مجله پژوهش آب ایران
پیاپی 40 (بهار 1400)

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, ps, 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): p_s=P(L≤R) (1) Where P(0) is probability. The failure probability, p_f, is a reliability complement and is expressed as follows: p_f=P[(L>R)]=1- p_s (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, W(X)=W(X_L ,X_R)as follows: p_s=P[W(X_L ,X_R)≥0]= P[W(X)≥0] (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, μ_W, to standard deviation, σ_W, the limited conditional function W(X) is defined as follows (Cornell, 1969): β=μ_W/σ_W (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, σ_cr. At any point when σ≤σ_cr, 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): σ= ( P_atm/γ- P_V/γ+h cos⁡θ )/(〖V_0〗^2/2g) (5) Where P_atm is the atmospheric pressure, γ is the unit weight of the water volume, θ is the angle of the ramp to the horizon, r is the curvature radius of the vertical arc, and h cos⁡θ is the flow depth perpendicular to the floor. Therefore, the limited conditional function can be written as follows: W(X)=(P_atm/γ- P_V/γ+h cos⁡θ )/(〖V_0〗^2/2g) -σ_cr (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 x_(i*). 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, p_s, and failure probability, p_f, 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%.

The studied region is located at 8 kilometer of west Mojen in the south of Mojen waterfall, a part of the Shahrood county. In order to study the hydrogeological and hydrogeochemical characteristics of springs in the area, discharge, electrical conductivity and temperature were measured from October 2017 to November 2018. Also, the concentrations of the main ions including Ca2+, Mg2+, Na+, K+, HCO3-, SO42- and Cl- have been measured in the water and environment laboratory of Shahroud University of Technology. The obtained results showed that the coefficients of variations for the physical and chemical characteristics for all springs are negligible and confirm the dominant diffuse flow system in the study area. Recession curve of the studied springs has solely one coefficient of discharge (α) with a gradient of 0.009 which indicates the dominant diffuse flow system in that karstic aquifer. One of the main reasons for the emergence of the springs in the studied region is contact of groundwater in the karstic catchment of these springs (Limestone rock formations of the Cretaceous and Lar) with impervious units (marls and marly limestone). According to the springs of the area are overflow springs and all these springs are drained from an aquifer. 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+ ion to Mg2+ ion concentration is used to determine the predominant aquifer in karst areas. The average ratio of Ca2+ ion to Mg2+ ion for the studied samples is about 2.60, which can be concluded that the predominant lithology of the studied karstic aquifer is limestone. Also in this research, the primary catchment area of the springs was drawed. 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 percent was obtained. Due to the negligible relative error between annually recharge and discharge volumes and as well as the stratigraphic status in the regionin the region, the drawn catchment area is quite accurate.

In this research, using FLOW3D software, the flow velocity distribution and shear stress of the bed in meandering compound channels due to the change of floodplain width and relative depth were investigated. For this purpose, four sections of meandering compound channels with floodplain width having 3.3, 4.31, 5.32 and 6.33 meters and three relative depths of 0.26, 0.35 and 0.45 have been used. The results of numerical simulation show that by increasing the floodplain width, the depth averaged velocity and bed shear stress are reduced. So that with a 92% increase in floodplain width, the maximum flow velocity in the main channel decreases by 24% , and the depth averaged velocity at relative depths 0.45 and 0.26 are reduced by 17% and 21%, respectively; and the rate of change of depth averaged velocity is more noticeable due to a change in the width of floodplain 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); so that by 92% increase in the floodplain width in the mid-section (CS3), the bed shear stress is reduced by 35%. Also, the amount of boundary shear stress in the inner arch wall in all channels which is higher than the boundary shear stress in the outer arch wall; and the maximum amount of wall shear stress occurs near the bankfull level of the main channel and by increasing the relative depth, the wall shear stress increases.

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 μm and cannot be removed by RO and in this experiment it was found that about 76% of the copper is less than 0.1 μm 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.

