مجله تحقیقات آب و خاک ایران
سال پنجاه و دوم شماره 7 (پیاپی 67، مهر 1400)

The occurrence of continuous water shortage as a natural hazard has dramatically impacted the country's performance of surface water delivery systems. In this research, drought risk analysis in surface water delivery systems in Roodasht irrigation network has been investigated. For this purpose, the streamflow Drought Index (SDI) has been used to assess the region's probability of drought. The consequence of drought was calculated by combining water distribution performance evaluation indicators, efficiency, adequacy, and justice with a simple additive weighting method (SAW) in five weight scenarios based on different management perspectives. Finally, by combining the probability and consequence of drought, the risk of this phenomenon in the agricultural water distribution system was calculated and analyzed. According to the SDI index, the results showed drought occurred in the monthly period with magnitude of -2.42 to 2.47, and in the annual period with magnitude of -2.54 to 1.65. The range of monthly drought risk values of the system in five weighted scenarios is as follows: evaluation perspective with emphasis on the opinion of the network administrator (0.668 to 0.804), With the emphasis on the beneficiary's opinion (0.636 to 0.803), the simultaneous emphasis of manager and beneficiary (0.647 to 0.802), emphasis on regional water opinion and provincial managers (0.684 to 0.804), and with emphasis on environmental considerations within the irrigation network (0.692 to 0.804). The obtained results of employing the risk analysis framework in both annual and monthly periods make the authorities present appropriate alternatives considering the magnitude and timing of the system's failure risk.

In this research, the simulation and optimization models are integrated to apply the reservoir hedging policy. The simulation of the studied basin is executed using the WEAP model to conduct the system optimization and the multi-objective MOPSO model is utilized so that the first purpose is to maximize the percentage of supplying demands, while the second one is to minimize the violation of allowable capacities of the reservoir during the operation period. In this regard, the operation modeling from the reservoir was carried out based on the current condition for a 360-month period. Finally, by defining the optimized scenario and applying the reservoir hedging policy, the optimization of the operation from the reservoir is conducted and the results were compared with the outcomes of the reference scenario. In this study, by considering 24 decision variables including 12 hedging level variables and 12 hedging coefficient variables, the optimal answers were achieved after 1000 iterations. The results showed that the violation of the allowable capacities has not occurred in any periods, while in the reference scenario the reservoir level has reached the dead level in sequent months with more water shortage which might lead to the lack of water supply in such months and serious damages to the system. Due to the application of hedging policy in the optimized scenario, the percentage of supply in the critical months has increased between 20-35% compared to the reference scenario, which indicates a significant reduction in the failure rate in such months compared to the reference scenario.

The main purpose of this study is to develop a multi-criteria decision model based on stakeholders in the study area of ​​Varamin plain with the approach of aquifer subsidence control. One of the important tools for developing a decision model for land subsidence control is to use numerical models and evaluate different scenarios in these models. Due to the relationship and sensitivity of groundwater abstraction with subsidence, use of MODFLOW model to quantitatively simulate the aquifer and then use of SUB software package to simulate the amount of subsidence can determine this relationship well. Quantitative analysis and simulation of the subsidence model showed that the condition of the aquifer is critical and the rate of aquifer drop in a period of 5 years is more than 6 meters and subsequently the subsidence in the central parts of the aquifer will reach 37 cm. Accordingly, the effectiveness of these strategies was studied by considering 8 scenario strategies that are a combination of reducing the withdrawal of groundwater resources and artificial feeding of the aquifer. The results of weighting the criteria showed that the environmental criterion, which is related to the land subsidence adjustment index, has the highest weight with value of 0.27 and was introduced as the most important criterion in decision making. After evaluating the results and priorities of the solutions by COPRAS method, it was found that the A8 scenario is introduced as the first priority of aquifer treatment. The results also showed that by applying this scenario, the amount of subsidence will be reduced and the maximum amount of subsidence will be 23.5 cm in the central part of the aquifer. Finally, the quantitative status of the aquifer also improved by 76% compared to the forecast period (2024).

