Shahram Khalighi Sigarodi; Mohammad Rostami Khalaj; Mohammad Mahdavi; Ali Salajegheh
Abstract
Large impervious surfaces and man-made waterways are the characteristic of urban area. Increasing urbanization and rapid growth of cities in recent decades towards the upstream watershed, has been severely affected on rainfall-runoff processes in urban area. Therefore, to computer models in order to ...
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Large impervious surfaces and man-made waterways are the characteristic of urban area. Increasing urbanization and rapid growth of cities in recent decades towards the upstream watershed, has been severely affected on rainfall-runoff processes in urban area. Therefore, to computer models in order to illustrate these processes the proper design or assessment of urban drainage systems has special attention. The purpose of this study is simulation and validation the volume of runoff and calibrated SWMM model in small urban area. Required parameters of the model using land use maps, DEM of study area, and field inspection were calculated. For calibration and validation process model, corresponding to three event rainfall runoff measured at the output of the basin and was compared with runoff simulated by the model. The results showed there is good agreement between simulated and observed runoff discharge and depth. There is a little difference between simulated and observed for runoff rate but this difference is more than acceptable value (NS>0.5). NS value for the first, second and third event is the, 0.69, 0.85 and 0.52 respectively. This performance represents that the SWMM model is effective in the study area and this model can be used for in appropriate designs, and evaluate network systems in urban drainage.
Khaled Osati; Ali Salajegheh; Mohammad Mahdavi; Paul Koeniger; Kamran Chapi; Arash Malekian
Abstract
Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic ...
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Within the climate change debate and its probable impacts on water resources systems, design and operation of management plans based on the assumption of stationary hydrology may cause serious challenge to accurately predict future supplies. Therefore this case study is trying to assess trend in hydroclimatic variables of Karkheh Rivers upstream by applying modified Mann-Kendall trend test on long term daily time series of temperature, precipitation and discharge. Temperature variables are mostly showing meaningful increasing trends but observed changes in assessed stations were not spatially uniform for precipitation. Streamflow variables depict a decreasing trend, though more noticeable in base flows. Decreasing trend is meaningful for annual discharge median in Holailan at 90% confidence level. Total yearly precipitation, number of precipitation days and number of days with precipitation equal to, or greater than, 10 mm/d show the most correlation with stream flow variables. Comparing monthly discharge with temperature and precipitation variables in the studied gages indicates a time-delay in system response to inputs. This may related to snowmelt contributions or contributions of water into streams after passing through different hydrological pathways such as groundwater. Some parts of streamflow changes, especially about base flows, is not completely verified by precipitation changes and can be attributed to changes in temperature or another factors such as groundwater overexploitation.
farshad soleimani sardou; Ali Salagegh; Mahdie Sanjari; Ali Azare
Abstract
Nowadays, designing hydraulic structures for flood damage mitigation has a significant importance in water engineering. One of the necessary parameters for the design of flood control measures is the probable maximum 24-hour precipitation in a 1000-year return period. This research was done using Jiroft ...
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Nowadays, designing hydraulic structures for flood damage mitigation has a significant importance in water engineering. One of the necessary parameters for the design of flood control measures is the probable maximum 24-hour precipitation in a 1000-year return period. This research was done using Jiroft Halilrud watershed data to evaluate Hershfild methods. Firstly, the maximum annual precipitation data series were used to do a frequency analysis using linear moments method to determine the maximum precipitation in 1000-year return period. Then this parameter was determined using the Hershfild method. The results showed a good agreement between the two methods according to correlation coefficient (0.87). The results of this research can be used for the monitoring system of the region
Ali Golkarian
Abstract
Erosion is one of the important factors in soil degradation and decrease fertility and slope length is one of the most effective factors in land form and amount of erosion. The objective of this study was investigation of spatially variation of sediment concentration in slope length until to receive ...
