Iranian Water Research Journal

Abstract Probabilistic designation is a powerful tool in hydraulic engineering. The uncertainty caused by random phenomenon in hydraulic design may be important. Uncertainty can be expressed in terms of probability density function, confidence interval, or statistical torques such as standard deviation or coefficient of variation of random parameters. Controlling cavitation occurrence is one of the most important factors in chute spillways designing due to the flow’s high velocity and the negative pressure (Azhdary Moghaddam & Hasanalipour Shahrabadi, 2020). By increasing dam’s height, overflow velocity increases on the weir and threats the structure and it may cause structural failure due to cavitation (Chanson, 2013). Cavitation occurs when the fluid pressure reaches its vapor pressure. Since high velocity and low pressure can cause cavitation, aeration has been recognized as one of the best ways to deal with cavitation (Pettersson, 2012). This study, considering the extracted results from the Flow-3D numerical model of the chute spillway of Darian dam, investigates the probability of cavitation occurrence and examines its reliability. Hydraulic uncertainty in the design of this hydraulic structure can be attributed to the uncertainty of the hydraulic performance analysis. Therefore, knowing about the uncertainty characteristics of hydraulic engineering systems for assessing their reliability seems necessary (Yen et al., 1993). Hence, designation and operation of hydraulic engineering systems are always subject to uncertainties and probable failures. The reliability, p_s, of a hydraulic engineering system is defined as the probability of safety in which the resistance, R, of the system exceeds the load, L, as follows (Chen, 2015):

(1)

Where P(0) is probability. The failure probability, , is a reliability complement and is expressed as follows:

(2)

Reliability development based on analytical methods of engineering applications has come in many references (Tung & Mays, 1980 and Yen & Tung, 1993). Therefore, based on reliability, in a control method, the probability of cavitation occurrence in the chute spillway can be investigated. In reliability analysis, the probabilistic calculations must be expressed in terms of a limited conditional function, as follows:

(3)

Where X is the vector of basic random variables in load and resistance functions. In the reliability analysis, if W(X)> 0, the system will be secure and in the W(X) <0 system will fail.
Accordingly, the eliability index, β, is used, which is defined as the ratio of the mean value, , to standard deviation, , the limited conditional function W(X) is defined as follows (Cornell, 1969):

(4)

The present study was carried out using the obtained results from the model developed by 1:50 scale plexiglass at the Water Research Institute of Iran. In this laboratory model, which consists of an inlet channel and a convergent thrower chute spillway, two aerators in the form of deflector were used at the intervals of 211 and 270 at the beginning of chute, in order to cope with cavitation phenomenon during the chute. An air duct was also used for air inlet on the left and right walls of the spillway. To measure the effective parameters in cavitation, seven discharges have been passed through spillway. As the pressure and average velocity are determined, the values of the cavitation index are calculated and compared with the values of the critical cavitation index, . At any point when , there is a danger of corrosion in that range (Chanson, 1993).
In order to obtain uncertainty and calculate the reliability index of cavitation occurrence during a chute, it is needed to extract the limited conditional function. Therefore, for a constant flow between two points of flow, there would be the Bernoulli (energy) relation as follows (Falvey, 1990):

(5) Where  is the atmospheric pressure,  is the unit weight of the water volume,  is the angle of the ramp to the horizon,  is the curvature radius of the vertical arc, and  is the flow depth perpendicular to the floor. Therefore, the limited conditional function can be written as follows:

(6)

Flow-3D is a powerful software in fluid dynamics. One of the major capabilities of this software is to model free-surface flows using finite volume method for hydraulic analysis. The spillway was modeled in three modes, without using aerator, ramp aerator, and ramp combination with aeration duct as detailed in Flow-3D software. For each of the mentioned modes, seven discharges were tested.
According to Equation (6), velocity and pressure play a decisive and important role in the cavitation occurrence phenomenon. Therefore, the reliability should be evaluated with FORM (First Order Reliable Method) based on the probability distribution functions For this purpose, the most suitable probability distribution function of random variables of velocity and pressure on a laboratory model was extracted in different sections using Easy fit software. Probability distribution function is also considered normal for the other variables in the limited conditional function. These values are estimated for the constant gravity at altitudes of 500 to 7000 m above the sea level for the unit weight, and vapor pressure at 5 to 35° C. For the critical cavitation index variable, the standard deviation is considered as 0.01. According to the conducted tests, for the velocity random variable, GEV (Generalized Extreme Value) distribution function, and for the pressure random variable, Burr (4P) distribution function were presented as the best distribution function. The important point is to not follow the normal distribution above the random variables.Therefore, in order to evaluate the reliability with the FORM method, according to the above distributions, they should be converted into normal variables based on the existing methods. To this end, the non-normal distributions are transformed into the normal distribution by the method of Rackwitz and Fiiessler so that the value of the cumulative distribution function is equivalent to the original abnormal distribution at the design point of . This point has the least distance from the origin in the standardized space of the boundary plane or the same limited conditional function.
The reliability index will be equal to 0.4204 before installing the aerator. As a result, reliability, , and failure probability, , are 0.6629 and 0.3371, respectively. This number indicates a high percentage for cavitation occurrence. Therefore, the use of aerator is inevitable to prevent imminent damage from cavitation. To deal with cavitation as planned in the laboratory, two aerators with listed specifications are embedded in a location where the cavitation index is critical. In order to analyze the reliability of cavitation occurrence after the aerator installation, the steps of the Hasofer-Lind algorithm are repeated. The modeling of ramps was performed separately in Flow-3D software in order to compare the performance of aeration ducts as well as the probability of failure between aeration by ramp and the combination of ramps and aeration ducts. Installing an aerator in combination with a ramp and aerator duct greatly reduces the probability of cavitation occurrence. By installing aerator, the probability of cavitation occurrence will decrease in to about 4 %. However, in the case of aeration only through the ramp, the risk of failure is equal to 10%.