WaterGEMS software provides a numerical model which simulates different parameters in water supply systems based on the principles of hydraulics. The most remarkable chemical substance used in water refinement procedure is the chlorine. Hence, WaterGEMS software models the chlorine to detect its concentration in each pipes of the water supply system. If the chlorine concentration exceeds 3mg/lit, it would be dangerous for the Man health. In addition, the model may calculate water age in water supply networks. And more, the WaterGEMS can trace the chlorine substance as well. In this research, the chlorine concentration, water age and chlorine trace parameters have been simulated by WaterGEMS for a case study: Vahidieh district (located on the west part of Tehran province). Meanwhile, other quantitative items have also been calculated in Vahidieh water supply network system. For example, flow discharge, flow velocity, water head loss in pipe networks. This is because, there are important relationships between qualitative and quantitative parameters for the optimization design of water supply networks. For more comfortable comparison and interpretation of the above concept, three pipes in different places of Vahidieh water supply network have been chosen (i.e. 18th,168th and 293th pipes put in the left, middle and right side of water supply network, respectively). The innovation of present research work is to provide quantitative and qualitative items for the simulation of Vahidieh region where it has not yet been found out up to now. In addition, modeling of all mentioned items will result in a comprehensive view to the design of water supply networks. A miniature previous research work on the subject is mentioned. Aghasi (2018) who has presented a model by WaterGEMS to determine appropriate points for injecting of chlorine in a part of Mashhad water supply network. He concluded that the appropriate points for chlorine injection dependent upon the network geometry, pipes diameter and the pattern of consumption. Javadinejad et al. (2019) utilized a pump and gravitational statuses in Semirom water supply by 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 by WaterGEMS. They resolved that the remained chlorine concentration in the pipes are in standard status (i.e. less than 3mg/lit).

The WaterGEMS numerical model has been designed by Haestad Methods company. Meanwhile, it is dependent upon the American hydraulics council. In the software, the analysis of water distribution networks is given step by step as: firstly, network drawing based on the nodes coordinates, pipes situation, reservoirs, tanks and other elements. Secondly, defining the network hydraulic traits. Thirdly, defining the distribution network for a hydraulic performance. Fourthly, defining the network analysis method. After that by running the software, the network parameters are obtained. Finally, the network quantitative and qualitative results may be achieved. The Vahidieh town water supply network where used as a case study; its population will be 78600 person at the end of 30 years design period. In so, for the total consumption of water will be 215lit/day per capita. The amount of water consumption in the region has been estimated 195lit/s. There are 2 reservoirs and 2 tanks in the new water supply network system. Volume of each reservoir is 5000m^3 and the volume of each tank is 500m^3. Meanwhile, a chlorination house has been designed to disinfect the region water that the maximum chlorine injection will be 3mg/lit. The pipes material was polyethylene. For modeling Vahidieh town water distribution network by WaterGEMS software, first of all, the nodes and pipes are drawn by AutoCAD software. Secondly, the reformed information imports to the WaterGEMS software. In this step, it is necessary to extract nodes altitude codes from ArcView software. Thirdly, other elements of network, consumption pattern and different scenarios are defined. Finally, the software reports will be analyzed and the results are obtained.

In this paper, a successful simulation has been carried out of a water supply network using WaterGEMS software. The numerical simulation reproduced the complex flow patterns in the pipes network associated with a particular water consumption in the Vahidieh water supply network are presented as a case study. On the basis of the analysis made by applying WaterGEMS, the following results are obtained: The chlorine concentration in 18th, 168th and 293th pipes were selected and have been studied, in more detail. Meanwhile, three defined scenarios are used: (1). Primary concentration in reservoirs, tanks, pumps, valves and nodes are 2, 0.5, 1, 1, 0.1 mg/lit. (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 upon the numerical model reports in 18th pipe, water age is higher than that of 168th and 293th pipes. According to the Vahidieh town population distribution, less population surrounded by 18th pipe in comparison to the other two pipes. Plus, in 18th pipe, the maximum water age is 3 times of maximum water age in 168th pipe. According to the WaterGEMS reports, under the different scenarios, chlorine concentration in 168th pipe is equal to injected chlorine concentration to reservoirs (the pipe which is closer to reservoirs). In addition, 168th pipe chlorine concentration is 10% higher than the other two pipes under three scenarios. The chlorine concentration computation in the selected pipes indicates much higher influence on the reservoirs chlorine concentration on chlorine concentration in water supply 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. The reason is that much higher volume of reservoirs in comparison with the tanks volume occurs. Based upon the obtained results from WaterGEMS reveals that in 18th pipe the maximum water provision probability from the 1st tank is about 45%. Additionally, 168th pipe water provision probability from two reservoirs is the same. Also, 293th pipe water has surely been supplied from 2nd tank. As well, flow velocity, water head loss and water discharge can be studied in each 24hour period based on hourly consumption pattern. Based on the WaterGEMS outputs, the maximum water flow velocity in 18th pipe is 0.3 m/s. This result is reasonable, because of water age item in the pipe which is higher than that of the other two pipes. As a consequent, it seems that sedimentation probably occurs along pipe 18th. Moreover, 168th pipe reaches a maximum head loss of 0.4 meter, and 293th pipe receives a maximum water discharge of 8lit/s.