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Erosion is one of the important factors in soil degradation and decrease fertility and slope length is one of the most effective factors in land form and amount of erosion. The objective of this study was investigation of spatially variation of sediment concentration in slope length until to receive transport capacity. To obtain this goal a hill slope simulator system designed and manufactured. This system include 10 flumes, each has five meter length which after series them become fifty meters. This system can produce cumulative flow via fifty watering can tube which are install on flumes with one meter interval and each flume discharging is 100 cc. Other variables include two type of soil and slope in three level 15, 22.5, 30 percent. Three replications were used for each treatment and totally 18 experiment was done. In each experiment four samples were gathered from end of each flume and concentration was determined. Complete randomized design with factorial arrangement was used for data analyzing. Richard’s function was used for fitting a suitable curve on observed data. Result was shown that effect of soil type on sediment concentration was not significant while slope and slope length effects was significant. Otherwise sediment concentration in the two last flumes was located in same class which is shown that sediment concentration achieved to transport capacity in this slope length. Also results were shown that Richard’s function can simulate trend of concentration variety in slope length.
ali shahbazi; Shahram khaliqi sygarodi; Arash Malekian; Ali Salajegheh
Abstract
In order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. Time of concentration is one of factors that impacts on peak discharge and runoff volume. The objective of this study ...
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In order to decrease the risks associated with the management of urban watersheds, the use of proper methods is an essential task to estimate the runoff with a high degree of confidence. Time of concentration is one of factors that impacts on peak discharge and runoff volume. The objective of this study is to select the best method among the empirical formulas for estimating the time of concentration. In this study, for determination of actual time of concentration, the field method based on measuring the travel time by using floating-object method was employed. To select the best empirical formula of the time of concentration, the statistical criteria including percentage Relative Error (RE), Root Mean square error (RMSE), Average percentage Relative Error (RME), Nash - Sutcliffe criteria (NS) and determination coefficient were used. Then, differences among the estimations obtained from empirical equations were compared with the actual values. The results of this study based on comparison of the relative error in each interval showed that in the reach No. 2, empirical formulas of California, Chow, Carter and Federal Aviation, with percentage error of 2.7, 2.9, 4.4 and 4.4 have showed the best estimation, respectively. The equation proposed by Kirby with percentage error of 1 in the reach No. 3, the equation of Ventura with percentage error 8.5 in the reach No. 9 and the equation of rational hydrograph with percentage error 4.8 in the reach No. 10 have showed the best estimates. Therefore, it is recommended to use the empirical formula that has the lowest percentage of error for areas with features similar to the studied reaches. In general, the results show that only rational hydrograph method in all of the reaches has the lowest error and then provides the most proper estimates compared than others.
Haji Karimi; Fathollah Naderi; Behrooz Naseri; Ali Salajeqeh
Abstract
Distinguishing the susceptible areas to landslide using different landslide susceptibility mapping (LSM) models is one of the primitive and basic works to reduce probable damages and reduce risk. The main purpose of this research is the efficiency evaluation of four methods including Information value ...
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Distinguishing the susceptible areas to landslide using different landslide susceptibility mapping (LSM) models is one of the primitive and basic works to reduce probable damages and reduce risk. The main purpose of this research is the efficiency evaluation of four methods including Information value (WINF), Valuing area accumulation (Wa), Analytical Hierarchy Process (AHP), Kopta-Joshi proposed method (LNRF) for LSM in Zangvan watershed, Ilam province. At first, all the effective factors in landslide occurrence were inspected. By analyzing the parameters, nine factors including slope, aspect, elevation, precipitation, distance from road, distance from fault, distance from drainage, land use and lithology were distinguished as the effective factors in landslides occurrence in the studied area. After preparing the information of these nine factors in GIS environment, the location of landslides were determined using areal photographs and satellite images and LSM performed by the above four methods. Finally, the landslide index was used for evaluation the ability of appropriate LSM model. Based on this Index, the information value method classified more 52 percent of occurred landslides in very high danger class. Therefore, this method is more efficient and proposed as the best LSM method in the Zangvan watershed because of compatibility of landslides with high danger classes and ability of differentiation of danger classes.
Ommolbanin Bazrafshan; Ali Salajegheh; Ahmad Fatehi; Abolghasem Mahdavi; Javad Bazrafshan; Somayeh Hejabi
Abstract
Drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. This paper presents the performances of autoregressive integrated moving average (ARIMA), Direct multi-step neural network (DMSNN), ...
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Drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. This paper presents the performances of autoregressive integrated moving average (ARIMA), Direct multi-step neural network (DMSNN), Recursive multi-step neural network (RMSNN), Hybrid stochastic neural network of directive approach (HSNNDM) and Hybrid stochastic neural network of recursive approach(HSNNRM) with time scale monthly and seasonally for hydrology drought forecasting and SDI selected as predictor in the Karkheh river basin. The results shown performances of HNNDA was found to forecast hydrological drought with greater accuracy for SDI forecasting, so performances model in monthly scale was greater accuracy to seasonality scale.