Abstract Karst aquifers are one of the most important water resources in the world. The importance of karstic aquifers comes from the fact that they provide about 25%of the world's drinking water (Ford and Williams 2007). In addition, the in karstic aquifers contain high quality water resources and they are suitable for drinking water. Springs are one of the most important hydrogeological phenomena of the hydrological cycle (Fiorrilo 2014). In karst systems, the dissolution channels are mainly connected to the karst springs. Therefore, evaluation of discharge, its variability and values of electrical conductivity and major ions can reflect the properties of the total system (Rezaei 2000). To study the hydrochemical characteristics of groundwater flow systems, comprehensive information on groundwater chemistry is used which depends on various factors such as location geology, rock weathering and its type, water quality of feeding into the aquifer, and hydrogeochemical reactions (Coetsiers and Walraevens 2006). Hydrogeological characteristics of karstic aquifers are very difficult to study due to the high heterogeneity of aquifers (Mohammadi and Raeisi 2007, Mohammadi and Field 2009). Therefore, one of the common and low-cost methods for studying karst aquifers in the last four decades is to study the temporal variations in the physical and chemical characteristics of karst springs(Raeisi et al. 2006) .Due to the physicochemical properties of the springs, some characteristics of the of water movement pathway and the type of dominant flow system can be found. The spring discharge variability is the most important criterion in characterizing the dominant flow system type (Karami et al. 2008). Most of the researchers have mentioned that the widespread use of springs in the karst studies is due to their reliable interpretations for the characteristics of karstic aquifers (Mohammadi and Field 2009). In the west of the Mojen region, there are extensive outcrops of calcareous formations in which karstic aquifers are formed. There are several large and small karstic springs emerging from this karstic aquifer that has not been studied so far. Therefore, the main purpose of this research is to investigate the hydrogeological and hydrogeochemical characteristics of the karstic springs of west Mojen and determine the dominant flow system in karstic aquifer feeding these springs. In order to evaluate the dominant flow system type and discharge mechanism of karst springs in west Mojen, the physical and chemical properties including discharge, electrical conductivity and temperature, major anions and cations were measured. The geological map of the studied region was prepared using the geological map of Shahrood with the scale of 1:100000 as well as field observations. The precipitation and temperature data-sets for the Mojen region were collected from the Shahrood Regional Water Company and Meteorological Organization. According to the results obtained in this research, the temporal variations in the physical (discharge) and chemical (electrical conductivity) characteristics of the discharging water from karstic springs in west Mojen are relatively low. Therefore, the coefficient of variations of all parameters indicates the dominant diffuse flow system in the karstic aquifer of these springs. In addition, the recession curve of the studied springs has a coefficient of discharge with a gradient of 0.009, which indicates the dominant diffuse flow system in that karstic aquifer. Such small discharge coefficients are consistent with the geomorphological characteristics of the studied region. The karst springs in the studied region are overflow springs, which the main reason for the emergence of these karst springs in this location is the contact massive limestone (i.e. karst aquifer) and impervious marls and marly limestone. The hydrochemical diagrams related to samples prepared from the studied springs in June 2017 show that all samples are high in Ca²⁺ and HCO₃^-, and are located in a specific range of karst waters. The ratio of Ca²⁺ to Mg²⁺ ion is used to determine the predominant aquifer in karst areas. The average ratio of Ca²⁺ to Mg²⁺ ions for the studied samples is about 2.60, which can be concluded that the predominant lithology of the studied karstic aquifer is limestone. In this research, the primary catchment area of the springs was drew. Then, precision of this primary catchment area was evaluated by the water budget method and comparing its values of annual discharge and recharge volumes. According to the mentioned comparison, a relative error of 0.8%was obtained. Due to the insignificant relative error between annually recharge and discharge volumes and as well as the stratigraphic status in the region, the drawn catchment area is quite accurate.

Abstract The river, as the main artery and natural drainage, plays a significant role in the transmission of floods. During floods, the water crosses the main section of the river and enters the floodplains. In this case, the river crossing becomes a compound cross section. Compound channels consist two hydraulic sections: main channel and floodplain. Natural rivers are rarely in direct flow because of the regulating energy grade-line, and usually have a curved path to which it is referred to as "meandering channels". In meandering rivers, the floodplain width is constantly changing according to the topography of the region. The change of the floodplain width has a significant role on the hydraulic conditions of the flow during the floods. Therefore, the aim of this study is to investigate the effect of changing the width of the floodplain and the relative depth of the channel on the flow velocity and shear stress of the bed in the meandering compound channels, using numerical modeling.
In this research, using FLOW3D software, the flow velocity and bed shear stress in meandering compound channel under the influence of floodplain width change and relative depth are evaluated. For this purpose, four sections of meandering compound channels with floodplain widths of 3.3, 4.31, 5.32 and 6.33 m, and relative depths of 0.26, 0.35 and 0.45 m have been used. According to studies performed on compound channels, the RNG turbulence model has better adaptation to laboratory data, therefore it has been employed used in the current study. In this study, the boundary conditions applied to the numerical model are for the channel’s upstream boundary, the volume flow rate and for the downstream boundary of the Outflow. The boundary condition of the wall was used to apply the boundary conditions in the floor and side walls of the channel. The upper surface of the flow field was also defined as symmetry boundary conditions in the model. The laboratory data of Liu et al. (2014) were used to validate and control the results extracted in the present study. In the laboratory study of Liu et al., the flow conditions in channels FA1, FA2 and FA3 (according to Table 1) were investigated. In the present study, the data of the depth averaged velocity in CS1 section, stage-discharge curve and the ratio of transverse velocity to longitudinal velocity in CS1.5 sections were used for validation. In order to evaluate the accuracy of the numerical model results, after examining the different meshes according to Table 3, the Root Mean Square Error (RMSE), according to Equation 5, has been used. The root error value of depth averaged velocity in CS1 section is 0.081 and 0.052 m/s for the relative depths of 0.45 and 0.35, respectively, and 0.025 m3/s for the stage-discharge curve, which indicates the appropriate accuracy of the flow simulation by the software.
The results of the numerical simulation show that by increasing the floodplain width, the depth averaged velocity and bed shear stress are reduced. Therefore the maximum flow velocity changes by increasing the floodplain width from 3.3 to 6.33 m (92% increase), from 0.51 to 0.39 m/s (24% decrease) and the depth averaged velocity at relative depths of 0.45 and 0.26 are reduced by 17% and 21%, respectively; and the rate of depth averaged velocity change is more noticeable due to a change in the floodplain width for low relative depths. The effect of changing the floodplain width on the bed shear stress has the highest value in the mid-section between two apexes (CS3 section); therefore, an increase of 92% in the floodplain width in the mid-section (CS3), resulted to a 35% decrease in bed shear stress. The shear stress of the inner arch wall of the main channel is higher than the shear stress of the outer arch wall. In each channel, the maximum shear stress of the wall occurs near the bankfull level of the main channel (h = 0.14) and by increasing the relative depth, the wall shear stress increases. By increasing the relative depth and flow depth in the main channel and floodplain, the average depth velocity and shear stress in the bed increases.

Abstract With the growth of population and industry, human demand for consumables and consequently waste production has increased. The purpose of this study is to investigate the biological, physical and chemical purification of hazardous wastewater using membrane bioreactor (MBR) method. The MBR method is a combination of an active sludge suspension system and a membrane separation process. These membrane filtration systems have been extensively tested and have been quite effective in removing organic and inorganic contaminants.
In this study, 185 L leachate from a landfill with a semi-continuous flow regime and polypropylene halo fiber membrane were used. For this reactor, two polyethylene tanks with the total capacity of 200 L were considered as feed tanks. The temperature was 21° C and the pH inside the reactor was about 9. Considering the sludge age of 30 to 35 days and the hydraulic retention time of 15 days, the MLSS was about 6300 mg/L. For diffuser aeration speeds of 2 and 4 cubic meters per hour, the amount of dissolved oxygen for each was 2.3 and 3.2 mg / l, respectively.. It seems that COD above the inlet leachate would be greatly reduced if ozone, pure oxygen, high aeration rates, and hydraulic and microbial retention time were used.
In the first step, after determining the sludge age and stability of the results from the reactor outputs, the results were recorded within 30 days. The amount of 1733 mg/L COD was reported as the average output. As the rate of dissolved oxygen increases, the amount of nitrite, which is known to be toxic for microorganisms, also decreases. The amount of nitrite in and out of the reactor has always been in the range of 0.5 to 1 mg/L (less than 1 mg/L). By reducing the aeration rate, the amount of active biomass present in the reactor decreases. Based on the results, the COD and BOD concentrations were about 2514 and 1247 mg/L, and the removal efficiencies were 96 and 93%, respectively, which significantly reduced the BOD removal. The nitrate concentration decreased in this state. The nitrite concentration increased significantly up to 20-times, indicating the completion of nitrification process. The turbidity reduction, measured in NTU 59, will be about 69%, which is 9% less than normal. In addition, about 98.83 and 96.14% of the input iron load can be eliminated using MBR systems with high aeration rates. At high and low aeration rates, the iron removal rates were about 96.14 and 94.4%, respectively. The reduction of zinc content using MBR system with aeration speed of 4 cubic meters per hour is 86% and with aeration speed of 2 cubic meters per hour is approximately 82.2%. While the removal of zinc in the RO system is about 85.8%. About 14% of zinc cannot be removed using the RO system. Also, about 15% of the copper present in the leachate has the particles size less than 0.001 ?m and cannot be removed by RO and in this experiment it was found that about 76% of the copper is less than 0.1 ?m in size and was not reducible.
In order to have MBR process with an economically justified use for purification, some parameters such as the type of membrane, physical conditions and quality of membrane output and economic considerations must be considered. Comparison between the activated sludge system and the MBR shows that MBR is much more common in the MLVSS aerobic process than the activated sludge system and its purification concentration reaches to about 7 g/L, which is due to the chemical factors and ions. In MBR systems, high efficiency of BOD removal and nitrification can be jointly achieved. Based on the results of this study, about 99% of BOD was removed and the nitrification removal efficiency reached about 97%. The MBR system is well-suited for the treatment of strong wastewaters, such as leachate treatment. Due to the high concentration of COD and BOD output from MBR, the use of RO for purification due to rapid clogging cannot be justified unless there is no longer a viable solution.