Optimization of agricultural water consumption is very important due to the limitation of water resources and its value in agriculture. Simulation models are a valuable tool for improving management of water consumption in the field because of the quantitative impacts of water on crop performance. In the present study, a model was developed in the MATLAB programming environment 2017 and linked to the ant colony optimization algorithm and the AquaCrop plant growth model. Three different modes of available water volume were considered: A- supplying 100% medium long-term volume of water resources b- supplying 70% medium long-term volume of water resources c- supplying 60% medium long-term volume of water resources. 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. Scenarios 1, 2 and 3 were implemented for each of the modes A, B and C. For case A, the best schedule of irrigation interval of 8 days and irrigation water depth 25 and 40 mm were obtained for autumn and spring crops, respectively. For case B, irrigation interval of 10 days and irrigation water depths of 24 and 48 mm were obtained for autumn and spring crops. And for case C, the best irrigation schedule was 8 days and depths of 16 and 40 mm for autumn and spring crops were determined. The optimal planting pattern was determined for different scenarios. Maximum area under planting in case of 100% water supply is 23029 hectares and by reducing 40% and 30% water volume, the area under planting will be reduced to 18512 and 17188 hectares, respectively.

“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 given area. Addressing the security 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). Green water (GW) is the portion of fresh water stored in the unsaturated soil layer and vegetation canopy that is available indirectly (Veettil and Mishra, 2016). The BW footprint is amount of consumptive water use by humans. The GW footprint refers to the indirect use of freshwater by humans to produce goods and services and, therefore, it is equal to actual evapotranspiration from an agricultural area (Falkenmark and Rockström, 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 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 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 the observation period 1995-2013.

Hydrologic model: Blue and green water resources are quantified using SWAT that is calibrated for three watersheds during the observation period 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. Dominant land uses are pasture (~92.7%) and agriculture (~6.4%) over the study area. Soil layers are Leptosols (83.7%), Regosols (13%) and Solonchak (3.3%) (FAO/IIASA/ISRIC/ISSCAS/JRC, 2009; Iranian Water Resources Management Company, 2018). Thes watershed is classified into five slope ranges of 0-10%, 10-20%, 20-40%, 40-60% and >60% and divided to 203 hydrological response units (HRUs). Daily data from ten climatic stations are included in SWAT to capture the spatial precipitation variation within the study area. The precipitation lapse rate (356 mm/km) is included in the model for ten elevation bands that are defined at each sub-basin. The temperature lapse rate (-6.5 ℃/km) is included for snowfall modeling. Minimum and maximum monthly snowfall rates are 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 (1991-2013). Potential evapotranspiration and surface runoff are calculated using the Hargreaves and SCS curve number methods, respectively. Scarcity and vulnerability assessment for green water: Green water footprint refers to indirect use of freshwater by humans to produce goods and services and it is equal to actual evapotranspiration from an agricultural area (Hoekstra et al. 2011). The green water scarcity and vulnerability are calculated using the following equations (Veettil and Mishra 2016): 〖GW〗_(scarcity(i,t))=〖GW〗_(footprint(i,t))/〖GW〗_(availability (i,t)) (1) 〖GW〗_(vulnerability(i,t))=〖GW〗_(footprint(i,t))/〖GW〗_(availability(P30)(i,t)) (2) in which 〖GW〗_(footprint(i,t)) is the green water footprint, 〖GW〗_(availability (i,t)) the available green water and 〖GW〗_(availability(P30)(i,t)), the historical low available green water in sub-basin i during time t. The green water footprint and availability are respectively equal to actual evapotranspiration (ET) and initial soil water content (〖SW〗_i) in HRU output of the SWAT (Veettil and Mishra 2016). Scarcity and vulnerability assessment for blue water: Blue water scarcity and vulnerability are calculated using the following equations (Veettil and Mishra 2016): 〖BW〗_(scarcity(i,t))=〖BW〗_(footprint(i,t))/〖BW〗_(availability (i,t)) (3) 〖BW〗_(vulnerability(i,t))=〖BW〗_(footprint(i,t))/〖BW〗_(availability(P30)(i,t)) (4) in which 〖BW〗_(footprint(i,t)) is the surface water footprint, 〖BW〗_(availability (i,t)) the available surface water for consumption and 〖BW〗_(availability(P30)(i,t)) the historical low availability of surface water in sub-basin i during time t. Surface blue water footprint is the amount of consumptive water use (Rodrigues et al. 2014; Veettil and Mishra 2016). The 〖BW〗_availability is the amount of water which can be abstracted from a river without affecting 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). 〖BW〗_(availability(i,t))=Q_((i,t))-〖EFR〗_((i,t)) (5) 〖EFR〗_((i,t))=0.8Q_(mean(i,t)) (6) where Q_((i,t)) is the river flow (m3/s), 〖EFR〗_((i,t)) the environmental flow requirement (m3/s) and Q_(mean(i,t)) the long-term mean monthly discharge in sub-basin i.

