فصلنامه علوم و مهندسی آبیاری
سال چهل و سوم شماره 1 (بهار 1399)

Shohada diversion dam was constructed on the border of agricultural lands of Behbahan plain (Khuzestan province, Iran) to divert the water of the Maroun River. This dam has a concrete-soil composite. The concrete part consists of an ogee spillway, a stilling basin, and two intake channels and sediments on the right and left sides. The height of the dam is 12.2 meters and its spillway length is 150 meters. The dam has a sloping basin and its capacity is 22 m3/sec. The longitudinal slope of this basin is 1 to 5 (vertical: horizon). The studies have shown that parts of downstream of the stilling basin are being eroded and scoured. Unless controlled properly, this will continue and might lead to the destruction of the basin or the main structure of the dam. Most of the stilling or apron basins used in the previous studies are horizontal and smooth, and no research has been conducted on scouring downstream of sloping basins so far. Therefore, the purpose of this research is to explore the causes of scouring downstream of the Shohada dam's stilling basin and its controlling factors to finally provide an appropriate strategy to prevent its spread.

The Unit Hydrographic Theory, which was first proposed by Sherman in 1932, is used as one of the most important rainfall-runoff methods in hydrology. One of the most efficient models in simulating rainfall-runoff phenomenon is the conceptual model known as Nash Instantaneous Unit Hydrograph. In this model, the number of reservoirs and storage coefficients describes the complete shape of Instantaneous Unit Hydrograph (Ahmadin et al., 2010). The model consists of two parameters including n and k. Different methods have been presented to estimate the mentioned parameters. Inaccurate estimation of the model parameters (n and k) causes an error in simulated hydrograph. Methods such as the moments, the least square and the maximum likelihood are some of the proposed ones (Snyder, 1955; Eagleson et al., 1966). The large number of parameters of these methods has limited their use (Rao and Tirtotjondro, 1995). Thus, the researchers tried to develop a model with lower number of parameters and more acceptable accuracy. Some researchers such as Aron and White (1982), Collins (1983), Rosso (1984), Hann et al. (1994), Singh (1998), Singh (2000), Singh et al. (2007), and Bhunya et al. (2003) proposed relationships for estimating Nash Model’s parameters. Others, including Bahremand and Mostafazadeh (2010), Ahmadin et al. (2010) and Aslani et al.  (2016) used the proposed relationships and estimated the parameters of Nash model in three different basins of Iran.

Precise estimation of the amount of water consumed, irrigation efficiency and water productivity of crops are the most important key indicators in agricultural sector planning of Iran. The figures given for the volume of water used in the agricultural sector are very different and there are serious doubts as to their accuracy. The average of water use efficiency in the country is 1.32 kg/m3 and its annual growth in the last 11 years has been reported to be 0.041 kg/m3 (Abbasi et al., 2017). Therefore, it is necessary to carry out an exploratory work that can be used to quantify the volume of water consumed by various products. Therefore, the main objective of this paper is to measure water consumption of wheat directly and to compare wheat water productivity in different irrigation systems under farmers management in Behbahan.

The volume of application water for wheat in different farms during one season (2016-2017) was measured and compared. The measured values were compared with the crop water requirement estimated by the Penman-Monteith and the national document. To determine the volume of water consumed, firstly, the flow rate of the selected water sources was measured, with the appropriate devices (flumes, meter and micro molina). Farm information including cultivated area, soil texture, soil electrical conductivity, electrical conductivity of the irrigation water used, and farm location with GPS were recorded. Other field information such as irrigation method, irrigation water sources (surface, underground), type of irrigation network (modern, traditional) were also recorded. Effective rainfall was calculated by the SCS method. Crop water requirement using the Penman-Monteith method was determined from data of current year and 10-year data for Behbahan city from the nearest meteorological station.