Abstract WaterGEMS is a software that provides a numerical model, which simulates different parameters in water distribution systems based on the hydraulics principles. The most remarkable chemical substance used in water refinement procedure is chlorine. Therefore, WaterGEMS software models the chlorine to detect its concentration in each pipe of the water distribution system. If the chlorine concentration exceeds 3 mg/lit, it would be dangerous for the Man health. In addition, the model may calculate water age in water distribution networks and trace the chlorine substance. In this research, the chlorine concentration, water age and chlorine trace parameters have been simulated using WaterGEMS for a case study: Vahidieh district (located on the west part of Tehran province). Meanwhile, other quantitative parameters including flow discharge, flow velocity and water head loss in pipe networks, have also been calculated in Vahidieh water distribution network system. This is done because there are important relationships between qualitative and quantitative parameters for the optimization design of water distribution networks. For more comfortable comparison and interpretation of the above concept, three pipes in different places of Vahidieh water distribution network have been chosen (i.e. 18th,168th and 293th pipes put in the left, middle and right side of water distribution network, respectively).
The innovation of the present study was to provide quantitative and qualitative parameters for the simulation of Vahidieh region, where it has not yet been found out up to now. In addition, modeling all the mentioned parameters will result in a comprehensive view to the design of water distribution networks. Aghasi (2018) presented a model using WaterGEMS to determine appropriate points for chlorine injection in Mashhad water distribution network and located the appropriate points based on the network geometry, pipes’ diameter and consumption pattern . Javadinejad et al. (2019) utilized a pump and gravitational statuses in Semirom water distribution using WaterGEMS. They stated that in pumping method, water qualitative management may guarantee a better system. Vidhi and Geeta (2019) simulated a rural region in India using WaterGEMS indicating the remained pipes’ chlorine concentration are at standard levels (i.e. less than 3 mg/lit).
In the software, the analysis of water distribution networks is given step by step as: Step 1, network drawing based on the nodes’ coordinates, pipes’ situation, reservoirs, tanks and other elements. Step 2, defining the network hydraulic traits. Step 3, defining the distribution network for hydraulic performance. Step 4, defining the network analysis method. After that by running the software, the network parameters would be obtained. Finally, the network quantitative and qualitative results may be achieved. The population of Vahidieh town’ water distribution network, where used as a case study, will be 78600 persons at the end of 30 years design period resulting in total water consumption of 215 lit/day per capita. While the amount of water consumption in the region has been estimated 195 lit/s. There are two tanks and two reservoirs in the new water distribution network system. The volume of each tank and reservoir is 500 and 5000 m3, respectively. Meanwhile, a chlorination house with the maximum chlorine injection of 3 mg/lit has been designed for disinfection. The pipes were made of polyethylene. For modeling Vahidieh town water distribution network using WaterGEMS software, at first, the nodes and pipes were drawn using AutoCAD software. Then, the reformed information were imported to the WaterGEMS software. In this step, it is necessary to extract nodes’ altitude codes from ArcView software. Then, other elements of network, consumption pattern and different scenarios were defined and finally, the reports were analyzed and the results were obtained.
The numerical simulation reproduced the complex flow patterns in the pipes network associated with a particular water consumption in the Vahidieh water distribution network that are presented as a case study. Based on the analysis made by applying WaterGEMS, the following results were obtained:
The chlorine concentration in 18th, 168th and 293th pipes were selected and have been studied, in more details. Meanwhile, three defined scenarios were used: (1). The primary concentration in nodes, tanks, pumps, valves and reservoirs were 0.1, 0.5, 1, 1 and 2 mg/lit, respectively. (2). The chlorine concentration reaches to 10 mg/lit in reservoirs, while its concentration is the 1st scenario in other ingredients. (3). The chlorine concentration reaches to 5 mg/lit in tanks, while its concentration is the 2nd scenario in other ingredients.
Based on the obtained numerical model reports, the water age in the 18th pipe was higher than the 168th and 293th. According to the Vahidieh town population distribution, the 18th pipe was surrounded by less population in comparison with the other two pipes. In addition, in, the maximum water age of the 18th pipe was 3 times of the 168th pipe. According to the WaterGEMS reports, under different scenarios, the chlorine concentration in 168th pipe was equal to the injected chlorine concentration to the reservoirs (the pipe which is closer to reservoirs). In addition, the 168th pipe chlorine concentration was 10% higher than the other two pipes in all the scenarios. The chlorine concentration computation in the selected pipes indicates much higher influence on the reservoirs’ chlorine concentration than chlorine concentration in water distribution network pipes. Furthermore, based on the third scenario, when the chlorine concentration increases in the tanks, there is not tangible variation in pipes chlorine concentration because of the higher volume of reservoirs in comparison with the tanks' volume. The obtained results reveals that the maximum water provision probability of 18th pipe from the 1st tank is about 45%. Additionally, the 168th pipe’s water provision probability from two reservoirs is the same. Also, the 293th pipe water has surely been supplied from the 2nd tank. In addition, the flow velocity, water head loss and water discharge can be studied in each 24-hour period based on hourly consumption pattern. Based on the WaterGEMS outputs, the maximum water flow velocity in the 18th pipe is 0.3 m/s. This result is reasonable due to the higher water age in the pipe in comparison with the other two pipes. As a consequent, it seems that sedimentation probably occurs along the 18th pipe. Moreover, the 168th pipe reaches a maximum head loss of 0.4 m, and the 293th pipe receives a maximum water discharge of 8 lit/s.