In this study, HYDRUS-2D/3D software was used to estimate the field capacity (FC) and permanent wilting point (PWP) using double-rings infiltration data via inverse solution. For this purpose, the double rings infiltration data obtained from 95 points of different regions in Isfahan were used as model input. The studied soils were classified into seven textural classes including Sandy Loam (SL), Clay (C), Loam (L), Silty Loam (SiL), Clay Loam (CL), Silty Clay Loam (SiCL), and Silty Clay (SiC). For most soil samples, the simulated values ​​of FC and PWP were less than the measured values. The results showed that the lowest error value in estimating FC was related to SL texture (R2 = 0.884 and RMSE = 0.021) and the highest error value for FC estimation was related to Clay texture (R2 = 0.1 and RMSE = 0.122). Furthermore, the lowest and the highest error values for PWP estimation were observed in Loam (R2 = 0.858 and RMSE = 0.003) and Clay (R2 = 0.21 and RMSE = 0.025) soils, respectively. In general, the simulation error increased with increasing clay content in the soil. The estimated PWP values ​​were relatively more consistent than the estimated FC values with their measured values, in all soil samples. Coefficients of determination (R2) were 0.77 and 0.80 for FC and PWP in all soils, respectively. In general, the inverse numerical solution method had acceptable accuracy for estimating FC and PWP, especially in light textured soils.

Watersheds are the sources of drinking water for cities and villages, and their pollution with heavy elements threatens the health of the inhabitants who use their water and agricultural products. Considering the importance of Baghan watershed in Bushehr province, the purpose of this study was to evaluate the contamination of soil particle size fractions (<63 and <2000 µm) by some heavy metals (Cd, Mn, Ni, Pb, Zn, Cu, and Fe) in three major land uses (range lands, croplands and orchards). Location of 120 surficial composite soil samples (0-20 cm) were determined using the Latin Hypercube technique on the topographical map. After pretreatment of soil samples, heavy metals were extracted by the Sposito method and measured using an atomic absorption spectrometry and geochemical pollution indicators including contamination factor (CF), geo-accumulation index (Igeo) and the pollution load index (PLI) were calculated. A significant increase in the concentration of Cu, Cd, and Fe has been observed by decreasing the particle size in different land uses. The contamination factor (CF) for particle sizes <2000 and <63 were ordered as Cd>Mn>Pb>Ni>Cu>Zn>Fe and Cd>Mn>Cu>Ni>Pb>Zn>Fe, respectively. The CF index indicates that the orchard soils for Cd were considerably polluted and for other metals moderatly polluted. Positive and significant amount of geo-accumulation index (Igeo) for Cd and Mn was observed for both soil particle classes in all land uses. Overall, the results of this study confirmed concentration of some heavy metals in smaller particles size. Comparing contaminants concentration of Cd and Mn in croplands and orchards soils with the range lands soils indicated anthropogenic effects on soil pollution. The results revealed risk of heavy metals in the watershed and necessity of reconsidering management policies.

Integrated operation of surface water and groundwater resources is one of the most important challenges facing water resources researchers. Integrated use is, in fact, the exploitation of surface and groundwater resources in order to increase the amount of available water and the sustainable use of available water resources. Therefore, one of the main goals of the present study is to simulate the interaction of surface water and groundwater by creating a dynamic couple between the WEAP surface water model and the MODFLOW groundwater model in the Miandarband plain. In this regard, the Soil Moisture Hydrological method was used to simulate the unsaturated zone of the soil. The results of simulation of surface and groundwater interaction were presented and the conditions for the use of water resources in the area was investigated for the continuous current policy. One of the most important achievements of this research is the simulation of saturated and unsaturated zones of the soil using complete hydroclimatology balance components as a coupled model of surface and groundwater. In the period of 6 years, the highest amount of aquifer recharge in the Miandarband plain, is about 10 to 19 million cubic meters in November to March. In some of these months, in addition to rainfall, the aquifer recharge is due to the infiltration of irrigation water. The highest rate of groundwater drowdown (7.5 meters) is related to the northern part of the plain and the average drowdown in the whole plain at the end of the 6-year operation period (October 2007 to September 2013) will be about 4 meters.

