مجله علوم و مهندسی آبخیزداری ایران
پیاپی 27 (زمستان 1393)

TDS parameter is the main factor in water quality assessment and it has many effects on the material movement، chemical alteration and ionization. Also، TDS density has important role in optimum water allocation for drinking water، agricultural and industrial uses. However، the aim of this study is TDS prediction in a case study in Lighvan Watershed using M5 and MLP models. The study area is one of the sub-basin or watershed in Urmia Lake basin and monthly data collected from two hydrometric stations during 1972 to 2010. Generally، based on the criteria which evaluate the models، M5 and MLP had the good performance in the TDS prediction and also mostly they had the same results. In the Lighavn station، among 6 scenarios، the fifth and sixth scenarios showed the highest correlation coefficient between observed and estimated series based on the inputs combination in two models. Due to these scenarios in the most errors criteria were closed together، the fifth and sixth scenarios introduced as the best scenarios. In the Hervi station the results showed that 5th scenario was the best scenario as model inputs. In general، 5th scenario with HCO-3، Ca2+، Na+، Mg2+ parameters showed the best results for the TDS prediction.

Bed load transport، has been extensively studied in the past few decades and many equations have been developed، but they differ from each other in derivation and form. As the process is extremely complex، obtaining a deterministic or analytical form of it is too difficult. Neural network modeling، which is particularly useful in modeling processes about which knowledge of the physics is limited، is presented here as a complimentary tool for modeling bed load transport. The developed model demonstrated a superior performance based on different statistical criteria. The significance of the different input parameters has been analysed in the present work to understand the influence of these parameters on the transport process.

The springs of Piranshahr watershed are sources that supplies drinking and irrigation water. Therefore، in this study geology and agricultural conditions is examined as the most important factor controlling spring water quality. After recording the geographical location of 145 springs، sampling was done in September 2012. The electrical conductivity (EC) were measured in the study area، whereas The values of other parameters، such as sodium ions، calcium ions، magnesium ions، potassium ions، carbonate ions، bicarbonate ions، chloride ions and sulfate ions were measured in the laboratory. Water quality parameters was analyzed، in which، the Piper diagram show the six types of water، including Ca-HCO3، Mg-HCO3، Ca-SO4، Mg-SO4، Na-HCO3 and Na-SO4. To investigate the influence of lithology (seven types of lithology) and landuse (two types of landuse) on spring’s water quality، the statistical analysis of variance (ANOVA) and t test was used، respectively. The results of statistical analysis showed that the parameters of springs، including EC، TDS، CO32-، HCO3-، Cl-، Ca2+، Mg2+ and TH in different formations of the study area have significant differences. Finally، averages of the water quality parameters of the lithology using Duncan test were compared. Also، landuse have a significant effect on parameters including CO32-، Cl- and K+. Gibbs diagram based on the results of chemical analysis showed that the chemical structure of water quality influenced by lithology. So the first and second priorities of influence on the water quality are lithology and landuse، respectively.

In order to reduce sediment and soil conservation plan generation، the design and calculation of the exact size of the dam at dams، evaluation and estimation of sediment yield in the watershed of the dam، is essential. In general erosion and sediment transport of the most complex issues that determine the exact hydrodynamic equations for the various variables، it is not easy. The aim of this study was to simulate suspended sediment load using a neural-fuzzy model is combined This is necessary for the various input combinations using stepwise regression، genetic algorithm model and gamma test and then determine the most suitable model for the input. Karaj Dam Sierra station data in the period 1974-2011 (37 years) was used so that the 15 variables as input and output variables as was considered. Results indicated neuro-fuzzy models in a suitable combination of the number of training data to select the most appropriate modeling of the genetic algorithm to be achieved. It should be noted that in the case of all input variables، modeling neuro-fuzzy model was not appropriate Therefore، methods are necessary to determine the appropriate combination of inputs. Finally، the Genetic Algorithm model as the most appropriate method and stepwise regression، second، and third order gamma test as appropriate methods to determine combination of neuro-fuzzy model inputs selected. The neuro-fuzzy model when using a selected combination of genetic algorithms to simulate suspended sediment load 99/0 correlation coefficient and the mean square error as the most appropriate modeling 0000009/0 has been selected.

Drought is a natural occurrence caused by repetitive and ephemeral that it is less rainfall than average long term and can occur in any climate. Since the drought phenomenon is stochastic and nonlinear، stochastic linear models، neural networks and hybrid models can be useful in the development forecasting results. This study models the performance of ARIMA، neural networks and hybrid models ARIMA prediction of hydrological drought in both monthly and seasonal time scale deals and SDI index is as a predictor of the watershed was selected Gamasiab in period (1353-1387). The period (1353 - 1379) used for calibration and the remaining 8 years used for verification in model. Results show that، among the three models used to predict one time step neural network models - stochastic (hybrid) models are suitable to the monthly and seasonal scales. So Kappa statistic values and the relative error of the model at monthly time scales Polchehr station (the outlet)، respectively RME= 5/79 %، K= 0. 565 and seasonal time scales Station Doab (the middle) RME = 22% and is K=0. 231.

Determination the effects of a drought or wet in the area، is one of the essential needs for environmental and economic plans، particularly for water resources management plan. One of the most important influences is affecting on the suspended sediment، which is very important in river engineering and water resource. The purpose of this study is the impact of drought and wet periods on the amount of sediment in Karkheh basin. With Studying of data in Meteorological and hydrometric stations and select of 18 stations، identified the drought and wet periods with using of five-year moving average. Then fitted Sediment rating curves and estimation of sediment for each of sub watershed. The result shows that in the dry periods sediment has decreased trend and in the wet period the sediment has increased trend. In wet year the sediment was 1. 57 dry year، that between 0. 9 and 5. In this year’s spatially sediment was 1. 12 spatially sediment in total periods While the in dry periods spatially sediment was 0. 74 spatially sediment in total periods.

Flood has caused financial and vital damages in the Hajighoshan watershed in recent decade. In this study، we investigated the efficiency of flood control structures in decrease of flood hazard and their effects in the downstream flow regime. First، a rainfall-runoff model has presented by using HEC-HMS model. The rainfall- runoff model was presented and optimized by using 5 past flood events and then was validated with 4 another flood events. The dams were simulated by using Elevation-Area method in the validated rainfall-runoff model. The results showed that The efficiency of flood control dams in decreasing of flood hazard dependents on their location، reservoir volume and the surface of watershed or sub-basin which it controlled its runoff.

Present research has been executed in Chaharmahal va Bakhtiary Province in order to investigation of rainwater harvesting techniques for runoff generation optimizing. Towards this attempt، nine rainwater harvesting systems having three different treatments (isolated surface، removed surface and natural vegetation cover) with three replicates were made on a slope of 20 percent. At the end of each system، a reservoir has been installed to collect runoff coming from the plot. Rainfall amounts are estimated using a rain-gauge nearby and runoff volume was measured in the reservoir. Compare of the mean of treatments indicated that the system with isolated surface has generated the maximum runoff volume. The runoff volume generated by isolated surface was five equal of removed surface and 17. 5 equal of natural vegetation cover. Analysis of 21 rainfall events led to runoff generation showed that the mean runoff coefficient derived from the system with isolated surface was 64. 3 percent. Statistical analyses using SAS software، proves that there is a significant difference in the system with isolated surface (p<0. 01). So utilization of isolated surfaces can be recommended in supplying water for hillside orchards in watersheds using rainwater harvesting systems.