Abstract The optimization of agricultural water consumption is very important due to the limitation of water resources and its value in agriculture. Two methods of field experiments and simulation models can be used to determine the best irrigation plan. The first method, in addition to requiring multiple field trials, also includes limitations such as limitation of location and conditions of the test and the short time of running test. On the other hand, simulation models are a suitable choice to improve management of water consumption in the field due to the quantitative impacts of water on crop performance. In this study, the optimization of water consumption and dominate cropping pattern for five major crops of winter wheat, barley, forage corn, grain corn and canola, in the Qazvin plain irrigation network were evaluated.
Qazvin irrigation network, in Qazvin province, is located at 150 km-West of Tehran. It is located between 36 20 N, 49 40 E and 36 00 N, 50 35 E. In the present study, a model was developed in the MATLAB programming environment 2017 and linked to the ant colony optimization (ACO) algorithm and the AquaCrop plant growth model. The AquaCrop simulation model is able to assess the crop production under different irrigation water management. Before using the AquaCrop, it is necessary to be calibrated and validated for different plants using appropriate field data at the study’s regional level or regions near to it. For this purpose, the results of the study of Ramezani et al (2017) were used which they used Golkar (1998) for calibration and validation of wheat plant parameters, Farhadi Bansoole (1998) for barley, and Mirlatifi and Sotoodenia (2002) for maize. In addition, the studies of Rahimikhoob et al (2014) were used for forage maize plant and Amiri et al (2017) was used for rapeseed. Extra-heuristic search algorithms, such as the (ACO algorithms, significantly help to solve water resource (Afshar et al., 2015) and management problems (Nguyen et al., 2016). Using ACO can increase the possibility of finding optimal or near-optimal solutions and increase computational efficiency by reducing the amount of search space during the optimization process. Research method was as follow: first, crop, soil and meteorological data from Excel file was exported to the MATLAB code, and the economic productivity for each crop with different irrigation scenarios with connection to Aqua crop model, was calculated and its maximum was determined. Then, by using ACO algorithm and given to water and crop area limitations, optimal crop pattern for all crops under water cultivation of Qazvin irrigation network in three possible water allocation states was obtained so that the network profit would be maximized.
Three different modes of available water volume were considered as A, B and C with supplying 100, 70 and 60% mean of long-term volume of water resources, respectively.. Three different scenarios of depth and irrigation water interval were defined: 1- Depth and similar irrigation interval for autumn and spring crops 2- Depth of different irrigation water and similar interval for autumn and spring crops 3- Depth and different irrigation interval for autumn and spring crops.
The 1, 2 and 3 scenarios were implemented for each of the A, B and C modes. For A, the optimum irrigation schedule was 8-day interval and the irrigation water depths of 25 and 40 mm were determined for autumn and spring crops, respectively. For B, the optimum irrigation schedule was 10-day interval and the irrigation water depths of 24 and 48 mm were determined for autumn and spring crops, respectively. And for C, the optimum irrigation schedule was 8-day interval and the irrigation water depths of 16 and 40 mm were determined for autumn and spring crops. The optimal planting pattern was determined for different scenarios. The maximum area under cultivation in case of 100% water supply was 23029 hectares and by reducing it to 40 and 30% water volume, the area under cultivation will be reduced to 18512 and 17188 hectares, respectively.

Abstract Water scarcity is a physical metric that refers to the volumetric abundance of water supply and consumption during normal periods. It is typically calculated as a ratio of human water consumption to available water in a specific area. Addressing the scarcity of freshwater (blue and green) is vital for sustainable water resources management (Liu et al., 2017). Blue water (BW), freshwater flowing in groundwater, rivers, lakes or other surface water bodies, is directly used for human consumption (Veettil and Mishra, 2016) and green water (GW) is the portion of freshwater stored in the unsaturated soil layer and vegetation canopy that is available indirectly (Veettil and Mishra, 2016). The BW footprint is the amount of consumptive water used by humans. On the other hand, the GW footprint refers to the indirect use of freshwater by humans to produce goods and provide services and, therefore, it is equal to actual evapotranspiration from an agricultural area (Falkenmark and Rockstr?m, 2006; Gerten et al., 2011; Hoekstra et al., 2011; Kounina et al., 2013; Liu et al., 2017). The sustainable development goal 6 in 2030 Agenda, adopted by heads of nations, relates to water scarcity in target 6.4, which was monitored by water stress indicator 6.4.2 (Vanham et al., 2018). The indicator 6.4.2 is the ratio of total freshwater withdrawn by all sectors to the water availability (total renewable freshwater resources minus environmental flow requirement) in a given region (Liu et al., 2017; Vanham et al., 2018).
The objective of this study is to assess the scarcity and vulnerability of blue and green water resources over three watersheds of Karaj, Latian and Mamlu Dams (Tehran and Alborz Provinces) using Soil and Water Assessment Tool (SWAT) during 1995-2013.
Blue and green water resources are quantified using SWAT that is calibrated for the three watersheds during 1995-2013. The SWAT is developed and parametrized using ArcSWAT 2012 interface. The watershed is delineated using a 30-m digital elevation modeling data, resulting in 8 sub-basins. The major land uses over the study area are pasture (~92.7%) and agriculture (~6.4%). Soil layers are Leptosols (83.7%), Regosols (13%) and Solonchak (3.3%) (FAO/IIASA/ISRIC/ISSCAS/JRC, 2009; Iranian Water Resources Management Company, 2018). Each watershed was classified into five slope ranges of 0-10, 10-20, 20-40, 40-60 and >60%, and divided into 203 hydrological response units (HRUs). Daily data from ten climatic stations were used by SWAT to capture the spatial precipitation variation within the study area. The precipitation lapse rate of 356 mm/km was included in the model for ten elevation bands that are defined at each sub-basin. The temperature lapse rate of -6.5 ?/km was included for snowfall modeling. The minimum and maximum monthly snowfall rates were 1 and 8 mm, respectively, for all sub-basins based on the long-term observed snowfall rates at Tehran and Abali climatic stations within the watershed. Daily outflow of the Latian dam is included in SWAT during the operation period of 1991-2013. Potential evapotranspiration and surface runoff were calculated using the Hargreaves and SCS curve number methods, respectively. Scarcity was evaluated using the ratio of GW footprint to available GW and vulnerability was evaluated using the ratio of GW footprint to historical low available GW in specific sub-basin and month (Veettil and Mishra 2016). The GW footprint and availability are equal to actual evapotranspiration (ET) and initial soil water content (?SW?_i) in HRU output of the SWAT, respectively (Veettil and Mishra 2016). Scarcity was evaluated using the ratio of BW footprint to available BW and vulnerability was evaluated using the ratio of BW footprint to historical low available BW in specific sub-basin and month (Veettil and Mishra 2016). The BW footprint is equal to consumptive water use within a sub-basin and available BW is the volume of water that can be abstracted from a river without affecting the river-dependent ecology (Hoekstra et al. 2011; Veettil and Mishra 2016). The presumptive standard method allows using 20% of the river flow for consumption and leaving 80% for sustaining the environment (Veettil and Mishra 2016). Thus, available BW in a sub-basin is equal to 20% of the long-term mean monthly discharge of the river.
The results for calibration (1995-2007) and validation (2008-2013) periods indicate that the SWAT simulates the daily discharge well at eight hydrometric stations. The results reveal that the annual scarcity and vulnerability indices for GW were 0.388 and 0.66, while for BW were 0.65 and 1.04, respectively. The watersheds of Karaj and Mamlu dams experience minimum and maximum BW scarcity and vulnerability and on the other hand, the maximum and minimum GW scarcity and vulnerability over the study area, respectively. The scarcity and vulnerability assessment of water resources (blue and green water) in a given watershed can highlight the ecological hotspots (regions under water stress) and provide analysis for sustainable water resources planning and management. For example, BW allocation and conveyance among sub-basins can reduce the water stress in ecological hotspots.

