واسنجی

In recent years, basins hydrological modeling has been one of the important issues, which its results have a significant impact on water resource planning. One of the tools in basins hydrological modeling is SWAT (Soil and Water Assessment Tools), this tool can be used as an extension in GIS software. The purpose of this research is to evaluate the accuracy of SWAT in Maroon basin hydrological modeling.

The calibration and validation of model, used from the flow data measured at the Idenak and Tange-Takab stations in the period of 1991 to 2017.

The results showed that the accuracy of the model in using daily data is lower than monthly data. The reason of the reduction of the accuracy in using of daily data compared to using of monthly data is that the daily calibrated data in each hydro-station is 3450 numbers and for the monthly data is 108 numbers. The simulation results show that the SWAT has an acceptable ability in the basins hydrological simulation with a mountainous nature and the process of flow changes in the calibration and validation stage is simulated with acceptable accuracy.

Modeling is one of the most effective methods in river water quality management, planning to reduce the entry of pollutants and control environmental damage. In this article, the water quality of Babolrood river using the Qual2kw model and meta-heuristic model of support vector machine and SVM-GA genetic algorithm with the approach of simulating six water quality parameters including temperature, alkalinity, electrical conductivity, total nitrogen, dissolved oxygen and biochemical oxygen demand in four time periods from 2018 was investigated. Genetic algorithm is used for simulation and optimization, and the hybrid of this model with support vector machine has improved the simulation performance. In order to compare the observed and simulated data, the explanation was used coefficient R2 of the average absolute error MAE and the root mean square of the normalized error NRMSE. The results showed that the best SVM-GA simulation for total nitrogen parameter in February is with MAE 0.15 and NRMSE 1.97. Also, the results of Qual2kw numerical model showed that the best simulation for May is with MAE 0.14 and NRMSE 1.2. The water quality of Babolrood River was evaluated using the NSFWQI index. Based on this, the best water quality is in the month of Bahman with an index of 56 in the medium to good range and the worst quality is in the month of May with an index of 49 in the bad range.

The aim of the research is quantitative modeling of the underground water flow of the plain aquifer and the investigation of management solutions to deal with the drop in the underground water level. This research was investigated using hydrogeological information, hydrology, meteorology and basic studies of underground water sources. Quantitative underground water modeling was done using GMS software and Modflow code and the underground water level was simulated for the years 2011-2015 with 60 monthly time steps. Manual calibration of the model was done for 2011-2014 and its validation was done for 2014-2015. Future management solutions, in the form of combined scenarios:One- 10% reduction in withdrawal from wells with a 5% reduction in feeding from return of agricultural water. Two- 20% reduction in withdrawal from wells with a 10% reduction in feeding from return of agricultural water. Three- Their comparison with the continuation of the existing trend was predicted for the years 2015-2019. The result of the aquifer modeling for the above time periods showed the deficit of the reservoir 33.09 MCM. But by applying a 10% reduction in withdrawal and a 5% reduction in feeding, 21.38 MCM/year and by applying a 20% reduction in recharging from the return flows of agricultural consumption and 10% reduction in feeding, 25.94 MCM/year were added to the volume of the water balance. But with the continuation of the current trend, the deficit volume of the aquifer was estimated to be more than 54 MCM.

Soil water content is measured by different methods, such as oven, gamma ray, and time reflectometry methods. Direct methods are time-consuming and lead to disturbance of the soil sample, and some indirect methods have risks of radioactive materials. Among these methods, the TDR method, which is one of the reflectometry methods, is a quick and safe method, and has received attention for this reason and gives acceptable results in soils with normal conditions. However, for saline soils, this method cannot measure water content accurately. The objective of this research was to make TDR sensors that can measure the water content of saline and fine-textured soils. By making these sensors, it would be possible to measure water content of saline soils by a TDR; and if an error is observed, the actual amount of soil water content can be obtained by providing suitable calibration models. For this purpose, a fine-textured soil was obtained from Tikmehdash Research Station and by adding different amounts of salt, soil  samples with electrical conductivity of 20, 35 and 50 dS/m with natural density were prepared. Through trial and error, the type of coating suitable for covering the moisture sensor rod, which is a polymer material, was determined. Then, the length of the coating used in the middle moisture sensor rod was determined for the mentioned soil that had the prescribed salinities and water content. This length was equal to the length of the moisture sensor rod. Then, the coated sensors were tested to measure other soil water contents, and suitable calibration models were presented. Thus, by entering into the models the volumetric moisture content measured by TDR, the moisture content of fine-textured saline soils can be estimated with good accuracy.

