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One of the most important consequences of soil erosion is sedimentation. The detection and surveying the type and amount of sediment is important because of  its effects on irrigation networks, environment, and reservoirs. This study was performed in order to investigate the suspended sediment changes under the influence of rainfall erosivity cycle in Sorkhab- Keshvar watershed in the Lorestan province. For estimating the suspended sediment, we used a combination of sediment rating curve of mean loads within discharge classes and average daily discharge data. Monthly and semi-monthly EI₃₀-based erosivity indices were calculated in 13 rain gauging stations inside and around of the watershead. In the next stage, erosivity maps based on kriging interpolation were produced in order to calculate the average monthly and semi-monthly rain erosivities. After calculating monthly and semi-monthly sediment loads, their correlations with corresponding erosivities were investigated. The results show that the maximum and minimum of suspended sediment occured in Azar and Shahrivar (Iranian month equal to Nov. 22 to Dec. 21 and Agu. 23 to Sep. 22) with the values of 246216 and 1272 ton, respectively. Also, the maximum and minimum of rainfall erosivity occured in Dey (Iranian month equal to Dec. 22 to Jan. 20) and summer respectively with the values of 182 and 0.01 MJmm h^-1.The highest values of semi-monthly erosivity and sediment observed in second half of Dey and Azar (Iranian month equal to Dec. 22 to Jan. 20 and Nov. 22 to Dec. 21) with the values of 104 MJmm h^-1 and 148241 ton, respectively.Sediment and erosivity showed two peaks in the watershed, two peaks of sediment occured in Azar and Farvardin (Iranian month equal to Nov. 22 to Dec. 21 and Mar.21 to Apr. 20) and for the reosivity occurred in Dey and Farvardin (Iranian month equal to Dec. 22 to Jan. 20 and Mar.21 to Apr. 20).

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Soil erosion and watersheds sediment yield, due to improper management and unprincipled exploitation of natural resources, is greater than allowable amounts in Kermanshah Province. To correct these problems, watershed management operations, in vast area and volume, are implemented. This study was conducted to evaluate the effects of biological and mechanical watershed management operations on erosion and sediment yield controlling of Hajiabad-e-kangavar watershed. Watershed management operations included Gabions and check dams, storage channels, and cultivation of almond and   grapevine. Assessment of variation of range condition and vegetation diagnosis accompanied by variation of soil erosion and sediment yield using MPSIAC and sediment volumetric was done. The results showed that planting operation in h_-int sub-watershed and seeding almond and grape in h5-1 unit, while improving vegetation biomass production in about 100 kg/ha, it also reduced erosion and sediment yield about 15 and 8 %, respectively. Also, in h2 unit, that the dominant erosion aspect was bank erosion, Gabion and check dam reduced soil erosion and sediment yields about 13%. Additionally, reducing about 5% of soil erosion and sediment yield in h8 unit contributed to execute biological operation of planting in this unit. Finally, biological and mechanical watershed management operations, in the entire sub-watersheds, were able to reduce erosion at the rate of one percent, over a period of 3 years after implementation. Main causes that lowered the efficiency of watershed management operation were the lower potential of erosion rate and sediment yield of this watershed.
 

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Environmental flow is explained as the period of time, quantity and the amount of required water for maintaining the water, fresh, the river’s ecosystem, human beings’ welfare and the life depending on the water. The main goal of this paper is to investigate and compare the hydrological methods including Tennant, aquatic flow, Tessman, analysis of the flow duration curve and the flow duration curve shifting (FDC shifting) in determining environmental flow of two rivers from two different prime basin of Iran, Karaj and Talar rivers with data of 59 and 63 years, respectively. According to the results, the flow duration curve shifting approach for its consideration to different ecological classes, attention to natural flow shifting and the efforts of maintaining this shifting in its own suggested environmental flows, has priority over other approaches and it is also more precise in comparing with others. Therefore, the environmental needs of Karaj and Talar rivers in the classification of environmental management C (the preservation of river’s least environmental condition) are assessed equal to 4.77 m3/s which is 38 percent of the average annual flow and 1.81 m3/s, equal to 24 percent of the average annual flow of each river, respectively.

 

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In recent decades, low-yielding rainfed farms have become known as the main sources of sediment production and soil erosion in the country. Therefore, more research is needed on the factors affecting erosion and sediment production in these areas. This research was carried out with the aim of studying the effects of slope and rainfall intensity on erosion between rainbow trout in test farms in Kermanshah provinces using field descendant simulator. In a preliminary study, the erosion situation in the high slope drilands of the province was studied by field observations. Then, in some representative fields (in terms of erosion, slope and climate class), the status of erosion and agronomic management and its components were examined and soil sampling was carried out. 11 farms were selected in the current management conditions and in the dominant slopes (10 to 30%), and rainfall simulator test were performed in these farms and erosion and runoff were measured. The results showed that in sloping fields, the percentage of crop residue and slope, respectively, significantly controls the process of runoff production and soil erosion.

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Zoning of gully erosion susceptibility and determining the factors controlling gully erosion is very important and vital. The aim of this study was to investigate the spatial distribution of gully erosion using two models of ANN and MaxEnt and to determine the factors affecting this type of erosion in Golestan Dam basin. Therefore, 14 factors in the form of three divisions, including topographic factors, other factors and combination of factors (14 factors) were considered as predictors of sensitivity. Out of 1042 gully erosion points, 30 and 70 percent were randomly classified as validation and test data, respectively. The results of Jackknife test showed that the parameters of height, rainfall and depth of valley are the most important variables affecting the prediction of gully erosion. The results of the modeling showed that the best accuracy of the model based on the ROC curve in the training model (0.923) and in the validation, stage (0.902) was the artificial neural network model, and this condition is achieved when all the factors in the modeling be involved. According to this model, about more than 20 percent of the domain (45633 ha) has a high sensitivity and is very susceptible to gully erosion.

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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.