where the best fit probability distribution is one of the log family distributions. Finally, among applied models, ANFIS showed the best performance with coefficient efficiency of 0.95 and RMSE of 5.4, MSE of 1.4 and ME of 0.42 in Biatoon gauging station and using the third scenario.
Seyed Hamidreza Sadeghi; Shirkouh Ebrahimi Mohammadi; Kamran Chapi
Abstract
The behavior of suspended sediment during flood events is not only a function of energy conditions, i.e. sediment is stored at low flow and transported under high flow conditions, but also is related to the variations in sediment supply and sediment depletion. These changes in sediment availability result ...
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The behavior of suspended sediment during flood events is not only a function of energy conditions, i.e. sediment is stored at low flow and transported under high flow conditions, but also is related to the variations in sediment supply and sediment depletion. These changes in sediment availability result in so-called hysteresis effects. Therefore, Hysteresis pattern analysis is of great importance in sediment studies in the watersheds. However, their analyses has been rarely considered. In this study, based on the discharge and sediment concentration data collected from 8 storm events occurred during March 2 011 to April 2012, event suspended sediment dynamics of 7 tributaries of the Lake Zarivar watershed was investigated using hysteresis patterns. Based on the fact that all sampling points were not active in all events, about 46 hysteresis patterns were obtained. The analysis of results showed that 16, 13, 11, and 6 events had clockwise, irregular, complex and counterclockwise patterns, respectively. Small tributaries of the Zarivar lake watershed showed the rapid responses to the variation of storm intensity and the most hydrographs of different storms were multi peak discharges and consequently high suspended sediment variations led to different hysteresis patterns. The diversity of patterns suggested that the detailed processes of sediment transport were not only complicated during one event but also varied from event to event. The reasonable and statistically significant relationship (p<0.05) between suspended sediment yield and peak discharge of each sampling point indicated that the data from all events may be statistically well described by a simple regression equation, regardless of different inter and intra-storm variations of the suspended sediment.
Elham Kakaei Lafdani; Ali Reza Moghaddam Nia; Azadeh Ahmadi; Heydar Ebrahimi
Abstract
This study aimed to examine the influence of pre-processing input variables by Gamma Test on performance of Support Vector Machine in order to predict the suspended sediment amount of Doiraj River, located in Ilam Province from 1994-2004. The flow discharge and rainfall were considered as the input variables ...
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This study aimed to examine the influence of pre-processing input variables by Gamma Test on performance of Support Vector Machine in order to predict the suspended sediment amount of Doiraj River, located in Ilam Province from 1994-2004. The flow discharge and rainfall were considered as the input variables and sediment discharge as the output model. Also, the duration of the model training period was determined through GT. Thereafter, in order to carry out the influence of pre-processing input variables on performance of model, the suspended sediment was predicted using SVM model while no pre-processing has been done on its input variables and the results were compared to each other. Results show the performance of the GT-SVM model in the test phase with minimum RMSE was equal to 0.96 (ton/day) and the maximum coefficient of R2 was equal to 0.98 between the predicted and actual values, was better than SVM model.