The agriculture sector, as the biggest consumer of water to produce more food, has faced the challenge of water shortage. One of the problems ahead in the agricultural industry is the sustainable use of available resources such as land, water, and labor to increase agricultural production and development, which requires proper planning and management policies. Plant models can be used to investigate the long-term effects of quantitative and qualitative changes in irrigation water on crops, soil salinity, evaporation and transpiration, deep infiltration, and surface runoff. One of the widely used plant models is the AquaCrop model, which was presented and developed by the World Food and Agriculture Organization. The Aquacrop model is one of the crop yield estimation models that can be used for a wide range of crops including fodder crops, vegetables, grains, fruits, oil crops, and tubers. In this model, the state of various stresses including water and soil salinity, simulation of lack of irrigation, and crop yield are considered. Various studies have been conducted regarding the calibration and validation of crop forecasting models in our country, and much research has been conducted on wheat at the global level. In this research, the AquaCrop model was used to predict the biomass and grain yield of wheat in Qazvin. This model can be a good substitute for field measurements and can be used in areas where there is a lack of ground information.

In the present research, the data of water wheat cultivation in a lysimeter in Ismailabad, Qazvin were used. The input information of the AquaCrop model includes information on climate, soil, management, and plant characteristics. To calibrate and verify the model, some farm information was needed to be compared with the output of the AquaCrop model. The biomass of the wheat plant was determined by taking random samples of the 0.5×0.5 m2 with two replications per sampling hectare. To measure grain yield in the fields, four samples were taken at the end of the growing season at the end stage. The validated AquaCrop model was used to estimate the effect of three planting dates and three low irrigation conditions on wheat grain yield. In this step, the average regional information around the farms was used so that the implementation of the model is not unique to the conditions of a particular farm.

In terms of the investigated meteorological factors, the model has moderate sensitivity to maximum and minimum temperature and low sensitivity to rainfall. The change in the maximum temperature in this region increases the error of the simulation on average. Regarding the soil parameters, the sensitivity of the model to the crop capacity moisture, wilting point, saturated moisture, and saturated hydraulic conductivity, especially in saturated conditions, is low to medium. The most sensitive of the AquaCrop model was the change in the reference harvest index. The model simulated biomass values with higher accuracy than yield. In the calibration stage, the values CRM, NRMSE, and d for biomass were -0.15, 0.17, and 92% respectively. These values were obtained in the validation stage for biomass -0.1, 0.24, and 92 % respectively, and for yield -0.03, 0.06, and 80 % respectively. By running the model in different climatic scenarios, it was determined that the maximum delay in the planting date is on November 15. A 25% reduction in irrigation water reduced grain yield in wet, normal, and dry years by 15%, 20%, and 28 %, respectively, and a 50 % reduction in irrigation water reduced its amount by 20, 25, and 45 %, respectively.

Evaluation of the AquaCrop model for common plants in a region plays an important role in comparing crop performance in different conditions. In this research, the ability of AquaCrop 6 model to estimate the yield and biomass of wheat in Ismailabad Qazvin was investigated. The results showed that the model is capable of simulating these factors with high accuracy. The accuracy of the model in biomass simulation was higher than the grain yield. By implementing the calibrated model in different climatic scenarios, planting dates, and irrigation deficits in two regions, it was determined that to achieve optimal performance, the wheat planting date should not exceed 15 November. It was the use of calibration coefficients by spending a long time in the AquaCrop model so that a calibrated model can be used in many areas with proper accuracy. More accuracy in the simulated results can be achieved by using more calibration factors, but it is clear that the use of more calibration factors requires spending more time and money. Finding a general recalibrated model that can be used in large areas is a good solution in crop management at the farm-to-regional scale. Comparing the statistical parameters obtained in this study with previous studies on wheat yield modeling by the AquaCrop model shows that the results of this study are within an acceptable range.

Today, fresh water sources are very important in human life. During the past years, population growth, development of industries, and agriculture have increased the need for water and subsequently increased the withdrawal from groundwater sources. This increase in withdrawal has occurred without considering the capacity of the aquifers. While logically, the exploitation of an aquifer should be limited to its dynamic storage, in most regions, the static reserves of aquifers have been used to a large extent, and it seems impossible to return these aquifers to their original state. The dynamic storage of the aquifer is actually a part of the storage volume of the aquifer, which has fluctuations, and by examining and determining these fluctuations, it is possible to estimate the permissible amount of exploitation of the aquifer. But the static storage of the aquifer, which is very important, is among the old and stable storage that has been stored for many years. The use of static aquifer storage causes events such as subsidence. The drying up and lack of water in many aqueducts, springs, and extraction wells across the country is one of the consequences of the overexploitation of groundwater resources. In the arid and semi-arid climates of Iran, factors such as climate change and water scarcity, along with overexploitation of water resources, especially groundwater resources, have caused the groundwater levels to decrease. In some areas, we are witnessing irreparable subsidence. As a result, it is necessary to manage and control the extraction of groundwater resources before the crisis occurs and reaches an irreversible level. In this regard, monitoring and controlling the condition of the aquifer using computer models is essential.