Estimation and computation of scouring around structures such as piers has a significant importance. In this study, scour depth in the vicinity of twin and three piers was simulated using Group Method of Data Handling (GMDH). First, effective parameters on scour depth were identified and then four different GMDH models were defined. To verify the simulation results, some experimental measurements were applied and 70% of these data were utilized to train the GMDH models, whereas 30% of the data were employed to test the models. Subsequently, the best GMDH model and the most influencing input parameters were introduced by conducting a sensitivity analysis. The sensitivity analysis showed that the GMDH models estimated the scour depth with acceptable accuracy. For instance, the correlation coefficient (R), scatter index (SI), and variance accounted for (VAF) for the best GMDH model were respectively calculated to be 0.949, 0.212, and 90.129. In addition, the Froude number was detected as the most important input variable to estimate the scour depth through GMDH model. Moreover, the mean discrepancy ratio (DRave) for the superior GMDH model was computed to be 1.228. For different GMDH models, four equations were presented and lastly a computer code was provided to simulate scour depth by means of the GMDH model.

Soil water repellency is a dynamic property that delays the infiltration of water into the soil and increases the potential for runoff and erosion. Accurate knowledge about the existence and severity of soil water repellency (SWR) in the coastal areas of Guilan, which are under different land uses, is very important. The present study evaluates the effects of land uses on soil water repellency in three areas: 1) Forested area with Pinus Teda, 2) forested area planted with Pinus Teda in some parts and covered with natural wild pomegranate in other parts 3) Agricultural land covered with Diaspyros Kaki. Soil water repellency was measured using three tests of the water drop penetration time (WDPT), the molarity of ethanol droplet (MED) and the soil wetted area (SWA). Significant differences in soil water repellency were found among the different land uses. Forest soils under pinus Teada showed the highest SWR and the soils under wild pomegranate and persimmon cultivated area showed the lowest SWR. Also, the relationship between SWR and soil properties (soil organic matter, pH, total nitrogen, phosphorus, Cation Exchangable Capacity, Electrical Conductivity, sodium, potassium, calcium, magnesium, soil texture, bulk and particle density) was investigated in 200 samples. Principal component analysis (PCA) showed that organic matter, total nitrogen with a positive effect and soil acidity with a negative effect are the most important parameters controlling repellency in these soils. To investigate which component of the soil particles have a more important role in creating water repellency, the intensity of water repellency was examined in six particle sizes of the soil (1-2, 0.5-1, 0.25-0.5, 0.125-0.25, 0.05-0.125 and less than 0.05 mm). The results showed that although coarse-textured soils are more prone to repellency, the smallest particle size in these soils plays a very important role in the intensity of soil water repellency.

Dust storms are known as one of the most important environmental hazards that affects various parts of the world. Following the intensification of dust storms in Khuzestan province, the internal sources of dust storms in Khuzestan province have been introduced in form of seven areas that southeast of Ahwaz was identified as the No.4 internal dust sources with the first priority of control and rehabilitation practices and the necessary executive measures for land reclamation in this region, including: management practices, biological operation and water distribution were on the agenda. The aim of this study was to investigate the land surface temperature (LST) changes and its relationship with land use changes as effective factors in creating a dust sources in south east Ahwaz. For this purpose, the Landsat 8 satellite data during the (2016-2020) were used and the land use maps of the study area were extracted using support vector machine (SVM) method and Split-Window method was used to extract the land surface temperature (LST) of the study area. The results showed that the area of barren land has been increased from 98.97% in 2016 to 99.81% in 2017 and has been reduced to 76.68% in 2020. The lowest areas of moderate vegetation, good vegetation and water bodies were corresponded to year 2017 which were equal to 0.05%, 0.01% and 0.03%, respectively. The highest areas of moderate vegetation and good vegetation were corresponded to year 2020 which were equal to 13.29% and 3.26%, respectively. The highest area of water body was corresponded to year 2019 which was equal to 7.73%. The results of mean LST estimation during 2016-2017 period showed 3.85℃ increase (from 32.62℃ to 36.47℃) and during 2017-2020 period showed 10.31℃ decrease, which reached to 26.16 ℃ in 2020. This trend has been affected by the land use changes, improved rainfall and the positive effects of modified measures taken to restore the vegetation of the study area.

