مجله مهندسی آبیاری و آب ایران
پیاپی 32 (تابستان 1397)

Without a doubt, the first step to manage water resources is accurately predicting of river flow. In This study, to predict time series of daily and monthly of kakareza and sarab seyed ali stations, artificial neural network and Adaptive neuro-fuzzy inference system models is used. the daily and Monthly rainfall and runoff time series of Sarab seyedali and kakareza basins were decomposed into sub-signals in various resolution levels using wavelet analysis and then these sub-signals entered to the ANN and ANFIS models to reconstruct the main forecasted time series. The model results show the high merit of Db-4 wavelet in comparison with the Haar wavelet. Too, results showed that WANFIS model produced better forecasts than either the ANN, WANN, ANFIS models.

Today, with population growth and, consequently, urbanization, runoff has become a serious problem in urban management. Therefore, runoff control and management is very important. In this research, the 4th district of Tehran with an area of ​​about 62 square kilometers and with geographical and hydrological conditions commensurate with the city of Tehran on a small scale as the studied area is considered.The purpose of this research is to achieve a practical approach to urban runoff control.In this research, using the SWMM model capabilities for Tehran's 4th district, considering the environmental factors, two designs of the best management solutions (BMP) under the intrusion network scenario and delayed repositories for controlling maximum runoff are quantitatively taken and Finally, their efficiency in reducing the total volume of runoff from the basin has been studied.

Since catchment scale measurement of meteorological and hydrological factors affecting on the basin response in the form of runoff generation and sediment production is not feasible, study of governing processes under a rainfall-runoff modeling framework is necessary. In this reaserch, to understand the relationship between runoff and sediment production in Beheshtabad Basin, and generalizing the results to Alej Watershed a six years daily simulation was performed using a distributed model called WetSpa. For this purpose the basic maps and hydrologic data including peak discharge and hydrographs were used. Spatial distribution of hydrological processes was taken into account in the modeling. Moreover, another 6-years time series (unused for parametrization), were used for model validation. The simulation results showed a satisfactory good agreement between modeled both simulated runoff and sediment against observations. The Nash-Sutcliffe model efficiency57.6 for runoff and coefficient of determination 0.59 mean that the sediment-runoff relationship for any rainstorm depends on the dynamic of hydrologic processes. The results of sensitivity analysis for WetSpa model showed that ksnow, ki, kg and kss were ranked as the most sensitive parameters correspondingly. While Krain and Pmax parameters were identified as less influential parameters on the simulated hydrograph. Sensitivity of ksnow and g0 parameters is an indication for the importance of baseflow in Beheshtaba basin and the necessity of paying special consideration for its key role in hydrological modeling.

For over three decades, hydrologists were recommended multivariate models to describe and modeling the complex hydrology data. While recently the multivariate models in hydrology is discussed. In multivariate models, the modeling and predicting various parameters can improve by involving other factors. Also Since nonlinear models with conditional variance, the remaining portion of the linear models to adequately model, we expect that the combination of linear and nonlinear models, partly to increase the accuracy of modeling and predictions. In this study, two multivariate periodic ARMA and combined multivariate with conditional variance models were investigated to modeling monthly discharge of Nazloochai, Babolrood and Hamoon Rivers that located in West Azerbaijan, Mazanderan and Sistan-Balochestan Provinces respectively during the period of 1962-2011 (50 years) under effective the precipitation and temperature of mentioned basin synoptic stations. The results of evaluation and verification models (Root mean square error) showed that booth models have a more accuracy to modeling the river flow rate. Also the results showed that the combined multivariate with conditional variance model has the more accurately than multivariate periodic ARMA model. Also the results indicated that with combined two mentioned models, the model’s error in modeling the Nazloochai, Babolrood and Hamoon rivers flow discharge will be better amount 30, 17 and 1 percentage respectively. Finally the results indicated that the combined model has a more accuracy in the moderate zones of Iran.

