Study of water balance is absolutely important for investigation of the hydrology cycle, and preparation of water balance components in the watersheds requires many spatial data and their analyzing; so new technologies, models and tools such as GIS are needed. In this study, the SWAT model, which is a conceptual and semi-distributed model in the water and sediment balance simulation, was used in Aharchay watershed, Ahar, East Azarbayjan Province. Efficiency of the model in hydrologic simulation for this area is evaluated. Meteorology and hydrometers data of 1979-2010 was selected for this simulation; the average amount of rainfall and evapotranspiration were obtained 559. 8 and 299. 1 mm respectively. The period of 1982-2002 were used for calibration and 2003-2010 for validation. Calibration and validation processes were performed using SWAT-CUP software and PSO algorithm. Nash-Sutcliffe efficiency coefficients for water simulation were 0. 39 for calibration and-6. 7 for validation. Results showed that water balance simulation was not performed perfectly. Deficiency of required information and use of different data periods in calibration and validation were some of the effective factors which reduced the efficiency coefficients of the model.

Many of the environmental problems are caused by the changes in the main components of the hydrological cycle. However, water balance modeling can help to better understanding the components of the hydrological cycle in order to develop appropriate management options. The purpose of this study is to calculate three important components of surface water balance using the WetSpass model and evaluate the model in Hamadan-Bahar Watershed located in Hamadan Province on a monthly time scale. The results of the model evaluation in the study showed that the coefficient of determination between the observed and simulated runoff in the calibration and validation period is equal to 0.79 and 0.83, respectively. Groundwater nutrition assessment was also performed according to manual calculations of the variable for 2012-2013. Then, the results of Kramer correlation coefficient between spatial distribution maps of runoff, actual evapotranspiration and groundwater recharge were investigated with input maps of the model. In general, due to the importance of evapotranspiration in water balance calculations, the evaporation and transpiration maps of the model were evaluated separately for different uses. The evaluation results confirmed the capability of the WetSpass model in simulating runoff, evapotranspiration and groundwater feeding with an acceptable accuracy. The results of spatial distribution maps of runoff, actual evapotranspiration and groundwater recharge indicate a high correlation between evapotranspiration component with land use (0.54), soil texture (0.45), evapotranspiration potential (0.42) and temperature (0.31). Also, these results indicate a high correlation between runoff components with land use (0.62) and soil texture (0.58), and average correlations between groundwater recharge component with land use (0.32) and soil texture (0.34). Therefore, land use and soil texture were the first and second factors affecting the distribution of surface balance components, respectively.

The greatest limitations to agricultural development and production in Iran are scarcity of water resources, ineffective irrigation scheduling and wasteful water usage. Avenues discussed for optimum water use include improving water productivity by improving irrigation scheduling, farm water management and water profitability. The present study evaluated current water use and ways to improve winter wheat productivity by varying field scale water usage in the Abshar irrigation network in Esfahan province, Iran.Optimal irrigation depth and scheduling, and yield function for winter wheat using current water management tactics were determined. The availability of water, rotational water rights laws and field data were combined using the AquaCrop simulation model for field scale crop growth. Crop yield and winter wheat productivity were then simulated and compared to field results. Field research indicated that 800 mm of water is applied annually for winter wheat and crop yield averages 5000 kg per hectare. Improvements in water management and productivity based on different irrigation schedules (changes in depth and time) and water quantity schemes and the effect on water balance and crop yield were investigated. The baseline scheme used current conditions as a reference for other schemes. The results showed that eliminating the second, third and seventh irrigations from the schedule decreased the quantity of water applied by 38%r and yield by 4%, which produced a 45% increase in water productivity over the baseline scheme. However, improving agronomic management and decreasing the first irrigation depth by 50% (from 200 to 100 mm) also produced a slight variation in crop yield. Increasing the water applied to the optimal depth increased water productivity, but increasing the water applied to greater than optimal levels had no significant effect on yield and decreased water productivity. The results showed that proper irrigation scheduling using the AquaCrop model in combination with improved agronomic management decreased the quantity of water applied during irrigation 38%, increased crop yield by 16% and water productivity by 79%.