For evaluation of the effect of different levels of zeolite and nitrogen on yield and some quality traits of potato under field condition, an experiment was carried out as a split plot based on a randomized complete blocks design in three replications in research fields of University of Kurdistan in 2018. The experimental treatments were clinoptilolite zeolite application at four levels (0, 5, 10 and 15 ton ha-1) as the main plot and nitrogen application at five levels (0, 50, 100 150 and 200 kg N ha-1) as the sub plot. The results indicated that with the application of different levels of zeolite, tuber yield, biological yield, average tuber weight, tuber dry matter, significantly increased, while, tuber NO3- concentration significantly decreased. Also, the results indicated that the nitrogen application led to significant increase in the tuber yield, biological yield, average tuber weight, tuber dry matter and NO3- concentration. The greatest tuber yield was recorded at 200 kg ha-1 N application treatment.  The highest tuber yield and harvest index were recorded at 10 ton ha-1 zeolite application treatment. The tuber yield in this treatment was 13.9% higher than the control treatments (no zeolite application). In general, the results of this study demonstrated that the zeolite application at 10 ton ha-1 can be a suitable practice for improving potato yield and quality.

Determining the amount of sediment carried by rivers is important in several ways. This parameter is effective in design of dimensions and geometric characteristics of flow regulation and diversion structures, reservoir dams as well as pumping stations. In this study, the calculation of flow discharge and bed load of Zaremrood river located in Mazandaran province has been investigated using Shiono and Knight quasi-two-dimensional model. This model is based on the Navier-Stokes continuity and momentum equations and has been simplified by depth averaged concept. For this purpose, using the finite element method, this model was solved numerically and the lateral velocity distribution was calibrated at the Garmrood hydrometric station. Comparison of obtained results by Shiono and Knight model in different flow discharges against measured data indicates the high accuracy of the model for lateral velocity distribution. Then, by using the computed lateral velocity distribution, the distribution of bed load across the river was simulated. The results showed that among the 17 empirical bed load equations selected in this study, the Duboy formula (1879) has the best accuracy in both one and quasi-two-dimensional modeling cases. In 1D modeling case, this formula with standard deviation of the discrepancy ratio of 0.34 percent had better agreement with the measured bed load in comparison to the Frijlink (1952) and Meyer-Peter and Mueller (1948) equations with the standard deviation of 3.46 and 7.32 percent, respectively. In 2D modeling bed load transport, the root mean square error (RMSE) was obtained 7.45, 98.8 and 172.9 for three equations of Duboy, Frijlink and Meyer-Peter and Mueller, respectively which indicates that only Duboy formula has an acceptable accuracy while Frijlink and Meyer-Peter and Mueller equations have large errors. The results also showed that the bed load transport in quasi-two-dimensional model using Duboy equation is more accurate than one-dimensional case.