Results for calibration (1995-2007) and validation (2008-2013) periods indicate that SWAT simulates well the daily discharge at eight hydrometric stations. Results reveal that annual scarcity and vulnerability indices for green water are 0.388 and 0.66, respectively, while scarcity and vulnerability indices for blue water are 0.65 and 1.04, respectively. The watersheds of Karaj and Mamlu Dams respectively experience minimum and maximum blue water scarcity and vulnerability, but they respectively experience maximum and minimum green water scarcity and vulnerability over the study area. 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, therefore, provide analysis for sustainable water resources planning and management. For example, blue water allocation and conveyance among sub-basins can reduce the water stress in ecological hotspots.

Due to limited water resources, there is too much emphasis on the efficient use of 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 had been used for the pharmaceutical industries. In order to evaluate the effects of different growth bed and magnetized water on growth and yield characteristics of marigold flower. Safana (31) showed that irrigation plants with magnetized water of (1000 and 1500 GS) gave a significantly increasing in height, leaf number, flower number, fresh and dry weight characteristics of marigold plants expect number of flowering days, while the irrigation with normal water gave lowest the average for all the studied characters expect number of flowering days. The results of some of 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 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 growth and yield properties of Marigold in the 3 replications as pot planting under greenhouse conditions in Ferdowsi University of Mashhad during 2019. Research Station is located in north-east of Iran at 36° 16' N latitude and 59° 38' E longitude and its height from sea level is 958 meters. 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 (0, 0.3, and 0.6 Tesla) and Soil texture treatments consisted of three levels (Silty clay, Clay loam, and sandy loam), which were applied on the plant. Data obtained (branches, leaf, root, stem, and flower dry weights, flower and leaf number, root length, root volume, and height) were analyzed using statistical software SAS. Ver. 9.0 and the means were compared using LSD range test at 5 % percent.

The results showed that soil texture on branches dry weight, leaf dry weight, stem dry weight, flower number, root volume, and height were significant at 1 percent level (P<0.01), and on flower and root dry weights and leaf number were significant at 5 percent levels (P<0.05). the effect of magnetized water on branches dry weight, leaf dry weight, root dry weight, flower dry weight, height, flower number, branches number, height, and root volume were significant at 1 percent level (P<0.01) and root length was significant at 5 percent level (P<0.05), while interaction of magnetized water and soil texture on the branches, root, and flower dry weights were significant at 1 percent level (P<0.01) and root and stem dry weight and root volume were significant at 5 percent levels (P<0.05). The results showed that irrigation with magnetized water (0.3 and 0.6 teslas) was increased flower number to 11.34% and 28.5 percent and was decreased 14.99% and 13.58 percent of leaf number, respectively. The results showed that irrigation with magnetized water (0.3 teslas) compared with 0.6 teslas in different soil texture was increased flower dry weights, another hand the highest of flower dry weights in the irrigation with 0.3 tesla (0.61, 0.64, and 0.75 g in silty clay, clay loam, and sandy loam, respectively). Thus, in order to achieve suitable yields of marigold can be considered as appropriate levels of magnetized water and growth bed as these agronomic approaches. Using magnetized water can be improved the management of water in agricultural and experience deficit irrigation methods. Generally, using magnetized water in irrigation, in addition to saving water consumption and increasing irrigation water use efficiency, a reliable yield can be produced in Mashhad climatic condition and recommended for using under same conditions.

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.

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 m 3 and the total groundwater extraction for agriculture was estimated to be about 126.7 million m 3 . 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, respectivelt. 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 m 3 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 scenarioincluding 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. Keywords: Crop pattern, Conjunctive use, Gravitational Search Algorithm, Optimizati

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: ( ) Where, In: net irrigation requirement (mm), θ Fc water content at field capacity, θi: 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.

The objective of this research is to investigate the accuracy of Qual2kw software in simulating the quality parameters of Sefidroud River at the bottom of the dam. For this purpose, sampling and conducting laboratory studies for 12 stations in the range of 110 km in two summer seasons (August) and autumn (November) in 1398 has been done. In this study, Qual2kw software to simulate the eight main parameters of water quality including water temperature, pH, electrical conductivity, total suspended solids, soluble oxygen, biochemical oxygen demand, total nitrogen and total phosphorus, for August and November 1398, respectively, measured and verified Is. The results showed that the highest and lowest accuracy of the model with average NRMSE values in two stages is equal to 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 0.97 and 0.96, respectively, in the model calibration stage. The results of the present study indicate the appropriate capability of Qual2kw model to model water quality parameters of Sefidroud River. The results of the present article indicate the appropriate accuracy of the Qual2kw model in order to simulate water quality parameters in the Sefidrood River, which is in accordance with the results of Aryan, Nejad et al. (2015). It should be noted that the hydraulic properties of the flow affect the amount of dissolved oxygen in the Sefidrood River more than changes in the quality of other parameters.

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 Iran\s 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.

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.

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.