Routing of river flow is one of the most important of water resources management topics to adopt appropriate decision in occurrence time of flood or droughts. In this study, artificial neural networks (ANN), gene expression programming (GEP), wavelet- neural network (WNN) and least square support vector machine (LS-SVM) models were used for routing of Baleqlu-Chay river daily flow, located at Dareh-Roud watershed. Daily river discharge data of two consecutive hydrometric stations located at the mentioned river for the period of 1997-2013. The statistics indices including, root mean square error (RMSE), correlation coefficient (R), Nash–Sutcliffe efficiency coefficient (NS) and Bias were used to evaluate the precision of the models. Comparison of results demonstrate that the LS-SVM with RMSE=1.540 m3/s, R=0.894, NS=0.713 and Bias=0.013 had the best performance in the test period. But in estimating of peak discharge values, the WNN model with average relative error equal to 34.21% had the least error. It should be mentioned that all of the models tended to underestimate the discharge values.

The use of geospatial methods has been considered due to the spatial relationship in various ecological issues. In order to, the present research was done with the aim of investigating the spatial variations of groundwater level in Bistoun plain located in Kermanshah province during the period of 1991-2015 and especially using interpolation estimation methods. In order to, data of groundwater level of the plain including 21 observation wells, collection and database were prepared in Excel software. Then, Different interpolation methods such as Ordinary Kriging, Inverse Distance Weighing with power of 1 to 5 and co Kriging are used to estimate the groundwater level. To evaluate the methods, we are performed the cross validation technique using Root Mean Square Error (RMSE) and Mean Bias Error (MBE). Then, we are prepared spatial zoning maps at the beginning and end of the study period, and finally we were drawn a map of groundwater level isodrop in ArcGIS 10.4.1 software Results of our analysis showed that the Gaussian semivariogram provides the best explanation for the spatial structure of the data. In addition, Kriging is shown as the most suitable method for estimating the groundwater level. The results obtained indicate a decline in groundwater levels in most of the plain. So that the maximum of this decrease is 22 meters in the southwest of the plain (the effective range of wells 9 and 17) and the minimum decrease is 5 meters in the central part of the plain at the 25 years’ period. The main reasons for reducing groundwater levels is being away from the flow of the river and the increasing growth of water-consuming industries in the region.

Groundwater is an important source of water supply in arid and semi-arid regions. Optimal management of water resources and their conservation and improvement for quality and quantity need to have amount and distribution of water data in a defined geographical area. According to this issue, in this study we want to assess both qualitative and quantitative risk of groundwater resources using the modified IMDPA model and geographical information system (GIS) in plains of Fars province. The purpose of this study is to prepare a suitable zonation and vulnerability maps of qualitative and quantitative status of groundwater in order to determine the areas with higher risk. This is a basic and vital step in water resources management for priotorization of areas in order to prepare a combat plan against qualitative and quantitative degradation of groundwater. To prepare Zonation maps of qualitative and quantitative status of groundwater, spherical ordinary kriging method was used. The required data of this study is related to precise data recording of Fars Regional Water Company. The results of this study indicate that the Lowering of Water Table (quantitative status) in 81% of Fars plains is at severe and very severe hazard classes. The quality status of about 58% of Fars province plains is at severe and very severe hazard classes. Overall, more than 83% of Fars province plains are in state of severe and very severe hazard classes of ground water condition. Severe and very severe hazard classes were observed in many parts of the province especially in central and southern regions, the moderate and slight hazard classes were observed mainly in the northeastern parts of the province.

Determination of water requirement in irrigation and drainage projects and water management is important and plant coefficients are one of the key parameters in determining the water requirement.. Therefore in this study, Four-year lysimeter data of grass and three-year lysimeter data of winter wheat and weather data were in Esmaeil Abad in the Qazvin Agricultural Research Center applied to calibrate different methods of estimating evapotranspiration. So with use of these results winter wheat water requirement in each month was Available. Results indicated that annual evapotranspiration of grass, annual evaporation from pan evaporation and winter wheat evapotranspiration respectively were equal to 1296 mm,1703 mm and 550 mm during growth period. FAO 56 method was the best method compare to methods of Turc , Makkink , Priestly_Taylor, Hargreaves and Samani , FAO Blaney and Criddle and FAO 24 . Also results showed that calibration of methods can provide acceptable result in estimates of evapotranspiration of winter wheat. On the other hand, pan evaporation method which is the easiest and most practical method, with use of coefficients and some modifications could estimate evapotranspiration of winter wheat with acceptable accuracy. The value of Plant evapotranspiration coefficient (Kc) was determined equal to 0.29-1.09 and value of evaporationpan coefficient (KP) was determined equal to 0.58-0.88 and value of evaporationpan coefficient (Kcp) was determined equal to 0.26 -0.99.