The proper irrigation scheduling reduces deep percolation losses, saves water and increases crop yield and water productivity. For this purpose, the crop water requirement must be determined carefully. In the present study, the water requirement of silage maize (ZP 606 cultivar) was determined using soil moisture monitoring method in the field conditions. An experiment in the form of split-strip plots based on a randomized complete block design with three replications was conducted in 2019 in Varamin region. The main factor included three levels of irrigation, supplying 120, 100 and 80% of maize water requirement (I2, I1 and I3, respectively) and the sub-main factor included two types of irrigation management: pulsed (P) and continuous (C). The actual evapotranspiration of silage maize under pulsed and continuous management in full irrigation treatment was 364-341 mm, in deficit irrigation treatment was 348-336 mm and in over-irrigation treatment, was 383-352 mm, respectively. The estimated evapotranspiration of silage maize using FAO-56 method was 400 mm that was 13.5% higher than the average actual evapotranspiration for full irrigation treatment in pulsed and continuous management determined by water balance method, which indicated the importance of using local crop coefficient to estimate crop water requirement accurately. The results also showed that the amount of deep percolation in over-irrigation treatment under pulsed irrigation management had decreased by 30% compared to the over-irrigation treatment with continuous management. Therefore, it is suggested to use pulsed irrigation management in order to save water consumption and to reduce deep percolation under drip irrigation system in the study area.

To counteract the widespread negative effects of zinc deficiency on rice yield and the health of the majority of people who depend on this crop for nutrition, it will be necessary and effective to find cultivars resistant to zinc deficiency. For this purpose, field experiments during the crop years of 1396 and 1397 in farm located in the village of Pas-visheh, Rasht city, Gilan province,  A two factors split plot experiment was conducted in a completely randomized design with three replications. Experimental factors include soil application of zinc sulfate fertilizer as the main plot in two levels (0 and 20 kg  ha-1 zinc sulfate) and cultivar as a sub-plot in 27 levels (including local and improved cultivars and promising lines). The results showed that the Zn application  and its interaction with  cultivar waere significant for all measured  traits except the length and width of the flag leaf. The lowest and highest values ​​of zinc uptake in plant organs in the treatment of non-application of zinc sulfate belonged to line RI18430-2 (Hashemi × Saleh) and Kadous cultivar, respectively. Comparison of the mean of treatments showed that the lowest and highest zinc uptake in plant organs in the treatment of zinc sulfate application belonged to two lines RI18432-2 (Mohammadi × Saleh) and RI18431-1 (Abji Boji × Saleh), respectively and three cultivars or lines that have the highest zinc uptake in plant organs in the application of 20 kg / ha of zinc sulfate are RI18432-2 (Mohammadi × Saleh) and RI18430-22 (Hashemi × Saleh) and Ahlemi-Tarom cultivar, respectively. The results of the GGbiPlot analysis  showed that in both levels of zinc (control and application of 20 kg per hectare of zinc sulfate) Gohar, Kadous and Caspian cultivars have been ranked 1 to 3 in terms of Zn efficiency. Saleh, Dilmani, Gilaneh and RI18430-1 (Hashemi × Saleh) cultivars were also ranked as high Zn efficient cultivars and line in both levels. Therefore, for future research works, these cultivars are suitable for cultivattion on Zn deficiency paddy soils or selection of  higher Zn uptake cultivar(s) for rice grain quality purpose.

The optimal design, operation and management of drip irrigation systems relies significantly on selection of a suitable combination of emitter discharge rate, emitter and lateral spacing, root depth and soil hydraulic properties that should be in consistent with root growth pattern in the soil for delivering required amount of water and nutrition to the plant. Modeling soil wetting pattern is more practical and easier than the conducting laboratory or field measurements. In this study, an empirical model was developed to predict the dimensions of the wetting pattern under pulsed drip irrigation using dimensional analysis method. The main inputs of the proposed model are emitter discharge rate, saturated hydraulic conductivity, total volume of applied water and pulse ratio.  Experimentations included determination of the maximum depth and width of the wetting pattern after water application under different combination of pulses in a clay soil. The treatments were consisted of three pulses (P2, P3, P4) and two Off-Time durations (T1, T2). The predicted values of wetted depth and width by the empirical model and the HYDRUS-2D model were compared with the observations. The coefficient of determination parameter for the measured and estimated wetting pattern dimensions that obtained from empirical model was 0.94 and 0.93 and for numerical model was 0.95 and 0.97, which indicates good accuracy of the models. The results of the T-test analysis indicated that the empirical and numerical model simulated values were not significantly different (with a probability of 99.5%) from the observed ones. Although, on the basis of RMSE, ME and EF parameters the HYDRUS-2D model performance was better than the proposed empirical model but due to the simplicity of use and requiring less number of input parameters, it is recommended to use the developed empirical model to predict the wetting pattern as required in the design of drip irrigation systems.

