فصلنامه مهندسی منابع آب
پیاپی 40 (بهار 1398)

In this paper the daily runoff of Ravansar Sanjabi basin (1260 Km^2), in Kermanshah Province of Iran is simulated through SRM hydrological model. The Snow Cover Area variable which a main and necessary variable in SRM model is calculated from MOD10A2 product of MODIS which separate snow cover maps with 8-day intervals. The runoff is simulated in a period of 2 years from 2002 to 2003, where 2002 (January 1 to December 31, 2002) is selected as a calibration period and 2003 (January 1 to 31 December, 2003) as a validation period of model. The results of simulations during the calibration and validation periods were evaluated through three statistical indices namely Nash–Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and volume difference (Dv). According to compared simulated and observed daily flow hydrographs and also calculated statistical coefficients in 2002 and 2003, the SRM shows appropriate and acceptable results in simulating daily runoff during both calibration and validation periods, so that the NSE coefficients are 0.9 and 0.85 for calibration and validation periods, respectively.

Drought prediction is an important item in realm of hydrometeorology and hydrology, and selection of suitable meteorological variables for drought prediction is a goal in recent studies. In this paper, suitable feature selection is investigated with application of Mutual Information (MI) on the predictor’s time series and the well-known statistical machine learning methods, Support Vector Machine (SVM), is proposed to predict drought class based on Standardized Precipitation Index (SPI) in some seasonal scale scenario in the main watersheds of Tehran. In current study, ground weather temperature (at 300, 500, 700 and 850 mi bar) and geopotential height (at 300, 500, 700 and 850 mi bar) was applied in prediction models based on data from 1975 to 2005 in the main watershed of Tehran. Regarding to the amount of predictors, suitable feature selection is investigated with application of Mutual Information (MI) on the predictor’s time series and target time series and the well-known statistical machine learning methods, support vector machine (SVM), is applied to predict SPI class. One of the important issue in this research is use of different variables, for example regarding to selected data points, the effective regions on Tehran precipitation are southern, southwestern and northwestern of Iran in spring, northern and northwestern in autumn and northwestern and western in winter. SVM depicted accurate results in classification and prediction of SPI and it is suitable and applicable. The predicted SPI in winter and autumn are more accurate than the other scenarios.

To evaluate a pipe network performance, both steady and unsteady flow conditions are required to be accurately analyzed in the system. For this purpose, mathematical models are developed and utilized. Calibration of parameters with dynamic effects like the steady and unsteady friction loss factors as well as pipe wave speed is crucial to the simulation models. A common approach for calibration of pipe networks under unsteady flow is the Inverse Transient Analysis (ITA) method. This study introduces a model for hydraulic analysis of unsteady flow in pressurized pipes using the numerical Method of Characteristics (MOC). To each calibration parameter a correction factor is specified. Then, a nonlinear optimization problem is developed with the aim of minimizing the discrepancy between the calculated and measured transient pressure heads at the measurement sites. The decision variables are the correction factors multiplied by the pipe wave speeds, steady friction factors and unsteady friction loss components. In this Article, the proposed model applied to an experimental system set up in the Technical University of Lisbon. By defining the genetic algorithm to minimize the objective function, after 30 generations error rate was reduced from 140 m to 92.15 meters. The results, increasing the accuracy of modeling showed as much as 33%.

One of the suitable & affordable methods for detecting karstic zones is geoelectric method. Geoelectric is one of the geophysical field operations, which is designed based on the transmission of electrical current into the ground, creating a potential difference between two points and calculating specific resistance of the ground in different depths. In this method, exploratory studies are carried out based on the standards for the resistance of different soil and rocks, as well as the electrical resistance values of materials such as water, metals, cavities, etc. In this research, in order to identify the karstic zones containing water in the Roniz plain in the west of Estahban, 97 electrical sounding were utilized using Schlumberger array and a maximum flow transmitter length of 300 m. After processing the data, Geological sections were prepared and analyzed. Finally, determined the hydraulic gradient of aquifer from west to east, based on specifying the saturated karsted zone in A2 sounding with a thickness of 140 meters at a depth of 260 meters has an electrical resistance of 100 to 150 ohms and at the place of D2 sounding at a depth of 150 meters with an electrical resistance of less than 100 ohms has 80 M thickness. That means, although the only seasonal river in this plain is near the D2 sounding, and therefore the rate of surface water in this area is at its highest, the maximum thickness of the subsurface aquifer is in the eastern part.