In this study, water balance of Ghare-sou watershed, was simulated using the SWAT model. The main objective of the study was to test the performance of SWAT and the feasibility of using this model as a water balance simulator for Ghare-sou watershed. The required input data were collected and the model was run. A parameters sensitivity analysis was performed using OAT method to determine the most important parameters. Model calibration was first performed manually and then automatically using SUFI2 algorithm. In order to reduce uncertainty, a number of hydrological components as well as a number of subcatchments were used simultaneously in the calibration and validation. The results showed that, the SWAT model performance for simulation of Ghare-sou watershed hydrology is satisfactory. During calibration, the simulated monthly flows in Syah-ab station (outlet of the watershed) matched the observed values with a Nash-Sutcliffe coefficient of 0. 6 and a coefficient of determination (R2) 0.65. These values were 0.36 and 0.62 during the validation. The values obtained for uncertainty assessment indicators were also satisfactory. P-factor and R-factor for the calibration period were 0.77 and 1.23 respectively and for the validation period were 0.97 and 1.73 respectively. Based on the model simulation, about 67% of the precipitation returns to the atmosphere through evapotranspiration process, about 17% runs off over land and moves toward the stream networks, about 16% percolates to the aquifer. This study provides useful information about water balance of the Ghare-sou watershed and helps better water resources planning for this watershed.

IntroductionAccurate knowledge of water balance components is necessary to optimize water consumption in agriculture. On the other hand, measuring water balance components is expensive and difficult. Therefore, the use of models that can simulate water balance values is important for water management in agriculture and water used by plants. Crop simulation models have been turned into essential tools for studying plant production systems. In the SSM-iCrop2 models, it is presumed that diseases and weeds are optimally managed and will not affect growth and yield. Additionally, except in cases where the model accounts for specific nutrients such as nitrogen, it is generally assumed that nutrient deficiencies are eliminated through fertilization. Therefore, parameterized and evaluated models are designed to fit these conditions. These factors are present in the field and affect crop growth and yield as well as water use. However, in several cases it is required to estimate yield and water balance components and irrigation water volume under grower conditions. Naturally, models parameterized using experiments are unable to simulate these conditions. Therefore, a model must be prepared so that it can simulate the real conditions of farmers. In this study, the SSM-iCrop2 model has been calibrated for the real conditions of farmers, and the purpose of this study is to use the SSM-iCrop2 model in simulating water performance and water balance for farmers. Materials and MethodsIn this study, the SSM-iCrop2 model was calibrated for farmers conditions using variables such as yield and harvest index, which are available for farmers’fields or are cheap to measure. The effect of factors such as pests and diseases, weeds and unsuitable nutrients, density and sowing date entered the model along with the calibration of three parameters of radiation use efficiency, maximum leaf area and maximum harvest index for farmers’ fields. Calibration was done by comparing the performance of farmers against the performance simulated by the model and by changing the parameters of radiation use efficiency (IRUE), maximum leaf area (LAIMX) and maximum harvest index (HIMAX). This calibration was done at Hashem Abad station in Gorgan for irrigated rice (paddy) and wheat. The simulated actual yield was calibrated with the actual yield. Due to the acceptable simulation of actual yields after calibration, it was presumed that other estimates made by the model are also reliable. Results and DiscussionMeasurement of water balance and other estimates of the model from growth and yield formation in the grower fields is expensive, but a calibrated model can estimate them at a low cost. In this study, it was shown that with the model calibrated for farmers' conditions, not other easily measured information (such as the irrigation water volume) can be obtained, with the assumption that the model accurately captures this information as well as performance. To evaluate the simulated real performance model, it was compared with the actual performance of farmers (Agricultural Jihad Report) after calibration. In addition to phenology, the SSM model simulates traits related to growth and yield, evapotranspiration values, irrigation water volume, runoff, available soil water during planting and harvesting, cumulative drainage, etc. The output of the model shows the amount of irrigation water is needed for a certain amount of performance in a given place (with specified rainfall and transpiration). The irrigation water volume calculated by the model was compared with the results of field tests from previous studies conducted by researchers at agricultural research centers. It was found that the model's output and the observed values were in good agreement. The root mean square error for rice and wheat was 216.6 and 157.6 kg per hectare, respectively, and the coefficient of variation and correlation coefficient were 4 and 85% for rice and 3 and 94% for wheat, respectively. Then, the irrigation water volume estimated by the model was evaluated and validated with the measured irrigation water volume in different crops (in Golestan province for different years). Based on the results of the evaluation, the coefficient of variation and the correlation coefficient for the simulated irrigation water volume were 8.9 and 98%, respectively, compared with the observed value. This calibration was done for rice (paddy) and irrigated wheat in the fields of Gorgan town, and the simulation and running were done using the meteorological statistics recorded in Hashem Abad weather station, Gorgan. Noting the fact that the actual yield has been simulated with good accuracy after the calibration, it was assumed that the other estimates of the model are also reliable. Thus, the calibrated model estimates them with low cost and appropriate accuracy and can complement field experiments. ConclusionThis study discovered that the SSM_iCrop2 model, when calibrated for the conditions of farmers' fields, can accurately simulate both growth and yield traits as well as water balance characteristics. Notably, the model provides reliable estimates of irrigation water volume in farming scenarios, a crucial factor for agricultural planning and drought adaptation.

