مجله علوم و مهندسی آبخیزداری ایران
پیاپی 13 (زمستان 1389)

The uncertainty in forecasted precipitation remains a major source of uncertainty in real time flood forecasting. Precipitation uncertainty consists of uncertainty in the magnitude, temporal distribution, and spatial distribution of the precipitation. Due to uncertainty propagation of precipitation in flood forecasting model of HEC-1, temporal disaggregation method is applied by using the framework of fuzzy Extension Principle supported by a normal genetic algorithm. The uncertainty due to the unknown temporal distribution of the precipitation is achieved by randomly disaggregation of the precipitation into subperiods. Uncertainty in discharge and volume of flood hydrograph due to precipitation with temporal disaggregation and precipitation without temporal disaggregation is estimated and is compared with each others. The results show that in all forecasts the uncertainty in discharge and volume of flood hydrograph due to precipitation with temporal disaggregation is significantly more than uncertainty due to precipitation without temporal disaggregation. So that for forecast subperiod equal to six and membership function of precipitation magnitude equal to zero, the uncertainty in peak discharge due to precipitation with temporal disaggregation and without temporal disaggregation are 33. 7% and 16%, respectively. Also the uncertainty in volume of flood hydrograph due to precipitation with temporal disaggregation and without temporal disaggregation are 23. 5% and 14. 8%, respectively. Also the uncertainty in peak discharge due to the uncertainty in the temporal and spatial distribution can be significantly dominant over the uncertainty due to the uncertainty in the magnitude of the precipitation. So that for forecast subperiod equal to six and membership function of precipitation magnitude equal to zero، the uncertainty in peak discharge due to the temporal and spatial distribution and the magnitude of precipitation are 17. 7% and 16%, respectively. Therefore using space- and time-averaged precipitation over the basin may lead to erroneous forecasts.

In this research، the hydrological homogeneity was used from three methods based on natural characteristics (Political boundaries of three provinces), characteristics and flow hydrological reaction (homogeneity Langbin test) and cluster analysis (Wards method) for regional flood analysis in basins located in three western provinces in Iran (Hamedan, Lorestan and Kermanshah). For this reason, firstly, necessary information and data were collected and secondly, periodical series of peak discharge were estimated during common statistical period (26 year) in 30 hydrometric selected stations. Using regional suitable distribution (log Pearson III type), peak discharges were estimated in different return periods. The research regions were divided into two homogenous areas in cluster analysis method, one homogenous area in Langbin test and three homogenous areas in political limits method. Then, discharge equations related to two- year return period was estimated in homogenous areas and all areas. The results demonstrate that obtained relations in homogenous regions using cluster analysis method have the least standard error and the greatest determination coefficient (R2). Therefore, cluster analysis was proposed as the best homogeneity method.

A large portion of volumetric catchments, water wastes through evapotranspiration (ET). Therefore، investigation and monitoring of spatio-temporal changes of ET would illustrate the amount of applied water in each land use unit, and also would help to proper management and allocation of water in a catchment scale. In such scales, generation of an ET map over the catchment would more applicable compared with point wise calculation of ET at some meteorological stations. Main objective of this study is introducing of Surface Energy Balance Algorithm for Land (SEBAL) as a new procedure for estimation of actual ET in from of a pixel by pixel basis map. In this study a time series of MODIS satellite images from Manshad catchment in Yazd province were acquired during 2006-2007 cropping season and used for generation of actual ET map. Results of this study show the adequacy of SEBAL in estimation of actual ET under the studied condition. Spatial distribution of ET also indictae that water demand of each land use unit is different comopared with other unit (varies from 27 to 1174 mm، spatially). The generated ET map would help for site specific application of water in the region and therefore, proper management of water resources in a catchment scale

Floodwater spreading over the alluvial located in the basins outlets with the aim of storing of floodwaters is a suitable method for exploitation of dried river, seasonal rivers and extra flows of permanent rivers. Determination of appropriate site for water spreading is one of the most important stages of these projects. The purpose of this study is site selection of floodwater spreading project using of analytical hierarchical processing)AHP(in the Eshghabad basin. Data layers: Slope, permeability, geomorphology, lithology formation and density of vegetation were combined in different models and site selection map was prepared. Then, this map was compared with floodwater spreading map that had been executed in the research area. Reduce of devastating floods; increasing percentage of vegetation; increasing biodiversity and discharge of the springs are all of the reasons for successful flood control project in the study area. Therefore, comparing the results of this research with Floodwater spreading map of the study area showed that the factors used in models are suitable for site selection of floodwater spreading and implemented project has been located in the good and suitable area that had been determined by present model. Therefore, AHP model is appropriate method for site selection of floodwater spreading projects in arid and semi- arid regions.