Abstract Due to the limited water resources, there is too much emphasis on the efficient use of the present water resources for irrigation. Magnetized water can be used for the reclamation of water and soil. The usage of magnetic water in agricultural production will enable intense and more quantities and qualitative production. Marigold (Calendula officinalis L.) is one of the oldest medicinal plants, which is used for the pharmaceutical industries. In order to evaluate the effects of different growth beds and magnetized water on the growth and yield characteristics of marigold flower. Safana (31) showed that irrigating the plants with magnetized water of 1000 and 1500 GS had significant increases in height, leaf number, flower number, and fresh and dry weight characteristics of marigold, plants except number of flowering days, while the irrigation with normal water gave the minimum average for all the studied characters, except number of flowering days. The results obtained from some studies showed that the combined application of different substrates (Treatment No. 4: garden soil + spent mushroom compost + Rice bran + manure at a volume ratio of 25%) significantly increased the leaf area (47.76 cm2), plant height (24.60 cm), shoots and flowers’ dry weight (0.043 and 0.014 g respectively), chlorophyll a and total chlorophyll. The highest root dry weight (0.0056 g) was observed on treatment No. 7 (garden soil + spent mushroom compost + manure at a volume ratio of 33%) and treatment No. 8 (garden soil + manure at a volume ratio of 50%) (24).
Greenhouse research was carried out to study the simultaneous effect of irrigation with magnetized water and different soil textures on the growth and yield properties of Marigold plant, with three replications as pot planting under greenhouse conditions in Ferdowsi University of Mashhad during 2019. The research station is located in north-east of Iran at 36° 16' N latitude and 59° 38' E longitude and it is 958 m above the sea level. The experiment was performed as the factorial arrangement in a completely randomized design with three replications including two factors; magnetic field levels consisted of four levels of 0, 0.3, and 0.6 Tesla, and soil texture treatments consisted of three levels of silty clay, clay loam, and sandy loam. The obtained data (branches, leaf, root, stem, and flower’s dry weights, flower and leaf number, root length, root volume, and height) were analyzed using statistical software of SAS. Ver. 9.0 and the means were compared using LSD range test at 5%.
The results showed that the soil texture on dry weights of branches, leaf and stem, flower number, root volume, and height were significant at 1% level (P

Abstract Agricultural water usage efficiency is one of the important goals of water productivity improvement program of Jahad-e Agriculture Ministry in Iran. In this case, the determination of appropriate irrigation scheduling, which is consisted of irrigation depth and frequency, is a key strategy. Many of the country’s agricultural plains are under traditional irrigation scheme and unlike modern irrigation networks have a more complex consumption pattern. This study was carried out to determine the irrigation depth and scheduling of major orchards of Honam sub-catchment of Karkheh River Basin (KRB), in order to optimize agricultural water consumption at basin level.
Honam sub-catchment was selected as the research pilots of KRB. Nineteen irrigation homogenous units supplied from joint water resources were delineated using ArcGIS 10.3 to predict irrigation depth and frequency of cropping pattern in 913.8 ha irrigated lands of study area. In addition, the land use map of crops and orchards in the irrigated lands was prepared by field survey and combining satellite images of irrigation channel, cultivation type and their distribution. The 15-years (2000 – 2014) data of Alashtar weather station were collected and the reference evapotranspiration (ET0) was calculated based on Penman-Montith method using ET Calculator software. Moreover, the length of plant growth period of cultivation pattern was determined by completing a questionnaire. Then, evapotranspiration of cropping pattern (ETc) was calculated considering proposed Kc of FAO-56. Effective rainfall was deducted from ETc and finally, irrigation requirement of crops and orchards were calculated by subtraction of ETc and effective rain as ten-day, monthly and entire growth period. The related soil physical properties for irrigation purposes including soil texture, Field Capacity (FC), Permanent Wilting Point (PWP) and water holding capacity, were measured at different soil depth at each irrigation homogenous units.
The net irrigation requirement of winter wheat in Honam sub-basin was calculated to be 318.1 mm. The maximum amount of net irrigation required for wheat was 112 and 5.7 mm in May and March, respectively. The annual and monthly maximum and minimum irrigation requirements for sugar beet were 842.3, 204.4 and 19 mm, respectively. For mixed orchards, the annual irrigation requirement was 993.4 mm, and the monthly maximum and minimum irrigation requirements were 230.2 and 14.8 mm, in August and April, respectively. For alfalfa, the annual irrigation requirement was 1190.7 mm, and the monthly maximum and minimum irrigation requirements were 284.4 and 7 mm, in July and March, respectively. Among the crops, the maximum irrigation requirement was related to alfalfa and then mixed orchard, and the minimum irrigation requirement was related to winter wheat with 318.1 mm during the growing season. The results also showed that the most of the irrigation homogenous units soil texture were silty clay loam and clay. Due to the favorable rainfall in autumn, winter and April, the plant's water requirements are met by rainfall. Therefore, no irrigation is required except in May and June. Wheat irrigation period in May was calculated as 16 days on average among all water units, and 11 days in June. In June, when the maximum water requirement of wheat occurs, the maximum irrigation interval for wheat is 13 days in all-homogenous units of 4 and 14 and the minimum irrigation interval is 10 days in all-homogenous units of 6, 10, 12 and 16. The irrigation interval for sugar beet in May was 21 days on average among the same homogenous units and in June. The irrigation intervals for sugar beet in July, August, September and October were 11, 7, 8 and 11 days, respectively. In July, when the maximum water requirement of sugar beet occurs, the maximum irrigation interval was 9 days in homogenous irrigation units of 14 and 15, and the minimum irrigation interval was obtained 7 days in irrigation units of 6, 10, 12 and 16. The irrigation periods for orchards and horticultures among all units in June, July, August, September and October were 17, 10, 10, 12 and 19 days on average, respectively. Alfalfa irrigation interval is shown in the units of 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, and 19 of irrigated lands of Honam sub-catchment. Meanwhile, its irrigation intervals among all irrigated units in April, May, June, July, August and September were 29, 21, 10, 7, 7 and 10 days on average, respectively.