Depending on land and water resourses avilibility, on-farm water management is usually aimed to maximize yeild or water productivity. The crop water stress index (CWSI) shows the plant's available water status well and therefore used as an appropriate tool for irrigation management in the field. The purpose of this study was determination of crop water stress index to soybean at different stages of growth in order to irrigation planing to achieve maximum yield and irrigation water productivity. For this purpose, soybean was cultivated with four irrigation regimes at the research farm of Lorestan University Agriculture faculty in the summer of 2016. The Irrigation levels were I1, I2, I3 and I4 with 100, 80, 60 and 40 percentof full water requirement, respectively. According to the results, the effect of irrigation levels on yield and soybean water productivity was significant at 1% probability level. The highest and the lowest values of CWSI were observed in I4 and I1, respectively in different growth stages. Also, the correlation of between CWSI and soil moisture content was significant at 1% probability level. The maximum yield was observed in I1 (1765.4 kg/ha) and The maximumwater productivity was 0.26 kg/m3 in I2. The values of CWSI for treatments ofI1 and I2were considered as the basis for irrigation scheduling to achieve maximum yield and water productivity. Finally, the CWSI values were obtained equal to 0.42, 0.37 and 0.29 for the maximum water productivity for the growth and development, middle and final stages of plant growth.

The aim of this study was to investigate the influence of discharge on wetting pattern and simulation by HYDRUS-2D model. After preparing a physical model made of Plexiglas with specified dimensions, and filled with silty clay loam soils. By manually adjustable emitter, four discharges 2, 4, 6 and 8 liters per hour were tested. Irrigation time for each fixed discharge 2 hours and for moisture reparation distribution, 24hours is validated. Comparison of measured and calculated values with HYDRUS-2D model of the diameter and depth of the wetting front revealed that the correlation coefficient was above 90 percent of all discharges and was very low error rate which shows the ability of the HYDRUS-2D model to simulate the moisture but this ability was higher in the lower discharge. A comparison between the simulation with HYDRUS-2D model using data from various input Rosetta and data observations of wet pattern soil showed the input data of the model Rosetta is more will increase accurate simulation with HYDRUS-2D model. By increasing the discharge, the extent of depth decrease and extent of the surface moisture increases. The performance of HYDRUS-2D model in lower discharge is more. And by increases the amount of data inputs to the model Rosetta, HYDRUS-2D model will be having higher accuracy

Although moving sprinkler systems such as traveling rain-gun are usually designed, so that the instantaneous water application rate which is associated with low pressure is less than the soil final infiltration rate to avoid runoff; there are a growing number of sprinkler systems where potential runoff increases so much causing soil erosion. Moving sprinkler systems such as travelling rain-gun and center pivot can have excessively high water application rates and are prone to runoff problems. This is exacerbated by the trend to low pressure operation, for the reason of saving energy which adds to the problem. The purpose of this paper is to assess, compare and simulate a more fundamentally based approach to predict runoff from sprinkler irrigation systems under moving rain gun conditions on coarse and fine soil textures practiced on both simple plane and ridge and furrow. Experiments were carried out on both simple plane and ridge and furrow plots sloped 0.67 percent with three replications. A travelling rain-gun with length of 200 m was employed to generate rainfall at three different speeds. Results showed no runoff with runoff coefficient of zero on coarse soil. However, a remarkable runoff with coefficient of 0.162 was considered from the fine soil texture on both simple plane and ridge and furrow practices plots, as machine run with the speed of 10 m/hr. Therefore, one of the approaches to overcome runoff problem and increasing irrigation coefficient is using this system over fine soil textures. On the hand, as much as the machine speed is lower, the potential for runoff is larger. In addition to field experiments, there was a good relationship between observed and predicted runoff using EUROSEM. This is because of a high regression coefficient (R > %90) and minimum Residual Mean Square Error (RMSE < 0.2) between them