Maximum scour depth around spur dikes is an important issue in design process. In the present research، time variation of scour around the first spur dike in a series of impermeable spur dikes was experimentally tested for different ratios of flow velocity to the threshold velocity of particle motion (U/Ucr) and four types of bed material gradation (D50). Experimental results showed that maximum scour depth reaches to an equilibrium condition in shorter time for lower ratios of U/Ucr. Furthermore the amount of 70 to 90% of equilibrium scour depth occurs during the first 20% of the equilibrium time. In the experiments, 787 laboratory data were totally collected with respect to maximum scour depth measured at different times of scouring. Analytical model (regression) and the best artificial neural networks model obtained from this study were compared by relationships provided with other researchers. The results showed that the ANN models of various training schemes outperform rather than the conventional regression models for both training and validation set of data.

During the last decades، because of incorrect using of natural resources, the degradation rate of watersheds, soil and water resources have been increasingly grown. Furthermore, while this issue intensifies floods occurring, increases sediment production rate and decreases useful life time of dam reservoirs, it has provided the causes of decreasing the country national investments and products. This research which has been done in Bardeh watershed with 32 square kilometers area in Charmahal province, deals with evaluating of mechanical impact measures on the watershed behavior in decreasing flood and flooding potential. The work method is on the basis of field investigations, results and also recording the physical and spatial characteristics of buildings. In the next stage, using SCS model and simulating the watershed flood, the effect of buildings on the watershed flood and runoff control has been studied. The results show that the buildings with volume about 471 m3 in addition to store runoff and to impact on percolation of runoff flow is also capable of controlling the flood with time period of 25 years. The analysis of output data resulted from SCS model in normal conditions and statistical comparison with simulated flood data along with watershed operations indicates that in 95 percent level there is a meaningful difference among data. Also, using the research results, an equation has been proposed to estimate the required numbers of small dams.

The sediment estimation in rivers in order to mitigate flood damages is one of the important problems for the experts.Thus they have tried to develop hydrological and hydraulic models in order to predict the sediment load. In this study, artificial neural network model based on the multi-layer model with back propagation algorithm and non-linear TangAxon function was used for stimulating the suspended sediment in three gauging stations; Ramian in Ghare-Chai, Taghi Abad in Jaffar Abad and Sarmo in the Mohammad Abad River basins. 80 percent of the existing data records used to train the model and also 20 percent of rest for testing its. RMSE (Root Mean square Error), MAE and R2 indices were used to estimate the accuracy of the neural network model. The results obtained from calculating statistical indices indicated high accuracy of the artificial neural network models to predict suspended sediment with R2 greater than 0.99, RMSE lower than 0.0166 and MAE lower than 16.45. Also Nash-Sutcliff coefficient calculated for the stations showed high accuracy of the model to the prediction of suspended sediment.

Construction of underground dams in mountainous stream is an appropriate solution for water resources development and provision. The aim of this study is to select suitable sites for underground dams in the West Tehran Province. The integrated system of a multi- criteria decision making (MCDM) by use of geographic information system (GIS) in the form of measured spatial decision support system (SDSS) was used for this study. Based on these criteria, with the help of the analtical hierarchical process(AHP) method, the land surface divided into smaller components. The criteria in each component (level) were prioritized using paired comparison method. Layers of information needed to prepare the weight of each factors were calculated in the GIS environment.Then, by use of SMCE Module in ILWIS 3.6 software, the decision tree employed and finally based on mentioned criteria, prioritization has been performed. Results show that water criterion in comparison to other criteria is the most important one.