In the present study, the modeling and quantitative investigation of the groundwater condition of the South Mehyar-Dasht Asman aquifer in the Gavkhoni catchment area has been done by the MODFLOW 2005 model and groundwater modeling system )GMS 10.4.5( software. GMS software is one of the few with good performance and has been used in groundwater studies in many countries worldwide. This software simulate groundwater both quantitatively and qualitatively. The MODFLOW (Modular Ground Water Flow) model is used to simulates groundwater flow in aquifers with specific boundary conditions, assuming the necessary values for hydraulic conductivity and other aquifer parameters. The program allows the user to select only the modules needed to study the desired system for specific hydrogeological processes and activate or deactivate a particular part. These features have made the MODFLOW model the most efficient and accessible groundwater model today. For this purpose, the statistics and information from 15 years ending in 2013 of the Iran Water Resources Management Company and topographical information extracted from satellite data have been used to model the groundwater of the South Mehyar-Dasht Asman aquifer.

After running the model, the parameters of hydraulic conductivity, anisotropy, or HANI, RCH, SY, and parallel lines of the groundwater level were obtained. In the next stage, or the calibration stage, the model was calibrated by the parameters mentioned to minimize the difference between the observed water level and the calculated water level. In the sensitivity analysis stage, the calibrated value of the parameters is systematically changed to determine the model's sensitivity to the parameters. In this stage, it was found that the model received the most influence from the parameters of anisotropy and hydraulic conductivity. To validate the model and measure its accuracy, validation was done. The RMS error was 2.21, which is a good value, but for more certainty, the RMSE was also calculated, and its value was 23 %, which is very appropriate considering the long-term simulation period. Finally, the numbers extracted from the FlowBudget engine based on the calibrated MODFLOW model revealed that during the 12-month simulation period, a particular share of the aquifer's fixed storage was reduced on a daily average basis, resulting in an average drop of 7.5 m in the aquifer's groundwater level during this period. We see that the most significant drop is related to the eastern part of the aquifer.

In this research, the South Mehyar-Dasht Asman aquifer was simulated and modeled by the MODFLOW model and GMS software, and the groundwater level was investigated during the simulation period. The model was calibrated to reduce the difference between the observed and the calculated water level. The sensitivity analysis section also examined the influence of the model parameters. Validation was also done to increase the accuracy of the model's performance. The coefficient of determination or R-squared correlation was 0.9971, which seems to be a good number compared to other studies. The results showed that the water withdrawal is greater than the aquifer's recharge, and a specific volume of the aquifer storage is always reduced during the simulation period, which caused a drop of 7.5 m in the groundwater level. The groundwater level of the South Mehyar-Dasht Asman aquifer continuously decreases from the western part to the eastern region, and the lowest groundwater level is related to the east part of this aquifer. Declining groundwater levels, water shortage conditions, and overexploitation, increase the risk of subsidence, which is an irreversible event. To prevent this from happening, the amount of water taken from the aquifer should be proportional to its capacity, and control and management measures should be carried out on a large scale. Computer models and up-to-date methods help to maintain and manage these water resources as well as possible. Factors such as the dryness of the Zayandehroud River, excessive harvesting, and lack of water have led to the aggravation of the adverse environmental effects of the Gavkhoni International Wetland, and this has increased the importance of simulating the existing aquifers in this basin. Due to the fact that no study has been done on the simulation of the groundwater of South Mehyar aquifer-Dasht Asman and also the duration of the simulation period is 15 years, this research can be a basis for future studies and provide the possibility of comparison with other studies.