Abstract Deficit irrigation was investigated for major crops in the west of Qazvin plain irrigation network in order to reduce the water consumption in the agricultural section, and provide suitable method for the conjunctive use of surface and groundwater resources in the irrigation networks. Solving the optimization problem of conjunctive management models for surface and groundwater resources using meta-heuristic algorithms can be considered as one of the efficient solutions. In this regard, comprehensive studies have proved the ability of these algorithms. The purpose of this study is to manage the conjunctive use of surface and groundwater using Gravitational Search Algorithm (GSA) with the objective of maximizing annual Net Benefit (NB) in water scarcity conditions.
The study area is the west region of the Qazvin plain’s irrigation network. The scenarios consist 30 items, combination of 6 levels of deficit monthly irrigation percentage (0, 0-10, 0-20,0- 30, 0-40 and 0-50%) and 5 levels of groundwater allocation percentage (80, 85, 90, 95, 100% of maximum extraction).
Based on SPI drought index, the water year 86-87(2007-2008) was selected as the base year of drought. In this year, the allocation of surface water was about 30.1 million m3 and the total groundwater extraction for agriculture was estimated to be about 126.7 million m3. The optimization model was prepared based on the GSA. The crop pattern in the study area was selected based on the crops in the latest pattern suggested by Jihad Keshavarzi, including fall crops of wheat, barley and rapeseed, and summer crops of sugar beet, tomato, corn- and fodder-maize. The gardens’ composition maintained and their water demands were subtracted from the total water consumption.
The decision variables in this optimization model were 82 items, which include 7 cultivation areas, 12 monthly surface water extractions, 12 monthly groundwater extractions and 51 monthly irrigation demands for different crops that were separately defined by specific limits in the program. The dimension and iteration numbers were 100 and 200,000, respectively. The amounts of water demand for the selected crops were calculated separately. The potential evapotranspiration was calculated from the data of Qazvin Synoptic Station using CROPWAT8 program with the calculation method of modified Penman-Monteith FAO.
The limits of the optimization model include a limit related to the maximum annual volume of surface water allocation, a limit related to the maximum annual volume of groundwater allocation, 12 limits related to the amount of monthly allocation of surface and groundwater resources, and a limit related to the maximum area of optimal crop areas. In order to define the yield function of the main crops, the results of Tafteh research (2014) in Qazvin plain were used. The optimization model was executed for different scenarios and the results were analyzed.
In comparison between scenarios with equal level of deficit irrigation, the percentage of fall crops increases along with decreasing the groundwater extraction, and in comparison between scenarios with equal groundwater extraction, the percentage of fall crops increases along with increasing the deficit irrigation percentage, Also, in scenarios with equal level of deficit irrigation, the percentages of wheat and tomato increase slightly along with decreasing groundwater extraction.
Increasing the percentage of wheat and rapeseed cultivation in fall crops and decreasing the percentage of tomato, corn and fodder maize cultivation are other changes in the cultivation pattern in the condition of deficit irrigation. Decreasing the volume of groundwater extraction and increasing the deficit irrigation levels cause decrease and increase in the area of cultivation, respectively.
In full irrigation treatment by selecting the optimum crop pattern, groundwater extraction reduces from 5 to 20% and groundwater resources saved up to 25.3 million m3 while NB decreases from 1.7% to 10.9%. Also by increasing the amount of deficit irrigation to 50% in scenarios with equal groundwater extraction, the NB decreases by about 6.4% to 10.7%. In comparison of the NBPD (Net Benefit Per Demand) between different scenarios, the scenarios with 20% reduction in groundwater extraction and the one with full irrigation obtained the highest value of NBPD, and the scenarios with deficit irrigation up to 40 and 50% obtained the lowest value of NBPD.
The deficit irrigation operations caused an increase in cultivated areas from 41 to 54% at deficit irrigation percentage of 50% compared to the full irrigation treatments, although it reduces the NBPD by the maximum amounts of 5.9 to 10.3%. In general, the rate of decrease in the NBPD percentage is less than the rate of decrease in the groundwater extraction percentage and the rate of increase in the deficit irrigation percentage, due to the high productivity resulted from deficit irrigation and optimal water use.
In all scenarios, most of the water demands were supplied from groundwater resources (about 77.0 to 80.8% of the total demand) and the rest from surface water resources. Almost in all scenarios about 63 to 100% of the annual demands were supplied and in the most critical months at least 50 percent of the demands were supplied.
The highest percentage of annual deficit irrigation was 37% and observed in scenario including reduce groundwater extraction equal to 20% and deficit irrigation up to 50%. In scenarios with the same percentage of deficit irrigation, with a 20% reduction in groundwater extraction, the water supply was reduced by a maximum amount of 5%, and in scenarios with the same groundwater extraction volume and different percentages of deficit irrigation, the water supply was reduced by a maximum amount of 37%. Therefore, the GSA optimization model was able to solve the problems of conjunctive optimization of surface and groundwater resources by providing a model of optimal crops in water scarcity conditions and flexibility in different percentages of irrigation, while increasing the area of cultivation.

Abstract Millet (Pennisetum glaucum L.) is one the conventional cereals in arid and semi-arid areas of tropical regions. Environmental stresses such as drought stress is one of the important factors restricting the plant growth in the most regions of the world and preventing from obtaining the potential yield of crop plants. Deficit irrigation is a suitable method for achieving economic and acceptable yield using the consumption of minimum volume of irrigation water. Nitrogen is one the most important nutrients for production systems of crop plants. Some studies reveal that the higher water productivity can be obtained by fertilizer consumption. According to the shortage of water resources in arid region of Kashmar and to attention of this point that many people in this region are occupied to agriculture and livestock, the necessity of appropriate water resources management in planting of millet is not avoidable. To this purpose, the objective of this study was to investigate the grain yield and water productivity of proso millet under deficit irrigation conditions and consumption of different levels of nitrogen fertilizer.
A field experiment including four irrigation regimes, three nitrogen fertilizer levels and two plant densities, was conducted based on completely randomized block design as split-split plot with three replications in Agricultural Research and Natural Resources Center of Kashmar, during 2018. The irrigation treatments were full irrigation providing 100% irrigation water requirement and deficit irrigation treatments providing 40, 60 and 80% irrigation water requirement as main plots; fertilizer treatments including 0, 50 and 100 kg/hanet nitrogen as sub plots; and plant density treatments including 10 and 20 plant/m2 as sub-sub plots. Each plot including six rows plant sowing had 5 m length and 50 cm spacing. There were two rows no sowing as spacing between sub main plots. A 3 m distance was considered as space between main plots.
For computing of crop water requirement, moisture changes in root zone was used. The soil water content was measured daily, using TDR. The net irrigation requirement for full irrigation was determined by following relation:
I_n=(?_fc-?_i )×D_r
Where, In: net irrigation requirement (mm), ? Fc: water content at field capacity, ?i: soil water content before irrigation event, and Dr: root development depth (mm).
The irrigation water volume for each plot was measured using counter. There was no effective rainfall during the growth period. The plant height, yield and yield components including grain yield and 1000-grain weight were measured and results’ analysis was done by SPSS software.
Variance analysis of results showed that interaction among irrigation regimes, different levels of nitrogen fertilizer and plant density was significant at the level of 1% on plant height, 1000-grain yield, grain yield, harvest index and water productivity.
The results showed that applying deficit irrigation caused a significant decrease in plant height, 1000-grain weight, grain yield and water productivity at 1% probability level. The grain yield for full irrigation treatment compared to 80, 60 and 40% irrigation water requirement was 17, 31.6 and 47.8% higher, respectively. In all irrigation treatments, the consumption of 100 kg/ha nitrogen fertilizer increased the grain yield significantly in comparison with the same treatments with no use of nitrogen fertilizer. The maximum amount of grain yield was 2259 kg/ha for full irrigation, 100 kg/ha nitrogen fertilizer and 10 plant/m2 treatment. For 80 and 40% irrigation water requirement treatments and 100 kg/ha nitrogen fertilizer level, increasing the plant density from 10 to 20 plant/m2, decreased the grain yield 5.6 and 6.3%, respectively. The minimum and maximum amounts of water productivity were 0.56 and 0.8 kg/m3, in 40 and 100% water irrigation requirement treatment, respectively. The consumption of 100 kg/ha nitrogen fertilizer increased the water productivity significantly in all irrigation treatments in contrast to no use of nitrogen fertilizer. The amount of increase in water productivity for 100 and 80, 60 and 40% water irrigation requirement treatments was 16.2, 5.8, 6.2 and 8.4%, respectively. The harvest index for irrigation treatments of 100, 80 and 60% irrigation water requirement had no significant difference at the level of 5%. The maximum and minimum harvest indices were determined in 100 and 40% irrigation water requirement treatments, respectively.
Based on the results obtained from this research, it can be stated that providing 100% irrigation water requirement, consumption of 100 kg/ha nitrogen fertilizer and plant density of 10 plant/m2 is recommended for Proso millet in Kashmar region.