The reduction in the quantity and quality of water due to over-cultivation and continued drought has caused irreparable damage to the groundwater resources of Lorestan province. The water levels have also dropped in the Central Plain, one of the large plains of the Khorramabad basin, which is the subject of this study. Water resource management is the most important and most strategic way to control this growing crisis. Hydrogeochemical assessment of the water resource is the first step in achieving this goal. For this purpose, the EC, pH and TDS parameters and the major anion and cation concentrations were measured in 40 samples well scattered within the aquifer. Ion ratios, saturation index and Gibbs, ion exchange and TDI graphs were used to determine the water quality and to define the factors affecting it. The Piper diagram shows that water samples from all parts of the aquifer contain Ca-HCO33 due to the distribution and diffusion of dissolved carbonate formations in the study area. The ion ratios indicate that the composition of water is influenced by the weathering of carbonate rocks, plagioclase minerals and, in the next stage, by direct and reverse ion exchange processes. Saturation indices show that due to the geological formations, the aquifer is undersaturated in gypsum, anhydrite, and halite minerals and oversaturated in aragonite, calcite and dolomite. The results of the Gibbs graph show that weathering is the dominant process in determining the water quality. Direct and reverse ion exchanges also affect the quality of water.

For proper groundwater resource management as a vital resource, accurate aquifer parameter determination is required. Existing groundwater management practices, for the sake of simplicity, overlook inherent uncertainties in measurements of pumping test parameters. In the current study a fuzzy simulation-optimization model based on consideration of uncertainties in parameter determination is used. To this regard, the novel fuzzy simulation-optimization model is able to predict the confined aquifer parameter precisely, based on minimizing the deviation between observed and calculated drawdown. The proposed approach is tested on a real pumping test data of a confined aquifer and then the results are compared with graphical solution of Theis method. Comparing several statistical indices based on the results of the proposed method and graphical solution of Theis method, performance of these models are evaluated. As an example, Mean Absolute Relative Error (MARE) of the proposed model and graphical Theis solution is 0.69% and 1.13% respectively which shows the appropriate accurate of the proposed model over the traditional method (graphical Theis solution). Thus, the proposed fuzzy simulation-optimization model may replace the graphical Theis solution. In the second part of the study, by considering pumping rate as an uncertain parameter, a fuzzy optimization model based on fuzzy transformation method is developed. Then, the effect of uncertainty in prediction of aquifer parameters is assessed and ranges of aquifer parameters in various α cuts, are determined. Based on the developed fuzzy results, T is found more sensitive to uncertainty in the pumping rate measurements, as compared to S.

Spillways are one of the Most Important Hydraulic Structures of Dams that Transmitted Flood Entering the Reservoir with Sufficient Safety when Capacity Reservoir Completed. To Reduce the Cost of long Spillways and Topographic Factors, Walls, Especially in the Chutes Constructed. In this study, Flow over the Gavshan Dam Spillway Comprising Approach Channels, Ogee Crest, Converging Chute and Flip Bucket using Flow 3d Software and Turbulence Model K- , Simulated and Hydraulic Characteristics of Flow such as the Distribution of Velocity, Pressure, and Changes in the Depth is Studied. Comparing Numerical Results with Experimental Model Showed that there is not much difference between them. Changes in flow velocity over a spillway crest increase sudden and Rapidly and this Process Followed along Chute as far as most flow Velocity Rate in 1350 Cubic Meters per second, Equivalent to 30 meters per Seconds Accurate at the End of Chute (start of Flip Buckets) . 2/07 Degree Angle Convergent Walls are Optimized Angle to Prevent the Formation of Transverse Waves and Need to Increase the Height of the Walls of the Convergent Spillway.