Land use changes are one of the main factors in the amount of surface runoff changes in watersheds. Therefore, it is necessary to investigate it to reduce the damages (human and financial) caused by floods and to modify watershed management. The watershed of Nahre Azam is located in the north of Shiraz city and a lot of loss of life and money to the residents of Shiraz due to floods has occurred in previous years. The present research was conducted to investigate the relationship between land use change and runoff in the Nahre Azam watershed in Shiraz using the SWAT model in the period of 2004-2020. The model was calibrated using data from 2004 to 2014 and validated for 2015 to 2020. These images were classified into 6 main land uses using the supervised classification method after performing necessary pre-processing, and a land use map was prepared for 2040 using the Markov chain method. Then, the effect of the land use change in 2003 and 2040 on the amount of simulated runoff was evaluated with the recalibrated model. The calibration results of Nahre Azam watershed for the values of statistical parameters in the calibration step for the coefficient of determination, P-Facor and R-Facor are 0.77, 0.72, and 2.43, respectively, and for the validation step we obtained 0.69, 0.65, and 2.3 respectively. The analysis of the land use map showed that the main land use change in the region related to the conversion of pastures to agricultural land and urban land, which caused a decrease in pastures. Also, the results of the model simulation using the land use maps of 2003 and 2040 indicated that the amount of runoff decreased. The results revealed that if all the uncertainties are minimized, the calibrated SWAT model can produce acceptable hydrological simulation results for the user, which is useful for water resource and environmental managers and politicians as well as city managers of Shiraz.

Due to inherent limitations of global climate models, their outputs are significantly biased in comparison to observed values which could provide unreliable climate projections. This study evaluates the performance of 10 global climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating precipitation in the Rafsanjan study area over calibration (1986-2005) and validation (2006-2014) period. For correcting simulated precipitation, various quantile mapping-based bias correction methods applied in these two periods. Evaluating the performance of various climate models and quantile mapping-based bias correction methods and approaches is carried out through multiple statistical metrics including NSE, PBIAS, MAE, and KGE as well as Taylor's diagram. Finally, simulated precipitation of selected model extracted for projection period under SSP1-2.6, SSP2-4.5 and SSP3-7.0 scenarios and corrected by suitable bias correction method. Results showed that the MPI-ESM1-2-LR model has better performance in simulating precipitation over calibration and validation periods compared to other climate models. The results of evaluating the performance of quantile mapping-based bias correction methods in both periods also showed that bernlnorm method performs better than others for the correction of simulated precipitation by climate models. In addition, the evaluation results of quantile mapping approaches including NTP, PT, and DDT in these periods demonstrated that NTP and PT have an acceptable performance compared to the DDT approach. Present study can help to improve the credibility of future climate projections using CMIP6 climate models.

This study aimed to calibrate the HYDRUS-2D model for simulating soil moisture distribution under tape irrigation in transplanting sugar beet, with and without mulching. The research was carried out during the cropping seasons 2017-2018 in 14 plots (7 plots with mulch and 7 plots without mulch) with 2 rows of 40x50 tape. To monitor soil moisture distribution, soil samples were collected from 12 plots, and access tubes of the PR2 device were installed at depths of 10, 20, 30, 40, 60, and 100 cm in two plots. The PR2 device was calibrated for a 7- day irrigation frequency and 6 irrigations. The calibration results showed that the default parameters a0=1.6 and a1=8.4 proposed by the PR2 manufacturing company were not appropriate for the loam-textured soil of the study area. For this research, a0 and a1 were modified to 1.8 and 8.3 for soil water contents higher than the filed capacity and to 1.2 and 8.6 for soil water contents lower than the field capacity, respectively. The PR2 device was then used to measure soil moisture contents for five irrigations (6 hours each irrigation), during and after irrigation until the next irrigation. The results showed that the HYDRUS-2D model performs appropriately in simulating soil water content in five irrigation intervals with and without mulch application. The mean absolute value of error (MAE) was less than 0.035, root mean square error (RMSE) was less than 0.042; correlation coefficient (R) was above 70%, and the sum of squared error (SSQ) was less than 0.41 percent. If the hydraulic parameters of the soil were recalibrated for the use of mulch, the HYDRUS-2D model provided the same efficiency. Therefore, the HYDRUS-2D model is recommended for designing and managing tape irrigation due to its good simulation during and after irrigation.

Exploitation, management and protection of water resources, especially groundwater resources, are very important. The management of water resources requires accurate knowledge of the characteristics of the aquifer, the tension to it and finally the groundwater balance. Simulation models help planning managers to determine the amount of aquifer utilization for long-term and sustainable use. For this purpose, changes in the water level of the Kashan plain aquifer in the statistical period of 1387-1397 were simulated by the GMS model for 125 stress periods. The model was calibrated in two permanent and non-permanent modes for a period of 94 months (1387-1395) and validated for a period of 31 months (1395-1397).The result was a drop of 4.4 meters of groundwater during the 10-year study period. To predict the behavior of the aquifer in the near future, the reservoir level was modeled until 1407. Due to the location of this plain in the climatic dry belt and the occurrence of climate change and the lack of effective rainfall to properly charge the aquifer, in this study the focus was on the management of extraction from the aquifer and according to these three scenarios, extraction with the current trend,15% increase and 15% reduction definition and simulation was done. The simulation results of these three scenarios showed a drop of 9.866, 11.895 and 6.993 meters at the end of 1407 respectively.