Samaneh Razavizadeh; Ali Salajegheh; Shahram Khalighi Sigaroudi; Mohammad Jafari
Abstract
Land use change is one of the main factors in the process of changing the regime of flood in watersheds. Taleghan watershed has been subjected to many land use changes over years, which probably effects on flood characteristics of Taleghan River. In present study the effects of land use change on some ...
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Land use change is one of the main factors in the process of changing the regime of flood in watersheds. Taleghan watershed has been subjected to many land use changes over years, which probably effects on flood characteristics of Taleghan River. In present study the effects of land use change on some parameters including peak flow, volume and flood base time, in part of Taleghan basin, was investigated by using Geographical Information System (GIS) and HEC-HMS model. Land use maps of 1987 and 2002 were prepared and integrated with soil hydrological groups and pasture conditions maps in GIS with the aim of providing of CN map. Then by using curve number and SCS unit hydrograph in sub basins and also Muskingum routing method, HEC-HMS model was calibrated and validated, for 10 incident rainfall - runoff views. Results of the simulation showed that due to the changes in land use (the reduction in the level of agricultural lands and increases in pasture areas), peak flow and flood volume in 2002 than in 1987 showed the average reduction of 46% and 34%, respectively. The evaluation of base time of flood showed no change in the parameter in flood hydrograph at the study period. On the whole the results showed that the trend of land use changes have the positive effect on reducing flood productions in study area.
Asghar Zare Chahouki; Ali Salajegheh; Mohammad Mahdavi; Sharam Khalighi; Said Asadi
Abstract
A flow-duration curve (FDC) illustrates the relationship between the frequency and magnitude of streamflow. Applications of FDC are of interest for many hydrological problems related to hydropower generation, river and reservoir sedimentation, water quality assessment, water-use assessment, water allocation ...
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A flow-duration curve (FDC) illustrates the relationship between the frequency and magnitude of streamflow. Applications of FDC are of interest for many hydrological problems related to hydropower generation, river and reservoir sedimentation, water quality assessment, water-use assessment, water allocation and habitat suitability. This study was carried out in 11 selected watersheds with common characteristics such as the 20 years period, the minimum land use change and similar annual water volume through all watersheds in 3 province of: Yazd, Semnan and Markazi which are located in central zone of Iran to regional flow duration curve. It was extracted Q5, Q10, Q20, Q30, Q40, Q50, Q60, Q70, Q80 and Q90 from 11 Hygrometric stations as a dependent variable were derived from flow duration curve. The flow duration curve is regionalized by using morphoclimatic characteristics of the drainage basin. Using multiple regression techniques, the geographic variation of each parameter of the best fitted flow duration model is explained in terms of the drainage area, length of longest flow, Stream slope, mean annual areal precipitation, course from the divide of the basin to the site of interest. The regionalized nonlinear regression equations are successfully used to flow duration curves at other locations within the hydrologically homogeneous regions of center of Iran. A cross-validation Nash–Sutcliffe Efficiency procedure was used to evaluate best fitting of the regional model in ungauged watershed.
Kh. Osati; A. Salajegheh; S. Arekhi
Abstract
Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be ...
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Spatiality assessment of groundwater pollution is very important to determine water quality condition, pollution sources and management decisions. In this case, GIS and geostatistics methods can be useful tools. Spatiality of groundwater quality parameters, in relation with various land uses, can be very extremely. Therefore water samples from 52 wells in the Kurdan area were analyzed in this study. The results show that nitrate concentrations are less than maximum acceptable concentration in drinking water (i.e. 50 mg/L as nitrate recommended by ISIRI and WHO guideline values) except to one sample (2 percent of samples) in the study area. Various geostatistics methods, e.g. IDW (power 1-4), ordinary Kriging and RBF (five Kernel functions) were compared after assessing the variograms and the spatiality of nitrate samples. Then the model parameters were calibrated and through the specific methods, predicted and standard errors maps were prepared. Errors criteria show that Kriging is the best fitting model in the study area. Finally, probability map of NO3 concentrations exceeding the threshold value of 50 mg/L, is generated using the Indictor Kriging method. Spatiality of NO3 show that Nitrate concentration is increased where the rock type is permeable, land use is agriculture and slope is enough low to infiltrate polluted water into the wells. This research also tries to describe how to assess the spatiality of groundwater parameters by GIS.