Choosing the methods and techniques of statistic and probability science for predicting the variable with certain return period is very important in hydrologic analyses. Maximum daily rainfall is one of the important hydrologic variables that have a basic role in flood magnitude and peak. More accurately prediction of maximum daily rainfall can help us for better planning and management of water resources and flood control. The purpose of this study is determination the suitable probability distribution for maximum daily rainfall in throughout of Iran and also in identified hydro-climatic homogeneous regions. For this purpose, the data of 46 Sinoptics and four Climatologic stations were used. After data prossecing, EasyFit software was used to identify the best-fit distribution. Kolmogrov-Smirnov test was carried out in order to select the best fit probability distribution. The homogeneous regions were determined using the cluster Analysis technique with Ward method based on six parameters; Altitude, the mean annual rainfall, the mean of maximum daily rainfall, the mean of rainfall in winter, spring and autumn.Then five region were obtaned. Then, frequency of suitable probability distributions for maximum daily rainfall in every homogeniuse area were determinated and compared with its in throughout the country. The results showed the Wakeby distribution is most suitable distributions for estimating the maximum daily rainfall in both cases. But the next probability distributions in every homogenius region were different from each other.

Post Audit is a subsequent review of numerical model’s prediction. In this method, the model’s predictions are compared with actual field data, at least a few years after prediction. This investigation will prepare valuable information in order to use numerical model for predicting input stress to aquifer and can be used for improving model ability in prediction. In this study we assessment the model prediction of Haji Abad Aquifer. Haji Abad Aquifer is sub Basin of Kol River and located in the south part of Haji Abad study area and 160 distances from BandarAbas City. Numerical model of this aquifer run in unsteady situation for 2007-2008 water year. This model was used for predicting water level in a 5-year period (2010-2015). Due to the existence of real data from ground water level in 2015- 2011, the result of model prediction compared with real ground water data. The result show, on average 1.35 meters error occurred in prediction. The most important factor in this error is predicting model for wet situation while in the reality the study area faced with drought condition. Other effective factors in this error are bad design of conceptual model and ignoring conceptual model uncertainty in numerical model simulation.

Abstract With sprinkler irrigation, determining water distribution uniformity of coefficient (cu) from a single sprinkler is time consuming due to overlap sprinkling by neighboring sprinklers and also different pressure heads (P), riser heads (RH), sprinkler gaps on laterals (Sl) and the distance between laterals (Sm).The best combination of the above parameters for maximum CU, is still unknown for applicators. In this research, CU quantities of zb model sprinkler (made in Iran) were measured at Hashemabad cotton research station of Gorgan under 3 different pressure heads (2.5, 3 and 3.5 atm), 2 riser heads (60 and 100 cm) and 7 sprinkler (Sl×Sm including 9×12, 9×15, 12×12, 15×12, 12×18, 15×15, 15×18m) arrangements. Different equations for genetic algorithm using mentioned parameters were evaluated using a written program with Matlab software. Based on R2, RMSE and standard deviations obtained between estimated and measured data using PSO algorithm, the equation of CU was selected as a final model. Keywords: Sprinkler Irrigation; Riser Heads; Laterals; Uniformity Coefficient

In the recent decades, water resources have been severely under pressure due to increasing demand. Besides, use of water by some users affects the possibility of using water by other users. Therefore, the optimal management and allocation of water resources have become increasingly important among policymakers and farmers. Undoubtedly, one of the most important tools for optimal allocation of water resources is economic valuation which the long-term development strategy of the country also emphasizes it. In this regard, the aim of the present study was to determine the economic value of agricultural water from the viewpoint of the applicants in wheat and rapeseed farms of Qazvin flat irrigation network area using the production function approach as an appropriate tool for better water resources management. Data and statistics were collected by completing a questionnaire from 144 farmers based on a two-stage cluster sampling method in 2015-2016. In order to achieve the research objectives, the estimation of various forms of flexible production functions was used and according to the results, the Translog production function was detected as the best form of the function. The results showed that the economic value of each cubic meter of water in the production of wheat and rapeseed was estimated 3715 and 3370 Rls, respectively, which had a huge difference with what farmers paid for water cost (418 Rls) in mentioned year.