Today, human activities are one of the most important challenges in issues related to the quality of water resources, which is currently considered one of the management threats in the exploitation sector. This issue will require the identification and evaluation of water resources from different perspectives, of which the vulnerability of water resources is one. This study evaluates the vulnerability of water resources by combining two DRASTIC vulnerability indices in the aquifer sector and WRASTIC vulnerability index in the upland sector of Astana-Kuchsefahan region. In this study, after assessing the vulnerability with the relevant indicators, two methods of entropy and hierarchical analysis were used for scaling based on maximizing the correlation with nitrate concentration. The results showed that the most importance in both indices based on recalibrated weights include industrial use in the WRASTIC index and underground water depth in the DRASTIC index. The analysis of the calibration results showed that the correlation of nitrate with the DRASTIC vulnerability index using the AHP method was 0.61 and with the WRASTIC index was 0.58 using the Shannon entropy method. Also, the measurement results showed that the WRASTIC index ranges from 17 to 46 and the DRASTIC index ranges from 119 to 180. Based on the consolidated results in the western and eastern parts of the highlands, the level of vulnerability using the WRASTIC index is lower and there is a higher vulnerability in the western part of the aquifer compared to the eastern part.

Optimal use and management of water resources is very important. Also, choosing the appropriate irrigation method plays a vital role in saving water consumption in the agricultural sector. Therefore, in the current research, the effect of the irrigation method on the simulation of sugar beet yield was investigated using the AquaCrop model. In this study, the effect of two methods of drip irrigation (tape) and surface irrigation (furrow) and three levels of irrigation water (50%, 75%, and 100% of the plant's water requirement) on the yield of sugar beet plants was investigated in Sarayan-Ayask region, Iran. A factorial experiment was conducted based on a completely randomized design with 4 replications in 2021-22. The results showed that irrigation method had a significant effect on leaf diameter, leaf length, leaf weight, tuber diameter, and tuber length and weight of sugar beet tuber. Also, according to the results, drip irrigation had greater effect than furrow irrigation on the studied traits. Then, the grain and biomass yield was simulated using the AquaCrop model and the simulated values were calibrated and verified using observational data. Calibration was done using two replications of 100% and 50% stress levels, and validation was done using the replication of 75% stress level. The NRMSE, RMSE, RD and R2 coefficients of the model calibration values showed that the simulated and validated values were close to each other and these values were more precise in drip irrigation than in furrow irrigation. Validation values of two irrigation methods also showed the ability of model in simulating grain yield and biomass.

Due to the importance of determining the behavior of plants in water shortage conditions, it is necessary to determine the coefficients of plant sensitivity to water at different stages of plant growth. Water shortage in the Sistan plain is a serious and important issue, so that the lack of water supply to the Helmand border river, which is the only source of water supply in the region, leads to the destruction of agriculture. The low possibility of increasing new water resources and the need to increase agricultural production from limited water resources in this region requires the use of appropriate scientific and technical methods to increase the productivity of agricultural water consumption. Also, changing the pattern of cultivation and replacement of high-income crops in recent years in arid areas has received much attention from farmers. The purpose of this study is to investigate the effects of water stress on the behavior of garlic in dehydrated conditions to calibrate the production function of this plant to obtain yield response coefficients in conditions of water shortage.

In this study, garlic plant was implemented in the form of a randomized complete block design with three replications in 1398 and 1399 in Sistan and Baluchistan province. Treatments were applied based on stress levels compared to control 30, 35, 40, 45, 50, 60 and 70% of water requirement. This station is located 20 km southeast of Zabol city at latitude 61 degrees and 41 minutes and latitude 30 degrees and 54 minutes in Sistan region. The altitude of the station is 483 meters above sea level, the average annual rainfall is 55 mm and the annual evaporation rate is 4500 to 5000 mm. This region has a very dry climate with very hot summers and mild winters. The area of ​​the experimental plot was equal to 750 square meters was selected for planting garlic of Chinese cultivar before planting the bed was reinforced with animal manure and after growing based on soil fertilizer test, 300 kg of potassium phosphate, 200 kg of triple phosphate and 100 kg. One kilogram of urea was added to the soil. Then plow and disc and finally leveled. On the 24th of October, grooves were planted with a shovel at a distance of 20 cm and a depth of 5 cm to plant garlic of Chinese cultivar, and garlic tubers were planted at a distance of 8 cm on the rows. Then, based on the obtained information, the two functions of Tafteh and Raes production were investigated and yield response factors were determined during the growing period.