Considering that water shortage is the major dilemma for Sustainable agriculture development and water potential of the country is no longer able to adequately meet the growing needs of water demand especially in agricultural section, it's essential to optimize water consumption.Uniformity of sprinkler irrigation is an important technical parameter for designing sprinkler irrigation systems. Due to high diversity of sprinklers used in sprinkler irrigation, it's necessary to improve irrigation system performance with simple changes such as changes in system operating pressures, riser head, setting sprinkler spacing on laterals and the distance between laterals. In this research, CU quantities of two types of sprinkler (AQ-20 and KA-6) were measured in slow wind velocity (0-2 m/s) , at Hashemabad cotton research station of Gorgan city under 4 different operating pressures (2, 2.5, 3 and 3.5 at), 16 distances of sprinklers (including 9×18, 12×18, 15×18, 18×18, 9×15, 12×15, 15×15, 18×15, 9×12, 12×2, 15×12, 18×12, 9×9, 9×12, 9×15 and 9×18) , 4 riser heads (60, 90, 120 and 150 cm) and 3 arrangements of sprinklers (square, rectangular and triangular). Decision tree model M5 was used to estimate uniformity of each sprinkler and the results were compared with K - nearest neighbor method. By statistical comparison of results, root mean squared error (RMSE) for AQ-20 sprinkler in M5 and K-NN methods were obtained as 0.0681 and 0.052 and for KA-6 sprinkler as 0.086 and 0.0716, respectively. The results indicate the high accuracy of both methods for modeling, since M5 is capable of estimating explicit equations for estimating CU; it incorporates more practical features.

Irrigation networks are the infrastructures in which researchers have shown an increased interest due to the huge costs of the construction and maintenance. In this sense, minimizing the costs of irrigation networks is the objective of many researchers in such a way that the conditions of minimum pressure and maximum speed are satisfied. In this study, DMPSO algorithm based on modification and mutation in PSO algorithm is proposed. Applying the proposed DMPSO algorithm, the optimum solution for the irrigation network of “Esmaeelabad” including 16 pipes and 17 nodes is explored deeply. The numeric results of hydraulic analysis were evaluated by creating a dynamic connection between MATLAB and EPANET. Using DMPSO meta-heuristic algorithm, the obtained optimum solution for the irrigation network of Esmaeelabad was compared with experimental method. It was shown that meta-heuristic algorithm reduced the total cost for 10.68% related to the experimental method and, furthermore, this proposed method is simple but more relatively accurate.

Optimal operation of dam reservoirs is important due to their role in runoff control and water supply for different sectors. In this study, the Firefly Algorithm (FA) is investigated to solve the problem of optimal operation of Haraz dam reservoir to provide water for agriculture, drinking, industry and environmental of downstream for a period of 27 years (since 1984 to 2011). The objective function was defined as minimizing the sum of squared monthly relative deficiencies during operation. The efficiency of these algorithms was compared and evaluated by determination of reservoir performance indices, the value of objective function, annual deficit, monthly average deficit and release. FA method with reliability of 88.3 percent is supplied the downstream demands better than GA and SOP with reliability of 82.4 and 66.7 percent. The Vulnerability index of models is obtained 0.20, 0.23 and 0.99, respectively. The results showed the better performance of FA algorithm compared to the other two methods in solving the problem of the reservoir operation.

Historical Helakoo dam with more than 700 years age is located in Seyedi district that is 16km far from north of Kerman city .This dam was constructed for supplying the Agricultural water and Flood Control on Seyedi river. The dam height in upstream is varied between 9.6m-10m and in downstream is decreased to 8m. The length of dam crest in upstream is 43 meter and in downstream is 32. In this study the dam stability was investigated with review of the literature, Field visits, measurement and theoretical calculation. The results of this study were shown that the technical instruments, environmental condition, Site Suitable Location, necessary lateral structures were considered. The dam remarkable lateral structures are Include emergency weir, intake tower and intake mouths. In addition the result showed that the dam stability criteria’s include of Overturning and Sliding stability are 1.86 and 1.36 respectively that is in the acceptable domain