Soil salinity, as one of the most important indicators of soil quality, has crucial roles in land use planning and land management in arid and semi-arid regions. The aim of this study was to model soil salinity at five standard depth (0-5, 5-15, 15-30, 30-60, and 60-100 cm) of global digital soil mapping project in 60,000 hectares of Qazvin plain with spatial resolution of 15m. Field studies included a sampling of 278 soil profiles and then the EC was measured in the laboratory. The recursive feature elimination (RFE) method was employed to select environmental covariates including parameters extracted from Landsat 8 image (OLI/TIRS) data, topography, and climatic parameters. Four machine learning algorithms as random forest (RF), cubist (CB), decision tree regression (DTr), and k-nearest neighbors (k-NN) were applied for predicting and mapping soil salinity. According to RFE, 10 covariates were chosen for each standardized depth. The results of modeling showed that the CB model at the depth of 0-5 and 15-30 cm with R2 values of 0.92 and 0.85 and RMSE 4.77 and 7.90 dS/m and the RF model at depths of 5-15, 30-60, and 60-100 cm with R2 values of 0.93, 0.94, 0.96 and RMSE 6.65, 5.10 and 3.20 dS/m, respectively, had the highest accuracy compared to two other models i.e., DTr and k-NN. Furthermore, the covariates extracted from RS data had more impact on topsoil salinity prediction while the climate and topographic attributes influence subsurface soil salinity. Generally, The RF and CB models along with appropriate environmental covariates were able to present salinity variation of study standard depths.

Due to the recent water shortages and droughts, the importance of water productivity is becoming more apparent. The main objective of this study is to examine water productivity of wheat according to its water requirement and proper irrigation management. This research was performed in Orzouieh city of Kerman province located in an arid region. In this study by using meteorological data of the region, wheat evapotranspiration was calculated by CROPWAT. Then, potential evapotranspiration was also calculated by Hargreaves-Samani and Jensen-Haise methods to verify the values resulted by CROPWAT package. Irrigation Hydromodule was calculated too. The Volume of water consumed by wheat per hectare during growing season was also calculated using irrigation hydromodule. For performing this study, three wheat farms with proper irrigation management were selected. For calculating physical and economical productivity of wheat farms in the region, one of the farms was examined. The results of this study showed that the physical productivity (CPD) is equal to 1.6 kg/m3 and economical productivity (NBPD) is equal to 13000 Rls./m3. The calculated productivities demonstrate that supplying actual water requirement of wheat along with proper management of the fields, results high economical efficiency.

Agriculture has been recognized as the main motive for economic growth and development in different countries of the world. In the meantime, mapping croplands through the classification of remote sensing images is one of the effective solutions in decision making and providing food security to the community. In this research, croplands are classified into different classes of agricultural products (including wheat, barley, corn, alfalfa, potatoes, and Sugar beets) using multi-temporal optical (Sentinel-2) and synthetic aperture radar (Sentinel-1) satellite images. All the steps related to the preparation of satellite images, have been conducted in the Google Earth Engine online processing platform. A novel three-dimensional deep convolutional neural network is used as the classifier. The designed network, in addition to three-dimensional kernels with the ability to extract spatial and temporal information of each pixel simultaneously, uses some escape connections of the previous layers. These connections, contrary to the feed-forward convolutional networks, feed the output of the previous layers to the new layers. After dividing the ground truth data into two categories of training and evaluation and assessing the performance of the network with 50 different training and evaluation data, the network’s overall accuracy was calculated 91.6% on average. According to the final results, the designed escape connections increased the overall accuracy of classification by 2%. The proposed network was also compared with temporal and spatial-temporal Random Forests and Support Vector Machines which showed a better performance with a difference of at least 2.4%.