Comparing the two methods used the highest yield of garlic in the study was 8240 kg / ha, for the production of which 833 mm of water was used. The data of the first year were used to calibrate the yield response factors of garlic and after calibrating the two production functions of Raes and Tafteh, the values ​​of the yield response factors of garlic were presented. This coefficient was different in the range of 0.5 to 1.2 in different periods of garlic plant growth, the change curve was presented. Evaluation of Rice method in the second year with root mean square error of 1302 kg / ha and normalized value was about 23%.

In the method of Tafteh the mean root mean square error was 485 kg / ha and the normalized value was about 11%. Therefore, the method of Tafteh is recommended in determining the yield of garlic under water stress conditions.

The FAO Penman-Monteith (FAO-56 PM) model is proposed as a standard model to estimate reference evapotranspiration (ETO) in various climates. Different models are used to estimate the total solar radiation (Rs) as one of the essential inputs of this model. This study aimed to calibrate and validate four Rs estimation models (Ångström-Prescott, Hargreaves-Samani, Mubiru et al., and Chen and Li) in Ahvaz (with arid climate) and Hamedan (with semi-arid climate) stations during the 1992-2020 climate period and the effect of these models on the ETO estimation. The coefficients of these models were calibrated by the intelligent shuffled frog leaping algorithm (SFLA). To evaluate the efficiency of these models, the estimated Rs values were compared with measured values. Based on the root mean square error (RMSE), the coefficient of determination (R2) statistics and Nash-Sutcliffe, the A-P model with RMSE=1.929, R2=0.918, NS=0.896 and Mobiro et al. model with RMSE=2.925, R2=0.875, NS=0.860 showed better performance than the other models in Ahvaz and Hamedan stations, respectively. A decrease of about 20% was observed in the percentage of ETO difference between, the calculated and the estimated Rs compared to the measured Rs in 2 stations at all of the models.

The recent growth in population has led to an increase in food supply requirements which, in turn, has resulted in an increase in groundwater exploitation. In areas where fresh and saline aquifers are adjacent, the overexploitation of fresh groundwater leads to a decrease in fresh ground water level and, as a result hydraulic gradient of saline groundwater towards fresh groundwater increases. Also, a decrease in fresh groundwater level leads to a decrease in the plain discharge. This way, the saline water cannot exit the plain and pressure head rises leading to extra waterlogging and salinization. Interception drain is an effective solution to intercept saline flow and discharge it out of the plain. In effect, the drainage system reduces saline water table level and prevents waterlogging and salinization. Salt marshes of Qazvin plain, located in the south-east of Qazvin, is facing the same problem and saline soil areas in the region have accordingly increased 10000 ha in recent years (Saman Abrah and Kamab Pars engineers, 2010). An interception drain system was thus implemented in the study area in order to reduce the saline water table level and prevent waterlogging and salinization. Following the construction of the drain in the region, 99 observation wells were also drilled around the drain in 9 sections (A-I) such that each row has 11 observation wells so as to monitor the groundwater fluctuation and salinity. At each section, 7 wells were located on the upslope and the remaining 4 wells were on the downslope (Sotoodehnia et al, 2014). However, it takes a lot of money and time to measure water table level and salinity from observation wells continuously. Modelling is indeed a cost-effective way to predict the water table level and salinity in future. HYDRUS is a powerful tool that can be used to simulate and monitor the drain situation reliably, but it should be calibrated for the study area. Calibration of HYDRUS means estimating soil hydraulic and solute transport parameters that can be done with HYDRUS inverse solution ability. Using HYDRUS-2D, Abbasi and Tajik (2007) estimated both soil hydraulic and solute transport parameters in the field scale. They also compared the measured and simulated values of soil moisture and salinity. Though soil moisture was almost overestimated, and salinity was almost underestimated, the results showed that the errors were small and the model was accurately calibrated (Abbasi and Tajik, 2007). The main objective of this study was thus to assess HYDRUS-2D ability for simulating solute transport in a very saline aquifer in the study area, and also to consider saturated and unsaturated regions simultaneously. Moreover, this study employed HYDRUS-2D to simulate salinity transport in the areas where the amounts of salinity was extremely high. According to Latifi et al. (2020), evaporation is an effective factor in groundwater fluctuations.This study also examines the effect of evaporation and aquifer thickness in an inverse solution. Aquifer thickness and evaporation have an important effect on the inverse solution due to the statistical indexes involved. Thus, some statistical indexes were carried out to assess the accuracy of calibration, and the results showed that the model was calibrated accurately.