Surface runoff is one of the most significant components of the water cycle, which increases soil erosion and sediment transportation in rivers and decreases the water quality of rivers. Therefore, accurate prediction of hydrological response of watersheds is one of the important steps in regional planning and management plans. In this regard, the rainfall-runoff modeling helps hydrological researchers, especially in water engineering sciences. The present study was conducted to analyze the rainfall-runoff simulation in the Gorganrood watershed located in northeastern Iran using AWBM, Sacramento, SimHyd, SMAR, and Tank models. Daily rainfall, daily evapotranspiration, and daily runoff of seven hydrometric stations in the period of 1970-2010 and 2011-2015 were used for calibration and validation, respectively. The automated calibration process was performed using genetic evolutionary search algorithms and SCE-UA methods, using Nash Sutcliffe Efficiency (NSE) and root mean of square error (RMSE) evaluation criteria. The results indicated that the SimHyd model with NSE of 0.66, TANK model using Genetic Algorithm and SCE-UA methods with NSE of 0.67 and 0.66, and Sacramento model using genetic algorithm and SCE-UA methods with NSE of 0.52 and 0.55 have the best performance in the validation period.

Precise knowledge of all components of water balance is essential to optimize water use in irrigated agriculture. However, water balance components are difficult to measure in required time intervals because their measuring is time consuming and costly. Unsaturated zone simulator models are useful tools for predicting the effects of agricultural management on crop water use and can be used to optimize agricultural practices such as agricultural water use. This research has been done on Wheat irrigated farms in Neyshabur plain, that is one of important plains in Khorasan Razavi province. SWAP Agro-hydrological model, was used for simulation of water balance components and crop growth in three wheat fields: Farob Roman, Hajiabad and Soleimani. Input data for model was a combination meteorological and field data. RETC software package was employed to evaluate and calibrate the soil hydraulic parameters, used. Simulation period was selected from October 2008 until early June 2009, in accordance with the wheat growing season. Sensitivity analysis to soil hydraulic parameters showed that the model is more sensitive to a and n coefficients. Also, acoording to presented statistical parameters, the results showed that SWAP is able to simulate water flow in soil, truly. Mean R2 coefficient value was 0.62, Mean Error was between -0.1 to -2.28 and Relative Error was fluctuated between - 0.33 and -12.69. Therefore, calibrated SWAP model can be used as an instrumental tool for calculating all components of water balance in field scale, with time and cost saving.

Considering the importance of knowing and awareness of the watersheds water balance status, and analyzing the hydrological behavior of watersheds for planning and implementing water-related projects, the need to use new technologies in predicting water balance components is more evident than ever. Based on this, in the Kashkan basin by utilizing the TOPKAPI-X hydrological model, the water balance components of the basin were simulated according to the cellular network design. Digital maps of the basin, land use, outlet point, soil texture, elevation, and continuous time series of temperature, precipitation, and discharge in the daily time step are the main inputs of the model. The model in each cell network balances the water balance of the entire period. Model calibration was done for the 15 years of the statistical period (1999 to 2014) and model validation for the 6-year period (2014 to 2020). The results showed that 27.02 and 28.43 percent of the total precipitation of the Kashkan basin was discharged from the basin as total runoff (respectively for calibration and validation periods), which is consistent with the observation data at the outlet hydrometry station. Next, to evaluate the efficiency of the model, the simulated values in both statistical periods were compared to the observational discharge. Statistical methods such as the Nash-Sutcliffe evaluation criteria showed that the TOPKAPI-X model predicted the water balance components such as actual and potential evapotranspiration, infiltration, and the amount of runoff, especially the total runoff, in this basin with relatively good accuracy (coefficient above 60%).