Maryam Khosravi; Ali Salajegheh; Mohammad Mahdavi; Mohsen Mohseni Saravi
Abstract
It is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. Hence, at present study, two models including Artificial Neural Networks and nonlinear multivariate regression were used to predict peak discharge in Taleghan ...
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It is necessary to use empirical models for estimating of instantaneous peak discharge because of deficit of gauging stations in the country. Hence, at present study, two models including Artificial Neural Networks and nonlinear multivariate regression were used to predict peak discharge in Taleghan watershed. Maximum daily mean discharge and corresponding daily rainfall, one day antecedent and five days antecedent rainfall, sum of five days antecedent rainfall and monthly mean temperature were extracted in Gatehdeh, Mehran, Alizan, Joestan and Gelinak hydrological units and entered into neural network model (from upstream to downstream, respectively). The feed forward network was used with one hidden layer and back-propagation algorithm. Then, the models were trained, validated and tested in three stages. The observed and estimated peak discharges of the models were compared based on RMSE and r. The results showed that neural network has better performance than nonlinear multivariate regression.
v Payravand; ali Salajegheh; mohamad Mahdavi; mohamad ali Zare Chahouki
Volume 63, Issue 2 , September 2010, , Pages 131-18
Abstract
One of the most appropriate approaches for flood forecasting is using peak discharge data of hydrometric stations in each region. However, lack of such stations or short duration of data in most parts of the country, make it necessary to use some alternative methods in order to estimate the flood discharge ...
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One of the most appropriate approaches for flood forecasting is using peak discharge data of hydrometric stations in each region. However, lack of such stations or short duration of data in most parts of the country, make it necessary to use some alternative methods in order to estimate the flood discharge properly. One of these approaches is regional flood analysis method that in a region using observation discharge data in separate points, it calculates relevant regional flood models. These approaches give us possibility at a region without gauging station with similar and homogenous hydrological condition to estimate flood discharge for different return periods with acceptable accuracy. In this research three methods of regional flood analysis including index flood, multivariate regression and hybrid method were considered in 20 watersheds of central Alborz region. After taking into account, the hypothesis and limitations of each method, the results were compared with observed flood discharges using RMSE and MBE. Considering the hypothesis and validation of multiple regression model indicated it is not appropriate. Finally Index Flood method in return periods of 2, 5 and 10 years and hybrid method in return periods of 50 and 100 years proved higher accuracy in the whole region and no difference between these two methods in return period of 25 were shown.
A. Salajegheh; A. Fathabadi
Volume 62, Issue 2 , October 2009, , Pages 271-282
Abstract
Correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. Conventionally, sediment rating curve used for suspended sediment estimation in rivers. In this method discharge and sediment discharge ...
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Correct estimation of suspended sediment transported by a river is an important practice in water structure design, environmental problems and water quality issues. Conventionally, sediment rating curve used for suspended sediment estimation in rivers. In this method discharge and sediment discharge or concentration related using regression relation that generally is exponential model. Respect to uncertainty and nonlinear relation between discharge and sediment concentration, sediment rating curve has not enough efficiency for this purpose. In this study using Artificial Intelligent (Fuzzy Logic and Artificial Neural Network), suspended sediment in Karaj River was estimated. First, various neural network and fuzzy logic models established. For neural network and fuzzy logic, models with four neuron in hidden layers and FIS (Fuzzy Inference System) with four Gaussian membership functions, respectively were selected as the best structure. Finally, the results showed that fuzzy logic estimates the suspended sediment loud better than the other techniques and therefore is suggested for estimation of suspended sediment load.
A. Salajegheh; A. Fathabadi; M. Mahdavi
Volume 62, Issue 1 , June 2009
Abstract
Rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. In this study statistical method ARMAX model, neural network, neuro-fuzzy (ANFIS subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate ...
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Rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. In this study statistical method ARMAX model, neural network, neuro-fuzzy (ANFIS subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate rainfall-runoff and prediction of streamflow. In each method optimum structure was determined then, streamflow forecasted using the best model. The results showed that hybrid methods have better application than single models and artificial intelligent has better application than linear ARMAX model due to nonlinearity of rainfall-runoff process. In this study all methods showed relatively suitable application but ANFIS method with subtractive clustering is suggested for modeling rainfall-runoff and streamflow prediction.