 32 wheat farms were selected and evaluated, of which 15 farms were irrigated with surface irrigation, 10 farms with sprinkler and 7 farms with drip irrigation systems. The results showed that the yield of wheat varied from 2000 to 6854 kg per hectare. The most water productivity of wheat occurred in a farm with drip irrigation being 2.79 kg/m3. Irrigation application efficiency varied from 22.7 to 99.7%. Updated crop water requirement changed from 373.4 to 517.0 mm. The highest water consumption was measured to be 4626 m3/ha in the farms receiving water from springs. The results of the t-Test analyses showed that the yield in drip irrigation farms (average being 5169 kg/ha) was significantly different as compared to sprinkler and surface irrigation systems with 3574 and 3795 kg/ha, respectively. The results of the comparison of the mean water productivity in the t-Test indicated that drip system with 1.51 kg/m3 of water productivity had the highest values and there was a significant difference with the two sprinkler and surface systems, which respectively had water productivity of 0.90 and 0.88 kg/m3. The Pearson correlation coefficients showed that the trend of changes in the amount of water consumed with the trend of changes in the application efficiency index and water productivity proved uncoordinated and it was significant at 1% level.

 The results of measurements in 32 farms showed that half of the drip irrigation fields were not cultivated on the recommended date range. Therefore, the growth period in this half was less than 140 days. Despite the decline in growing season and the non-observance of planting dates, yield in these farms was over 4000 kg ha-1. Application efficiency in sprinkler irrigation method was more than other irrigation methods. The reason for the high application efficiency in sprinkler irrigation was the backwardness of sowing date on one side and the late harvest of wheat on the other. The surface system with a growth period of 158 days had the highest growth period and has a significant difference with two dripping and sprinkler systems. The surface water system with the volume of water consumed at 4398.7 m3/ha had the highest volume of water consumed and showed a significant difference with the drip system, but this difference was not meaningful compared with the sprinkler system. The volume of water consumed by two systems of drip and sprinkler was measured at 3490.5 and 3863.6 m3/ha, respectively. The backwardness of wheat harvesting time in sprinkler irrigation fields caused the major filling time of the grains to be adjusted to April, which coincided with a higher increase in the air temperature. This led to increased water consumption at this particular time point and caused a significant decrease in water consumption despite the lower consumption of water in the sprinkler system.

A stepped spillway consists of steps that start from near the crown and continue to downstream heel. Generally, the amount of energy dissipation in stepped spillway is more than the one of flat spillways (with no steps) with the same dimensions. The high amount of energy dissipation caused by steps allows reducing the depth of drilling of downstream stilling basin, length of stilling basin, and the height of sidewalls. This way, a considerable economic saving is achieved in the implementation of dams. Since spillways help reduce flow rate and increase intake airflow rate, they can be referred to as a combination of a spillway and an energy dissipater. Some of the studies on stepped spillways are as follows:Launder and Spalding (1972); Olsen and Kjellesvig (1998); Chen et al. (2002); Tabbara et al. (2005); Dermawan et al. (2010); Sori and Mojtahedi. 2015; Haji azizi et al. (2016) So far, the studies on stepped spillways have been mostly on experimental and physical models. However, experimental and physical models are costly and sometimes have limitations such as required space and a large number of tests. This necessities consideration of further mathematical and numerical models. Several numerical models can be introduced to analyze flow on a stepped spillway. CFX is one of the numerical models. CFX has been known as one of the most robust software for fluid flow analysis and heat transfer. The finite volume method (FVM) is a numerical method to solve the governing differential equations, which is capable of simulating complexities of a turbulent flow on a spillway appropriately. On the other hand, CFX numerical model uses the coupled model, which increases the speed to achieve results considerably as compared to other numerical models. This research aims at simulating a stepped spillway using CFX numerical model and assessing the amount of energy dissipation under geometric parameters (such as spillway height, spillway gradient, number of steps, and height of steps) and hydraulic parameters (such as flow rate). The difference between this research and other studies can be attributed to the coherence and correlation in studying various components (geometric and hydraulic parameters) and the ability of CFX numerical number in replacing some of the costly and time-consuming tests.