 Simulation of quantity and quality of surface runoff in mountainous watersheds is one of the most challenging topics in modeling due to its unique features, such as unusual topography and complex hydrological processes. One of the lesser-known aspects of modeling such catchments is the uncertainty analysis of water quality predictions, especially about the vital phosphorus parameter. Phosphorus is one of the important quality variables in water, and its increase in water resources can cause eutrophication phenomena in streams and reservoirs of dams. Due to the importance of the phosphorus parameter and the fact that water quality modeling has not been employed in the Karaj catchment area so far, in this research, total phosphorus has been modeled as a water quality parameter along with the flow and sediment discharge. This study aims to identify the most sensitive parameters of the model to flow, sediment, and total phosphorus discharge and calibrate, validate and analyze the parametric uncertainty of the SWAT model in predicting these three variables in a mountainous catchment. The case study was the catchment area of ​​the Karaj River upstream of Bileqan pond, which is one of the mountainous watersheds in Iran. There are two critical water structures along the Karaj River, namely Amirkabir dam and Bilqan pond. Amirkabir dam (Karaj) is a multi-purpose project that is constructed to supply drinking water to Tehran and regulate water for irrigation and agriculture in the suburbs of Karaj. The Bileqan pond is also the essential point of supply and transfer of drinking water in Tehran. Given the importance of this region in supplying water for different uses, providing a calibrated model for quantitative and qualitative variables of water can be the basis for decisions to apply future management scenarios in this basin.

 The case study was the Karaj River catchment area upstream of Bilqan Basin, which with an average height of 2880 meters, is one of the mountainous areas located in the Alborz Mountains. This basin with an area of 1076 square kilometers in the north, includes parts of Mazandaran province. In the east and south of the catchment area includes parts of Tehran province and most of it is located in Alborz province. The average annual temperature and rainfall in this basin are 12.1 °C and 480 mm, respectively, and the average of 117 glacial days during the year is observed in this area. The long-term daily data of synoptic stations adjacent to the study area from the beginning of 1998 to the end of 2018 (21 years in total) was introduced to the model. Also, daily data of relative humidity, rainfall, minimum and maximum temperature, solar radiation hours, and wind speed as meteorological parameters measured at stations in the study area were introduced to the model. It should be noted that there was a lot of missing data in meteorological information, especially for daily temperature data. In addition to the above information, daily flow data discharged from Amirkabir dam and technical specifications of the dam were introduced to the model. In addition, orchard management information, including irrigation periods and information related to phosphate fertilizers used in regional orchards, were presented to the model. The global sensitivity analysis method was used to determine the sensitive parameters of the model. Furthermore, the SUFI2 algorithm was used in SWAT_CUP software to calibrate and analyze the parametric uncertainty of the SWAT model. This algorithm quantifies the output uncertainty by 95% prediction uncertainty boundaries.

 According to the results of sensitivity analysis, the parameters Baseflow alpha-factor (ALPHA_BF), Manning’s “n” value for overland flow (OV_N), and Precipitation Laps rate (PLAPS) were the most sensitive parameters to flow, sediment, and total phosphorus, respectively. The best Nash-Sutcliffe (NS) coefficients for runoff, sediment, and total phosphorus simulation obtained in all stations and after full calibration and validation periods were equal to 0.76, 0.56, and 0.92, respectively. Simulation of the peak points of the diagram of all three quantities was also associated with increased uncertainty and decreased model prediction accuracy, but due to the placement of more than 70% of the measured runoff and sediment values and nearly 60% of the measured total phosphorus values in the prediction uncertainty boundaries generated by SUFI2 algorithm the final value of the parameters used in the calibration process can be appropriate for simulating future scenarios in similar mountain catchments. The main weakness of the model is simulating the peak points of flow and sediment discharge. In the case of flow and sediment discharge, the liability of modeling can be generalized due to the lack of accurate prediction of the snowmelt inflow to the river in spring, which begins to increase in February and reaches the peak point in May. A considerable number of missing data in meteorological stations can effectively reflect the lack of accurate model prediction at the peak points. In this region, missing daily temperature data compared to other meteorological parameters has been significant. The dependency of the SWAT model on many experimental and quasi-experimental models such as SCS-CN and MUSLE can be another factor affecting the weakness in predicting the peak points of the sediment discharge, as well.