Abstract Many variables such as volume and concentration of point and non-point pollutants, land use and geology, geometric and morphological characteristics, time and place of river sampling and etc., can affect the changes of water quality parameters in a river. Modeling is a suitable tool for managing water resources in terms of quantity and quality. Rivers are the most important water resources that can be used in arid and semi-arid regions. In recent years, quality management of rivers has become particularly important due to the discharge of various pollutants. The literature review shows that the Qual2kw model has a good ability to model the water quality parameters and evaluate the self-purification of the rivers. The objective of this research is to investigate the accuracy of Qual2kw model in simulation of the water quality parameters of Sefidrud river at the bottom of the dam. For this purpose, sampling and conducting field and laboratory studies for 12 stations in the range of 110 km in two summer (August) and autumn (November) seasons has been done. From 9 out of 12 sampling stations are located on the main tributary of the Sefidrud river and the other 3 stations are located on the tributaries of the Sefidrud, including Tutkabonrud, Tarikrud and Zilakirud. In addition to the water quality parameters such as temperature, pH, electrical conductivity, total suspended solids, dissolved oxygen, chemical and biochemical oxygen demand, total nitrogen, total phosphorus and fecal coliform, also the hydraulic characteristics of the flow such as depth, velocity and discharge were measured at these stations.
In this study, the Qual2kw model has been used to simulate the eight main parameters of the water quality including water temperature, pH, electrical conductivity, total suspended solids, soluble oxygen, biochemical oxygen demand, total nitrogen and total phosphorus. The hydraulic model was developed based on the Manning formula to simulate the flow characteristics including depth, velocity and discharge. The tributaries of the Sefidrud river (Tutkabon, Tarikrud and Zilakirud) were considered as sources of the pollutants in the model. The length of 110 km of the Sefidrud river between the dam and the Caspian Sea was divided into 70 unequal reaches in order to achieve more accurate results. The measured data on August and November 2019 are used to calibration and validation stages in the Qual2kw model, respectively. Auto calibration of the model was carried out by genetic algorithm after initial setup of the model. Three evaluation criteria including normalized root mean square error (NRMSE), mean bias error (MBE) and correlation coefficient (R) were used to measure and simulate the water quality parameters.
Due to the flow regulation in the Sefidrud river and its dependence on the amount of release from the dam, the maximum and minimum flow have been recorded in August and November 2019, respectively. The results of the flow’s hydraulic parameters indicate that the model is underestimate and overestimate in the minimum (November 2019) and maximum flows (August 2019), respectively. This is due to the additional withdrawals from the river in the high-flow and input runoff into the river in the low-flow conditions, which there is no accurate data for them. However, the values of depth, velocity and flow rate have been simulated with an acceptable accuracy in the calibration and validation steps. The results showed that the Qual2kw model was able to simulate the water quality parameters of Sefidrud river. The changes in quality parameters along the Sefidrud river indicate an improvement in water quality from the outlet of the Sefidrud dam to the entrance to the Caspian Sea. So that the amount of dissolved oxygen in Sefidrud river increases from upstream to downstream indicating the proper self-purification in the Sefidrud river. The results represented that the best and worse accuracy of the model in the base of average NRMSE values in calibration and validation stages are 3.3 and 47.5% for pH and total nitrogen parameters, respectively. The highest correlation values between the measured and simulated values for the parameters of total solids and electrical conductivity were equal to 0.97 and 0.96, respectively, in the model calibration stage. The results of the present study indicate the appropriate capability of the Qual2kw software in modeling the water quality parameters of the Sefidrud river. Generally, this study showed that by regulating the amount of flow released from the Sefidrud dam, the water quality parameters can be managed on river’s downstream. However, the changes in the quality parameters have many complexities and many factors may affect them.

Abstract Corn is one of the most important crops that is well adapted to arid and semi-arid regions. Amount and quality of irrigation water has an important effect on its yield. Therefore, different researchers have tried to study the effect of different irrigation methods and qualities on corn’s yield and biomass. The Irans arid and semi-arid climate confirms that it is necessary to study the best irrigation methods along with different qualities of irrigation water on the growth of this crop. In order to save time and money, crop models have been proposed to simulate the response of plants to different field conditions. AquaCrop, provided by the Food and Agriculture Organization (FAO), is one of the best crop models due to the simplicity, low input data, user-friendliness, high accuracy and acceptable proximity of modeling conditions.
The present study was conducted using data collected by Minaei (2014) in a research farm in Ahvaz during two cropping seasons (2012-2013) on corn crop. In this research, irrigation types (D: sprinkler irrigation with saline water, F: sprinkler irrigation with saline and fresh water, and S: surface irrigation) and water quality (S1: 2.5, S2: 3.2, S3: 3.9, S4: 4.6 and S5: 5.1 dS.m-1) were examined. The minimum salinity was selected equal to the available water source as S1 treatment, which was the Karun River. On the other hand, the maximum salinity was also considered as S5, to reduce the corn yield by 50%. The S2, S3 and S4 treatments were also the intermediate between these two treatments.
The highest and lowest differences between the simulated and observed yields were 0.7 and 0.1 ton.ha-1, obtained from SS5 and FS1 treatments, respectively. The average of these values was equal to 0.3 ton.ha-1. It can be concluded from the results that the model had an average proximate error of 300 kg. Based on the results, the maximum and minimum values of the biomass differences were 2 and 0.1 ton.ha-1, obtained from SS3 and FS3 treatments, respectively. The average difference was 0.7 ton.ha-1. Comparison of biomass results and yield showed that the differences in results between yields were less than those in biomass. If these results are expressed as a percentage; the highest and lowest differences between the observed and simulated yield values were 223 and 31%, respectively. The highest and lowest percentages of these differences in biomass were 252 and 12.6%, respectively. By increasing water salinity, the yield and biomass decreased linearly. These results were observed in all three irrigation treatments. The canopy cover results simulated by the AquaCrop confirm these results (Figure 3). As it can be seen in the figures, the increase in salinity caused a rapid decrease at the end of the growing season. The maximum and minimum differences between the simulated and observed water use efficiency were 0.08 and 0.001 kg.m-3, respectively. The average difference was 0.03 kg.m-3.
Based on these results, the AquaCrop had an underestimation error in simulating corn yield in all three irrigation methods. The accuracy of this model was almost the same in all three irrigation methods and was in the excellent category. However, according to Table (5), the efficiency of this model based on EF statistics for each of the used irrigation methods was less than the determined value. The AquaCrop in simulating sprinkler irrigation with saline water (D) had an underestimation error to simulate corn biomass. This model had an overestimation error in simulating corn biomass in the two F and S irrigation methods. The accuracy of this model in simulating corn biomass in S method was less than sprinkler irrigation. The efficiency of AquaCrop in biomass simulation was desirable. The accuracy and efficiency of this model in simulating the water use efficiency of corn in all three irrigation methods were almost the same and acceptable. Comparison of two NRMSE statistics for two parameters of performance and water use efficiency represented that the model was more accurate in simulating performance.
According to the results, AquaCrop had acceptable efficiencies for simulation of yield, biomass and soil salinity. However, its efficiency for water use efficiency was not acceptable. In addition, the AquaCrop’s results were the same for all three irrigation types. Then, irrigation type had not any effect on AquaCrop’s accuracy and efficiency.