Heavy, long-term precipitations can lead to severe floods in most drainage basins, thus causing financial losses and casualties (Fotakis and Sidiropoulos, 2014, Avila-Melgar, et al. 2017). Low precipitation, lack of surface water and groundwater, and increased demand for water calls for optimized use of reservoirs and floods. Inevitably, critical points should be identified and simple non-structural and structural methods or a combination of both, which are environmentally friendly and feasible, should be employed for flood prediction and control. In addition to imposing considerable costs, construction of flood control installations cannot fully eliminate the flood risks and, therefore, more severe floods may still lead to disasters. Construction of large flood control structures such as dykes is not only financially unjustifiable, but also inappropriate as solution both environmentally and socioeconomically. Flood prediction and alarm systems are among the non-structural criteria the importance of which are further realized over time. Installation and implementation of smart flood prediction and alarm systems can lead to reduced casualties and damages from both perspectives of flood risk management and nonstructural management.

Intakes are the most significant hydraulic structures, which are also used as inlet structures in outlets to supply water for hydro-electric power, irrigation, and drinking. A major problem for vertical circular spillways is that vortexes are formed on their inlet with several negative effects: reducing discharge coefficient, excessive head formation on spillway inlet, structure vibration, increasing of cavitation formation probability, suction of floating bodies into conduit, excessive oscillations on flow surface, unsteady flow formation, and increasing energy losses are the major consequences. Vortex flows result from flow direction variation, viscosity and surface tension. The flow type causes negative effects in operation of structures such as vertical circular spillway (Kabiri Samani and Borghei, 2001).Taştan and Yildirim (2010) indicated that critical submerged depth for intake in canal with uniform flow equals radius of spherical sink surface, which was finally named critical spherical sink surface. Rankine (1858) represented a model of vortex, namely Rankine compound vortex. In this model, it is assumed fluid particles, which are in the vicinity of vortex center, are solid bodies with high viscosity and rotational motion around their axes (Forced Vortex). The area is located inside nonviscous zone at a distance from vortex center. This research investigates geometric and hydraulic properties of critical sink surface by simulating flow in the environs of vertical intake inlet.

Side weirs are used to control the water level, flow deviations and drain the excess discharge in irrigation networks, sewer systems, and flood control systems. Considering that it is not possible to increase the length of side weirs to increase their capacity, other types of weirs may be used to overcome this problem. Therefore, incorporating weirs that are associated with a higher length of the same width can be helpful. Accordingly, non-linear piano-key weirs may be used side weirs. Numerical methods can be used to estimate the discharge coefficient of piano-key weirs. Bilhan et al. (2011) used an ANN to estimate the discharge coefficient in a curved canal with a labyrinth weir. Ebtehaj et al. (2015) used the GEP model to estimate the coefficient of discharge in a straight canal. Parsaei (2016) studied the accuracy of the ANN in estimating the coefficient of discharge in a sharp-crested rectangular ogee weir and found the ANN to offer an acceptable accuracy. None of the previous studies have addressed the efficiency of intelligent models in estimating the discharge coefficient of ogee-shaped piano-key weirs. Therefore, this study aims to obtain the discharge coefficient of the piano-key weirs using RBF, ANFIS, and ANN models.

Engineers are looking for solutions for flood control and increasing discharge capacity of canals and rivers. Application of labyrinth weir is suggested as a solution for increasing discharge capacity. In this research, labyrinth weir with sidewall angle that was equal to 6°, was simulated through Flow-3D model using experimental results of previous researchers. After validation, the changes of discharge coefficient of weir with angles of 45° and 85° and apex shapes of triangular and half circular shapes were analyzed. Based on the results, discharge coefficients of labyrinth weir with angles of 85° and 45° were on average 2.28 and 1.24 times greater than discharge coefficient of labyrinth weir with angle of 6°, respectively. Also, discharge coefficient of weir with triangular and half circular apex shapes has an increase of 50.29 and 4.15% in comparison with linear apex. Finally, an equation was proposed for prediction the discharge coefficient of labyrinth weir that is able to estimate the discharge coefficient with an acceptable level of accuracy.