 According to the uncertainty analysis results, most of observed flow, sediment and total phosphorus discharge values were within the uncertainty prediction boundaries generated by the SUFI2 algorithm. The NS coefficient for all three variables has met the satisfactory modeling threshold. Therefore, it seems that the sensitive parameters identified and used in the calibration process in this study and their final values can be appropriate for modeling future scenarios for this study area and similar mountain catchments. One of the limitations of the present study was a large number of missing data in meteorological stations, especially for the temperature variable. Thus, providing required measured meteorological data to the model may emhance the simulation, especially at peak points.

The purpose of this study is to compare and evaluate five different methods of estimating the evapotranspiration of the reference plant on a nine-year daily data scale in Yazd province. Selected methods included Hargreaves-Samani (HS) , Priestley-Taylor (PT) , Turk (Turc) , Makkink (MK) and Dalton (D). For this purpose, data from ten synoptic meteorological stations were used covering a period of 9 years. The results of the mentioned methods were evaluated by FPM-56 method. Also, using FPM-56 method, the mentioned methods were calibrated for the studied stations. Also, using FPM-56 method, the mentioned methods were calibrated for the studied stations. RMSE, NS, SI, MAE, R^2 statistical criteria were used to evaluate the results. The results showed that before calibration the results of different methods are very different from FPM-56. The only acceptable model before calibration was the HS model. After calibration, the results of the models improved and model D, which was the worst model before calibration, was recognized as the best model for estimating evapotranspiration in Yazd province among the five selected methods. Mean values of Model D before calibration MAE = 3.83, R^2= 0.84, NS = -1.99, SI = 0.83, RMSE = 4.21 and after calibration MAE=0.83, R^2=0.86, NS=0.72, SI = 0.22, RMSE=1.02 was obtained. After calibration, Turc, PT and MK models were in the next categories of the best models.

In this study, sediment load in Shirin Darreh Dam basin was estimated based on hydrological, UNESCO and FSM methods. Comparison between the total deposited sediments in the reservoir (17 Mm3) and results of the three methods showed the hydrological and FSM methods with the estimated value of 1158000 and 5565000 m3/year were the most proper and the most improper ways to sediment load estimation, respectively. Annual erosion intensity based on EPM was obtained about 1426300 m3/year, and the actual sediment delivery ratio was calculated about 0.78. The predicted sediment delivery ratio based on the results of EPM method and the three methods of total sediment load, and some of empirical models, was calculated. The results of the calibration showed that the hydrological method and the empirical model, in which the slope is the most important factor to obtain the sediment delivery ratio, with minimum error and maximum accuracy were the most proper methods.

The use of appropriate and reliable soil moisture sensors can greatly help the process of soil moisture monitoring and irrigation scheduling. The purpose of this study is to evaluate optical sensors for measurement of soil moisture under different conditions of irrigation water salinities. These sensors are based on the active proximal sensing techniques in which measure the reflections emitted by the objects in a specific range of the wavelength (300-1100 nm). In this study, four irrigation water salinity treatments (2, 6, 10 and 16 dS.m-1) were applied to the soil columns (or Lysimeters). Each Lysimeter have been equipped with an optical sensor, connected to a data logger and monitoring screen. Simultaneously, gravimetric and volumetric soil moisture of the Lysimeters have been measured to calibrate the readings of these sensors and to estimate the accuracy of calibration equations. The results showed that the highest accuracy of the sensors occurred at the salinity level of 2 dS.m-1, where the coefficients of R2, RMSE and NSE were to around 0.92, 0.02 and 0.92, respectively. In addition, declines in the accuracy of the sensors were observed for the salinities of 6 and 10 dS.m-1, but were in the acceptable range. While, for the salinity level of 16 dS.m-1, the accuracy of the sensors was drastically decreased and the NSE reduced to the unacceptable value of 0.55. According to the results of this study, these optical sensors can be confidently recommended for measurement of soil moisture and irrigation scheduling for salinities of less than 10 dS.m-1.

To evaluated ORYZA2000 model, an split-Plot in RCBD experiment with three replication. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, from 2012 to 2013. The main factor was irrigation management at three levels (flooded and water stress) and sub-factors include rice genotypes. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R2), the absolute and normalized root mean square errors (RMSE). The results indicated, the RMSEn for predicting grain yield in calibration and validation phases for rice genotypes was assessed in the range of 4 to 16 and 9 to 17 percent respectively and the RMSEn for predicting amounts of biological yield in calibration validation and phases for rice genotypes was assessed in the range of 8 to 15 and 9 to 19 % respectively. Results show that, coefficient of determination values for grain yield and biological yield, 0.78-0.94 and 0.84-0.88, respectively. Results show that, ORYZA2000 could be used successfully to support irrigation management under the pond and vegetive water stress conditions.