Abstract Climate variations are one of the most important factors affecting water resources. Severe floods and runoff increase the risk of the vulnerability of hydraulic structures. The failure of an embankment dam causes extensive financial, human, and environmental damages. Overtopping and internal erosion are the main causes of the embankment failure. More than 46% of the embankment failures around the world are attributed to overtopping. The breach process during this event is generally divided into two parts: the breach initiation stage; and the breach development stage. In the initial stage, the outflow discharge from the dam is not considerable and includes a small stream along the channel, while in the breach development stage, the outflow and erosion processes are significant. On the other hand, about 48% of failures and accidents affecting embankment dams are related to piping. In an embankment dam failure, accurate determination of flow, time, and breach characteristics along with the analysis of hydrograph components can play an important role in reducing the financial losses and fatality.
Several equations have been established using literature data and field observations to calculate the peak outflow discharge (Qp) as a function of the height of water above the breach (Hw) and stored volume above the breach (Vw) (Costa 1985; Gupta and Singh 2012; Hooshyaripor et al. 2014; MacDonald and Langridge?Monopolis 1984; Pierce et al. 2010). The failure time (tf) has been investigated by various researchers. The tf equations were obtained as a function of the average breach width (Bave) (USBR, 1988), Hw, or their combination (Von Thun & Gillette, 1990). Therefore, the height of breach (Hb) and Vw are also considered as important parameters (Froehlich, 2008). On the other hand, Hb is found to be an important factor affecting the hydraulic and breach characteristics (Dhiman & Patra, 2019; Wang et al., 2020).
In this research, physical models with different geometrical and mechanical properties have been used to investigate the mechanisms of erosion and breach evolution. Therefore, several experimental models were constructed and tested in the laboratory flume at three heights of 0.3, 0.4, and 0.5 m. Therefore, five different soil combinations were used and studied. The breach hydrograph components were analyzed, and the breach characteristics were examined as well as the hydraulic characteristics. The BREACH mathematical model is one of the most common models used to evaluate the breach parameters and output hydrographs in embankment dam failures. This model is developed by the National Weather Service (NWS) and is based on the principles of hydraulics, hydrology, and geotechnics. In overtopping failures, the flow over the crest is calculated by the broad-crest weir formula. While the flow into the pipe is simulated by the orifice equation. The results of the model are compared with the observations of some historical failures, which indicates the higher accuracy among the existing mathematical models. In the present study, the output hydrograph components of the experimental models were also compared with the historical data obtained from the BREACH mathematical model. Gene Expression Programming (GEP) was employed as one of the artificial intelligence methods along with the nonlinear regression to obtain a suitable relationship between the input parameters of the models. In order to evaluate the efficiency of the models, three statistical indices, including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and coefficient of determination (R2) are used for performance assessment of the proposed equations in the present study. To develop new equations for the determination of Qp, there are several input variables, that were not introduced before. Therefore, multiple combinations of datasets including historical, experimental, and the hypothetical failure of real dams have been used in this study. Based on observations, the values of tf are highly correlated with hydraulic and breach characteristics. Therefore, new relations have been proposed based on those parameters. On the other hand, the newly introduced equations related to the Hb can lead to more accurate assessment of the breach process in the overtopping and piping failures.
According to statistical analyses, the values of R2 for the proposed equations of Qp, obtained from GEP, as well as nonlinear regression, were 0.84 and 0.84, respectively, based on the breach parameters. The values of the recent coefficient for the development of tf relations obtained from the regressions were 0.87 and 0.88, respectively, according to the hydraulic and breach characteristics. By application of GEP for the determination of Hb in both overtopping and piping failure cases, the values of R2 were 0.99 and 0.99, respectively, as a function of the embankment and hydraulic characteristics. Soil gradations play an important role in increasing the erosion rate and reducing the tf. Therefore, breach formation in coarse-grained particles will take less time to evolve due to its lower shear stresses compared to fine-grained soils. Similarly, the Bave has a significant effect on the breach output hydrograph and its components. The Bave variations based on Hw defined in this study, could cover a wide range of embankment dam failures.

Abstract There are various methods for assessing and regulating flow in order to protect the environment. In total, 207 methods have been identified for determining the environmental flow of rivers in 44 countries around the world, which can be classified into four general methods, including the hydrological method, hydraulic rating, habitat simulation, and holistic methodologies. Among these methods, the hydrological method has been the most used due to its ease of use, access to data and short calculation time. The aim of this study is to determine the environmental flow of Balikhluchay river in Ardabil, using Tennant, Tasman and flow continuity methods. Also, the effects of Yamchi dam construction on environmental and hydrological flow in downstream of the river were investigated and analyzed using IHA software.
To achieve the objectives of the present study, some hydrological methods have been used. The input data in these methods is the daily runoff data of the Pole Almas station. The research stages are based on two main steps of calculating the river's environmental flow from 1970 to 2013 without considering the Yamchi dam and applying the Tennant, Tessman and Flow duration curve methods in different months of the year. According to the Tennant criteria, values of 10, 30 and 60% of the mean annual flows, respectively, are allocated as minimum flows, for Short-term survival of fish, maintaining relatively good survival status and maintaining suitable habitat. In Tessman method, if the 40% of mean annual flow was greater than the mean monthly flow, then the average monthly flow would be considered as the minimum monthly flow, otherwise, 40% of mean annual flow would be considered as the minimum monthly flow. The flow duration curves, by presenting the relationship between the amount and frequency of the river flow, show the full range of river discharges, from drought to flood events. The flow duration curves include information on river water planning, drinking use, or construction of diversion dams. In this method, the daily average data is first sorted in descending order. The next step is to investigate and analyze the effects of the Yamchi dam construction (before and after the dam construction in 2004) on environmental and hydrological downstream flows of the river using IHA software.
The results showed that the Tennant method calculates the river flow between 1.96 to 3.27 m3/s to keep the river flow regime at the optimum range for all months of the year, while Tessmann method calculates 1.31 m3/s. The results of the FDC indicate that for the protection of the river in suitable and relatively suitable conditions, the flow rate of 2.95 and 2.46 m3/s was required, respectively. The results of the flow duration curve method can be useful to simulate the historical flow regime to maintain good or moderate environmental conditions and to provide a management model for the protection of the Balikhluchay river as well as early planning. The flow duration curve method estimated the environmental flow values more than other methods. The Tenntant method also estimates the environmental flow values less than the other two methods. In all months of the year, the Tenant method estimates the amount of environmental flow less than the Q75. In some months, Tasman method has estimated the amount of environmental flow less than the Q75 and in some months more than the Q75. The results of the periodicity and continuity of the pulsating behavior of the Balikhluchay river in low and high water periods, showed that before and after the construction of Yamchi dam, the duration of low-flow pulse has little hydrological change. However, the hydrological change degree of the wetness period pulse in terms of frequency and continuity is moderate and high, respectively. Changing these parameters can cause the movement of organic and food materials between the river and floodplain, the frequency and severity of soil moisture stress for plants, the frequency and duration of plant oxygen-free activities stress, and the effect on substrate transport, channel sediment texture and duration of disturbance. The intensity of flow decrease and increase in the period after the dam construction has had moderate changes. Generally, it was found that the dam’s operation has influenced downstream hydrological and environmental parameters. The extent of these effects on hydrological parameters such as magnitude of monthly water conditions, magnitude and duration of annual extreme water conditions, timing of annual extreme water conditions, and frequency and duration of high and low pulses status were 61.38% with moderate change degree. Also, despite the dam, 51.6% of the environmental parameters such as monthly low flows, extreme low flows, small floods and large floods have changed.