Water deficiency or drought is among the most important factors in reducing crop production (Heidari, et al., 2013). Water deficiency or water stress occurs when transpiration is more than water absorption (Alizadeh, 2008). One of the methods that researchers have been studying to increase water use efficiency and performance over the last decade is the use of superabsorbent polymers and deficit irrigation (Khyrabadi, et al., 2014). The superabsorbent polymer is a kind of hydrocarbon, which absorbs water several times as much as its own weight. Due to the drying of the root environment, the water inside these polymers is gradually evacuated and placed at the disposal of the plan, thus the soil will remain moist for a long time without the need for re-irrigation (Abedi Kupai, And Sohrsb, 2005). Considering that the most important advantage of superabsorbent application is reducing the effect of drought stress, this study investigated the effect of deficit irrigation and different levels of superabsorbent on yield, yield components and water use efficiency of lettuce.

 Groundwater has always been considered as one of the main sources of drinking, agriculture, and industrial water, especially in arid and semi-arid regions. Investigating groundwater level changes in any region has an important role in planning sustainable water resources management. Continuous decline of groundwater level has been observed worldwide in the past half-century. Groundwater is the most important and the only source of freshwater in Neyshabour plain. Unallowable discharges of the groundwater resources and the reduction of recharge factors have caused about 200 million cubic meters deficit in Neyshabour aquifer. Therefore, estimating groundwater is vitally important for the management of water resources.

This study was conducted in Neyshabour aquifer in Khorasan Razavi province situated between 58o13' to 59o30' eastern longitude and 35o40' to 36o39' northern latitude. Neyshabour plain has an important role in agricultural productions of Khorasan Razavi. In this study, the fuzzy possibilistic regression and fuzzy least square regression approaches were evaluated in order to forecast the groundwater changes in Neyshabour aquifer. For this propose, the parameters affecting aquifer level, including monthly precipitation, discharge detected, and fuzzy regression approaches were employed to estimate groundwater level of aquifer, and then raster maps were determined by geostatistical methods. Data bank was determined by Arc GIS software from raster maps to train and test fuzzy regression models. 50 percent of data was selected as calibration data and 50 percent of data was selected as validation data in each model. In linear regression, for each series of input variables, only a specific output value is computed, while fuzzy regression models estimate the boundaries of possible values for the output variables. Therefore, unlike the classical regression, which was based on probability theory, the fuzzy regression is based on possibility and fuzzy sets theory. Fuzzy possibilistic regression, introduced by Tanaka et al. (1982), is an approach that provides the best regression equation by minimizing the amount of fuzzy. The general form of this fuzzy regression function is as follows: [ Ỹ =Ã0+Ã1X1+Ã2X2+ Ã3X3+…+ÃnXn (1)where Ã0 and Ã1 are the fuzzy intercept and fuzzy slope coefficients, respectively, and X is the independent variable and the output Ỹ (or dependent variable) is a fuzzy number.Fuzzy least-squares regression (FLSR) method as proposed by Savic and Pedrycz (1991) was adopted for this analysis. For the purpose of current study, the efficiency of the fuzzy possibilistic and fuzzy least square regression models for groundwater prediction in Neyshabour aquifer were compared. Validation and Verification of models were determined based on mean error (ME), root mean square error (RMSE), and coefficient of determination (R2).

 The results of the comparison of the fuzzy possibilistic regression and fuzzy least squares regression models in estimating the groundwater table of Neyshabour plain show that the highest accuracy of water table prediction in the studied aquifer occurred in June and the lowest accuracy occured in January for both fuzzy possibilistic regression and fuzzy least squares regression models. Likewise, in both models, the estimation accuracy of the winter was lower than other seasons. The results of validation of the fuzzy regression model in summer showed that despite a sharp decrease in rainfall in this season, applying inputs with a delay of one to two months had good results in predicting the water level. In agreement with the findings of the present study, previous investigations reported that the ANFIS model with inputs of discharge, total rainfall of the current month, the total rainfall of the previous month, the total rainfall in the past two months, and the groundwater level had the best performance in the prediction of groundwater level of Neyshabour plain (Khashei-Siuki et al., 2013). While in most research done the data used is on a daily or annual basis, it is the monthly changes in the water level which is important: the ascending and descending trends were observed in winter and summer months, respectively. Using monthly forecasts helps managers to make more effective decisions regarding how much water is taken from groundwater resources. Therefore, the aquifer's response to monthly water changes is more effective than annual or daily. Also, the findings of the current study indicated that the fuzzy possibilistic regression model estimated values are more consistent with observed values and provide better estimation of groundwater subsidence and drainage.

