Mitra Tanhapour; Mohammad Ebrahim Banihabib
Abstract
Prediction of the sediment load in water resources engineering projects such as flow diversion projects and dam construction is important factor for determining their service life. In this study, a model for estimation of daily sediment discharge was proposed using multilayer perceptron Artificial Neural ...
Read More
Prediction of the sediment load in water resources engineering projects such as flow diversion projects and dam construction is important factor for determining their service life. In this study, a model for estimation of daily sediment discharge was proposed using multilayer perceptron Artificial Neural Network (ANN) model with back-propagation learning algorithm. For this purpose, current day’s discharge (Qt), precipitation, number of day in the year (DOY) and previous day’s discharge (Qt-1) data of Zoghal Bridge station (located on Chalus River) from 1990 to 2009 were used for training, verification and test. Results of testing different combinations of input data sets showed that effective parameters of the model performance are current discharge parameter, antecedent discharge, precipitation and DOY, respectively. This results has a relatively good agreement with standardized coefficients of regression model. Coefficient of determination (R2) and Root Mean Square Error (RMSE) were used to compare the different structures of ANN. Therefore, best network with 3-5-1 architecture and the amounts of R2=0.89 and RMSE=0.02 was obtained by elimination of DOY variable. The performance of ANN model in the prediction of sediment discharge was compared with Sediment Rating Curve (SRC) and Multiple Non-Linear Regression (MNLR) model. The results showed, in the training and test steps, SRC method and ANN model have the best performance, respectively. Furthermore, in the test step, the ANN model performed better results compared to two other methods by increasing R2 about 16%. Generally, the proposed ANN model can be estimated sediment discharge by less calculation time and cost and also with more accuracy.
Hamidreza Peyrowan; Mohsen Shariat Jafari; Dadvar Lotfollahzadeh
Abstract
The study performed to determine the relationship between landslide and increasing sediment load in Latian dam watershed. Sediment yield of six sub-basins were estimated with by two methods of MPSIAC and hydrometric station . More than 150 landslides were mapped by ETM+ and Google Earth image processing. ...
Read More
The study performed to determine the relationship between landslide and increasing sediment load in Latian dam watershed. Sediment yield of six sub-basins were estimated with by two methods of MPSIAC and hydrometric station . More than 150 landslides were mapped by ETM+ and Google Earth image processing. Comparing the observed data with MPSIAC output in Lavasanat and Kond-Afjeh sub-catchments, it became clear that Lavasanat has less sediment yield. But, despite of this subject, observed sediment yield in Lavasanat hydrometric station is about two times in Kond–Afjeh, while the landslides area in Lavasanat and Kond–Afjeh sub-basins are 1.8 and 0.7 percent of the area. Based on the estimated sediment yield of MPSIAC model, the weighted average of specific sediment yield for Kond-Afjeh and Garmabdar sub–basins with landslide area of 0.7 and 2.4 percent are 387.02 and 431.39 m3km-2y-1 respectively, which means that increasing the relative percentage of landslide area from 0.7 to 2.4 percent, specific sediment yield increases by 11.5 percent. Based on data analysis in Roodak hydrometric station in Jajrood basin, average sediment discharge of the river in the first nine months of 1383 before Hajyabad landslide was 6.17 tons per day that increased to an average of 16.9 tons per day at nine months after landslide. This amount is equivalent to 170 percent increasing of sediment load in nine months after mentioned event. The interesting point is that this increasing of sediment yield was in the period of about 30% decrease in water debit . This means that not only increasing sediment yield of the river is not related to the water debit, but also, about 30% reduction of water debit is should reduce sediment yield. So, regarding to the area of 20.45 ha of Hajabad landslide zone, each hectare of landslide area could increase more than 8% of the sediment load in the river.
Soheyla Aghabeigi; Abdol Rasoul Telvari; Sayed Khalagh Mirnia; Sadat Feiznia; Mehdi Vafakhah
Abstract
Sediment concentration in rivers, especially in seasonal ones, is affected by flood situation due to changes of rainfall or snowmelt events. Due to the importance of flooding flows in inundation and the useful age of reservoirs built on seasonal rivers, the study and assessment of this issue seems to ...
Read More
Sediment concentration in rivers, especially in seasonal ones, is affected by flood situation due to changes of rainfall or snowmelt events. Due to the importance of flooding flows in inundation and the useful age of reservoirs built on seasonal rivers, the study and assessment of this issue seems to be essential. In the present research, suspended sediment concentration variation in spring and autumn floods and runoff from snowmelt in spring, have been studied for Abshine River in Ekbatan Dam Watershed. Over the forecast period, three storms in autumn, two storms in spring and five snow melt events were selected and compared. Analyzing 226 suspended load samples showed its variability in the area. Sediment rating curves in different base times showed different trends. The correlation coefficient (r) were 0.79 and 0.50 for storms and snowmelts and 0.81 for all data, respectively. Also, coefficient and power value analysis of sediment rating curve, presented the same erodibility for hill slope in both seasons (spring and autumn). Separating falling and rising limbs of flow hydrograph and assessing their effect on discharge explains a better Q-sediment concentration relationship. The hysteretic shape of discharge and sediment concentration had clockwise and anticlockwise form and compound pattern of both forms that reflected the distribution of probable sediment sources throughout the catchment.
Hossein Rastgar; Mehdi Habibi
Abstract
Sedimentation is one of the most important problems in watershed management. The characteristics of geological formations are the most basic factors which have an important role in sediment yield. There are several methods for sediment estimation, but sediment transport equations and formulas have been ...
Read More
Sedimentation is one of the most important problems in watershed management. The characteristics of geological formations are the most basic factors which have an important role in sediment yield. There are several methods for sediment estimation, but sediment transport equations and formulas have been developed for special conditions which may not represent all conditions. Therefore to find out which method is suitable for a specific river, it is required to compare each method with the measured data. The purpose of this research is to evaluate efficiency of different methods of sediment discharge estimation in Jagin River at Panhan hydrometric station. The methods of modified Einstein, Engelund-Hansen, Yang, Habibi and Van Rijn are used in this investigation. The required data was collected from Water Regional Organization of Hormozgan Province. The sediment yield is estimated based on concentration of collected samples of floodwater. Then, the collected data were checked and corrected. The conclusion shows that the modified Einstein method is the most suitable method for sediment estimation in the study area.
Jafar Dastoorani; Ali Fazlollahi; Ali Salajeghe; Ghasem Dastoorani
Volume 2, Issue 3 , October 2010, , Pages 133-142
Abstract
Effective discharge (Qeff) that transports the most of suspended sediment in rivers and controls the bed conditions is an important criterion for evaluating the quality of water. Qeff usually has 1.5 years recurrence interval on the yearly maximum flood data series. For examining similarity between Qeff ...
Read More
Effective discharge (Qeff) that transports the most of suspended sediment in rivers and controls the bed conditions is an important criterion for evaluating the quality of water. Qeff usually has 1.5 years recurrence interval on the yearly maximum flood data series. For examining similarity between Qeff and Q1.5 in ten stations of Daryacheh Namak Drainage Basin, at first the probability density function (pdf) of daily flows and sediment rating curves was plotted, after that probability density function of suspended sediment was constructed by multiplying the coefficient of sediment rating curves with pdf of daily flows. Then its recurrence interval was estimated by Vibul's method. The results showed that there are not any similarities between Qeff and Q1.5, and the ratio of Qeff to Q1.5 ranged from 1.03 to 16.8. Therefore more research is required to reach more certain result.