Manures are used to increase pH and fertility of acidic soils in Gilan province. Although they are useful, but contain coliform bacteria that can reach the groundwater resources and lead contamination. This study aimed to investigate an indicator bacterium; Escherichia coli transport in two acidic soils. Two soil samples with pH vlues of 5.88 and 3.99 were taken from Amlash and Lahijan area respectively. For leaching experiment, air dried soil was freely packed in Polyvinyl chloride sylinders (with diameter of 4.8 and height of 14.92 cm). A 0.1 pore volume (PV) of bacteria (1× 108 CFU mL-1) and bromide (0.008 mol L-1) as a pulse flow was applied on the top of the soil columns after water flow rate reached steady state condition and leaching experiment was followed with distilled water. Leachate sampling was carried out in regular time intervals till 4.5 PV and E. coli and bromide concentrations were measured in the leachate. Resident E. coli number were also determined in each cutted 3 cm section of soil after leaching experiment endup. C/C0 peak of E. coli in the leachate of Amlash and Lahijan soil columns was observed at 0.7 and 0.9 PV repectively, while the C/C0 peak of bromide was occurred at 0.8 and 1.8 PV respectively. Early occurance of E. coli bacteria rather than bromide in the leachate of both soils was attributed to preferential water flow path which was dominant in the Lahijan soil column due to more clay and organic carbon content. The most resident E. coli number was determined in the surface layer of both soils which was greater in Amlash soil and decreased by 0.9 and 1.44 (log unit) in Amlash and Lahijan soil columns respectively. Overall, not only the cumulative number of E. coli bacteria was higher in the leachate of Amlash soil column, but also it contained more resident E. coli bacteria rather than Lahijan soil column due to greater pH value.

In operation of dam reservoir, due to the possibility of severe water shortages in the future, supplying total demand of current step is not rational, and the use of hedging rules can provide insurance for water supply in the future. In the reservoir long-term operation to supply the irrigation water demand, uncertainty of reservoir inflow and uncertainty of irrigation water demand have a significant effect on release. Crop water stress sensitivity variation at different growth stages varies the crop production function slope, which is not seen in seasonal production functions. In this study, a stochastic planning model with time-dependent production functions and a deterministic planning model with seasonal production function, in operation of the Buchan dam reservoir by using hedging rules are compared. The results show the reservoir operation by hedging rules increases economic benefit by 46.8% compared to the existing operation model. The time-dependent production function can improve the results by 19% over seasonal production functions. Also, the results show using stochastic model with the inflow uncertainty, irrigation water demand uncertainty and both, inflow uncertainty and irrigation water demand uncertainty simultaneously, the economic benefit increase by 0.73, 4.95 and 12.99%, respectively.

While having economic advantages, nonlinear labyrinth weirs have more passing flow capacity than linear weirs. Having a high capability of extracting hidden complex relationships among dependent and independent variables besides saving financial and time, intelligent algorithms are economic and time-saving and have dedicated a remarkable role among researchers. In this research, the performance of support vector machine (SVM) and gene expression programming (GEP) algorithms is figured out to predict the discharge coefficient (Cd) of the arched labyrinth weir using 226 experimental data series. Involved geometric and hydraulic parameters are total head (Ht), weir height (P), cycle arc angle (θ), Froud number (Fr), cycle wall length (Lt), the width of a cycle (w), weir nose length (A), an increase of weir height of 15% and change of weir crest shape change to quarter circle (U). Results showed that the maximum values of the Cd belong to arc labyrinth weir of arc angle 40 degrees. Numerical simulation illustrated that combination of (c، u،  ، ، ،) and (c، u،  Fr، ، ،) parameters have optimum performance in the SVM and GEP algorithms of assessment indices as (R2=0.9791, RMSE=0.03, DC=0.9776) and (R2=0.9871, RMSE=0.0231, DC=0.9856), respectively; showing highly accurate performance of two algorithms in the prediction of the Cd.