 Comparison of the performances of the studied fuzzy regression models showed that the output of both models varies in different months due to fluctuations in the water level. Both fuzzy regression models have a good ability to estimate groundwater table of Neyshabour plain. The results showed that the estimation accuracy of both employed models in winter were lower than other seasons. The best accuracy was observed in May with a RMSE= 6.05, MAE= 6.01 and R2= 0.93 for the fuzzy possibilistic regression model. It is worth noting that according to the model validation indices, the accuracy of the fuzzy possibilistic regression model is more than the fuzzy least squares regression; therefore, the mentioned model can be introduced as an acceptable approach in estimating the groundwater level. It is also suggested that other fuzzy regression models and approaches, including fuzzation of independent variables, should be used in future research.

Conservation tillage systems are recommended by government agencies around the world as an appropriate management option for preserving soil and water resources. Protective tillage has advantages over conventional tillage in terms of reducing energy consumption (Abbaspour et al., 2005). These include reducing erosion of water and wind (Lithourgidis et al., 2007), requiring less labor, increasing soil organic matter, and accelerating time of the second crop (Ito et al., 2007). Here, Manning’s roughness and penetration function are particularly important. More  accurate evaluation, design and simulation of these parameters provide better irrigation systems. If the parameters of the penetration equation are not close to the field conditions, irrigation may cause runoff and deep percolation. Kuotsu et al. (2014) studied the effects of different tillage on soil hydraulic properties and the productivity of rainfed land under rapeseed cultivation in northeastern India. The results of their research showed that infiltration and hydraulic conductivity significantly increased in conservation tillage systems, and the amount of water use efficiency (WUE) was the highest in the conservation tillage system. Considering the necessity of protecting the soil and water resources and the important role of tillage operations, this research investigated the effects of different tillage methods on the hydraulic properties of barley surface irrigation using WinSRFR model.

Khuzestan plain is part of Mesopotamia. This plain was long ago irrigated and drained due to floods (Rangzan and Jafari, 2017). Then, plants started to grow everywhere in this area. With the construction of dams in the past decades, the flooding was hindered; however, since soils were saline, civil plant could not grow anymore (Anonymous, 2011). Therefore, these lands became bare and dust storms started to happen in the plain. In this research, we studied soil salinity and its sources or agents in these area (Ayers and Westcot, 1976). We specially focused on evaluation of dam contractions and effects of the Karoon Rivers’ hydrology regime change on the ecology of certain areas of Khuzestan plain.

We focused on studies done by Rangzan and Jafari on the Karoon River (at Mollasani station) over a forty-year period in order to investigate its discharge and salinity changes (Anonymous, 2011). Dam construction data in the same period were collected. Also, soil salinity and alkalinity were recorded during summer for 6800 hectares in the south of Ahvaz and north of Shadegan Wetland, over a period of 25 years, in 1991 and 2011. Soil EC was also determined in extracted paste in 2017. Sodium absorption ratio (SAR) was calculated from Na, Ca, and Mg concentrations determined in these extracted pastes. Soil salinity and alkalinity (SAR) maps were drawn by Arc GIS Ver. 10.3. For this manure, ECe and SAR were partitioned in 10 levels from 0-90 and polygons were shown in these ranges for all provided maps.

The Karoon River’s discharge data show that maximum charge was 892 m3/s in June 1991, which decreased to 685 m3/s and 359 m3/s in June 2011 and June 2017, respectively. The water salinity of the river increased from 590 µS/cm in 1969 to 745 µS/cm in 1989, and finally to 1643 µS/cm in 2017. This trend can be related to the constructed dams such as Karoon 3 (it was charged in 2005) and upper Godvand in 2012. Also, mean annual precipitation decreased over the same time periods. For instance, mean annual precipitation decreased from 506 mm/year in 1986-1989 to 271.4 mm/year in 2008-2012. These two agents (dam construction and climate changes) decreased the Karoon River’s discharge and increased its EC. The soil salinity is shown in figures (1) a. and b. in 1991 and 2017.

The control of speed and pressure oscillations along the stream, as two critical parameters in designing hydraulic systems, is vital since they have to be set within an acceptable range in order to prevent damages to hydraulic structures. Ead and Rajaratnam (2002) studied the hydraulic jump characteristics on the corrugated bed and calculated the thickness of dimensionless boundary layer to be 0.45. Pourabdollah et al. (2015) investigated the effect of roughness and adverse slope of the bed on the velocity profile and determined the mean shear force coefficient to be 11.5 times more than that of the classical condition. Fiorotto and Rinaldo (1992) stated that in hydraulic jump the pressure is oscillating around the mean pressure value, which is almost equal to piezometric head at each point. Also Lopardo and Solari (1980) determined the pressure oscillations equal to 0.084 for hydraulic jump at downstream of valve. Accordingly, although various studies have been carried out on hydraulic jump characteristics under different conditions, the simultaneous effect of end positive step, bed roughness and adverse slope on hydraulic jump characteristics have not yet been explored. Therefore, the aim of this study was to investigate the velocity profiles, flow surface and pressure oscillations in hydraulic jump within the stilling basin at defined conditions.

Ample research has been done on optimization methods for the exploitation of reservoirs in the form of a specific optimization. In this type of studies, a certain series of flow is provided for the reservoir during the operation period and the release from the reservoir to downstream is optimized under such circumstances. They are certain drawbacks for these models. First, optimal solutions cannot be generalized for other possible inputs to the reservoir. Second, in the event of a change in the flow of input into the reservoirs, it is likely that the optimal solutions are not efficient and the operation of the system in the form of an optimization algorithm should be performed again. In such circumstances, one of the solutions is the use of intelligent methods such as support vector machines to apply the results of system optimization in real time. The main goal of this study is to integrate artificial intelligence methods such as support vector machine with NSGA-II optimization algorithm to convert it to real time. In this structure, contrary to the conventional design of the scheduling, in the event of a change in the flow of input, there is no need to perform re-optimization to understand the optimal coefficients. Instead, the extraction relationship of the support vector machine can be based on the input to the reservoir (at the beginning of the month), the volume of water storage in the tank (at the beginning of the month), reservoir storage changes and downstream needs in the current month to yield optimal release rates in real time.

Nowadays, monitoring of river quality information is one of the most important issues in water resources engineering because of the direct relationship of water quality with environmental health and quality of life. Today, traditional methods of river monitoring are receiving less attention due to the fact that they are costly and time-consuming for the researcher. Instead, the recent, low-cost methods are favorable to many researchers in this filed. Different methods have always been considered for river monitoring, but the application of spectral indicators and remote sensing technologies to control and monitor the water quality of rivers and reservoirs is very cost-effective and could be a good alternative to traditional methods. Since it is time-saving and less costly, it would be a good indicator for the whole region and a good alternative to manual methods (Bonansea et al., 2015). Although satellite imagery has been widely used in estimating water quality indices (Onderka and Pekárová, 2008), the complexity of hydrological systems and the presence of noise in images can increase the calculation error. Wavelet transform and intelligent models are among the most efficient methods that can significantly increase computation accuracy by filtering and noise reduction. Good research has been done on the use of wavelet transform in image processing (Graps, 1995) and fuzzy inference system to estimate water quality parameters (Solgi et al., 2017). In this study, using wavelet transform, Landsat 8 images were processed, then the processed images were considered as inputs of ANFIS model.