فهرست مطالب abolfazl majnooni heris

Evaporation is one of the most complex and important processes in studying hydrological and meteorological factors and plays a major role in determining the energy balance equations on the earth's surface. So, knowing the exact amount of evaporation volume is important for monitoring and correct management of water resources, irrigation planning, determining the irrigation needs, estimating evaporation from the reservoir of dams and modeling hydrological projects, especially in arid and semi-arid regions. On the other hand, modeling such a complex process in which many parameters interact with each other is so difficult that it is not possible to simplify this issue without multiple assumptions. Therefore, accurate estimation of evaporation has always been of great importance. Many experimental methods have been presented in estimating evaporation, but since these methods require a lot of input data or it is not possible to measure the variables in all areas, many of these methods have lost their effectiveness. Therefore, it is necessary to use methods which need fewer number of meteorological variables and estimate the evaporation with high accuracy. Therefore, the aim of the current research is to evaluate and present the most accurate model of evaporation estimation using three data-driven models in six synoptic stations in arid, semi-arid and humid climates of Iran, so that the proposed model, in addition to having sufficient accuracy, requires fewer input parameters to estimate evaporation even when there is no sufficient data.

In this regard, the ability of three machine-learning methods of gradient boosted tree (GBT), generalized linear model (GLM) and artificial neural network-multi layer perceptron (MLP) in estimating the amount of pan evaporation in dry (Yazd and Bafq stations), semi-arid (Birjand and Siah-Bisheh stations) and humid climates (Sari and Ferdous stations) were investigated. Daily parameters of some fundamental and effective meteorological variables on evaporation during the time period of 2001-2020 were collected. In order to investigate the possibility of using different combinations of meteorological parameters to estimate the evaporation as accurately as possible, six different combinations of meteorological parameters (average temperature, relative humidity, and wind speed and sunshine hours) were considered. Also, to evaluate the accuracy of the mentioned models, four assessment criteria were used including root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R) and scatter index (SI). Furthermore, diagrams of time series of the best models and the distribution diagram of observed and predicted pan evaporation by the models were presented and the most suitable combination of meteorological parameters that had suitable accuracy for estimating pan evaporation was suggested.

The results showed that in Birjand, Yazd, Ferdos, and Siah-Bisheh stations, MLP-VI with RMSE of 1.97, 1.95, 1.97, 2.91, respectively, performed more accurate than other studied models. Moreover, In Sari station MLP-IV and in Bafq station, MLP-V, with RMSE of 1.41 and 1.92, respectively, provided the most precise estimates of evaporation values. Finally, it can be comprehended that in all three studied stations, MLP provided the most accurate estimations of the amount of pan evaporation and it is suggested as a method with high degree of accuracy. Furthermore, GBT presented the weakest performance in comparison with other studied models. The mentioned trend about the high accuracy of the mentioned models for all studied stations can also be concluded from presented Figures. So, it can be inferred that the accurate models mentioned in each station had the least distribution around the bisector line and had the most accuracy and the least error. In other words, it is possible to estimate the evaporation values in all stations with the meteorological data of temperature, relative humidity, sunshine hours and wind speed with acceptable accuracy.

Evaporation is one of the main components of water balance in agriculture and is one of the effective and influential factors for suitable irrigation planning. Therefore, accurate estimation of this parameter has a significant role on reducing excessive water consumption. So, in this study, three data-driven models of MLP, GBT and GLM were implemented in six stations including Yazd, Birjand, Sari, Bafq, Siah-Bisheh and Ferdous. The obtained results indicated that the sixth scenario using all utilized meteorological parameters in Yazd, Birjand, Siah-Bisheh, and Ferdous stations, forth scenario in Sari and fifth scenario in Bafq station with the lowest error provided the most accurate estimates of the evaporation and may be recommended for proper estimation of pan evaporation values.

A combined assessment of drought risk and associated impacts on crop production based on a probabilistic approach seems appropriate to understand the multivariate nature of drought risk in agriculture. To overcome the problems caused by drought impact detection, several approaches have been developed in recent decades. Among the multivariate analysis approaches, copula functions are very popular. Copulas use univariate marginal distributions to form a joint distribution. The joint distribution can be described by the corresponding marginal distributions and copula functions that describe the dependency structure. In this research, using the statistical precipitation data in the Tabriz plain in eastern part of Lake Urmia basin, and yield of rainfed wheat in this area, a model based on copula functions was developed to determine the diffrent probabilities of yield risk and different drought conditions. Also, the application of copula functions related to rainfed wheat yield in this region was performed for the first time, and the presented method will be applicable to other areas and other crop cultivation.

In the case of meteorological drought, the basis for calculating the degree of drought is determined by comparing the amount of precipitation with the long-term average or its normal values. The SPI index is considered to be an appropriate and powerful index to use as a time scale droughts monitoring. Basically, SPI was created to detect the lack of precipitation on multiple time scales. Among the reasons that make the use of this index so popular, we can mention the standard nature of this index as it can be used in regional studies and establish a temporal relationship between drought events in different parts of the same area. The SPI index is a dimensionless index and its more negative values show the more severe the drought.
Analysis of variables individually is easy and can be analyzed by statistical distribution functions; but statistical analysis joint variables is very complicated and impossible in most cases. If the correlation criterion of these variables is known, their joint probability distribution can be obtained using copula functions. Using copula functions for modeling has a high degree of flexibility as it is possible to choose different marginal distributions to create a multivariate model. Copulas are functions that form a bivariate or multivariate distribution based on two or more univariate marginal functions. Several copula functions can be used to construct a two-dimensional joint distribution of hydrological and agricultural variables, among which Archimedean and elliptical copula families are the most commonly used. In the present study, six copula functions are used and the parameters of the paired functions are determined using the two-stage maximum likelihood method, which estimates the parameters of the marginal distribution and the copula function by forming two likelihood functions. In order to investigate joint probability of rainfed wheat yield and drought index, the time series of rainfed wheat yield in the Tabriz Plain region and SPI index during the last 30 years from 1990 to 2020 was applicated in this study.

In general, the improvement in agricultural methods, investments and technological advances during this period have led to a continuous increase in crop yield, however, a sharp drop in crop yield is clearly evident at times during the reporting period. In this research, to ensure that the observed trend does not affect the results, the Copula model was built using the detrended time series data by removing the trend in the values and the variance in the yield data. Based on the results obtained, crop production decreases dramatically during severe droughts, so such sensitivity to moisture deficits caused by low rainfall after several wet years can be attributed to farmers' expectations and management policies driven by high productivity during the previous ones wet years were determined.
To use series of standardized yield and growing season SPI in copula, the most appropriate distributions were selected and used, logistic and normal, respectively. Also, according to the calculated Kendall correlation (0.35), the best fit joint was Claytons function with AIC = -11.10, RMSE = 0.036 and used to construct the joint probability distribution of the standardized yield series of rainfed wheat and SPI of growth Period. Results showed that the cumulative probability of yield risk event in mild, moderate, severe, and very severe drought was 18.42, 7.82, 4.26, and 2.32 percent, respectively,and for an overall rainfed wheat yield risk and drought condition is about 33%. Meanwhile, the probability of rainfed wheat yield risk and non-drought events is only about 7% and joint probability of yield risk and SPI>1 is so close to zero.

In the current research, the probability of occurrence of the rainfed wheat yield risk and drought conditions was extracted by copula functions. Based on the results obtained, most changes in yield occur when the drought index is in the range greater than -1.5. In other words, in the conditions of severe and very severe drought, the yield of rainfed wheat does not show noticeable changes in probability. The opposite situation can also be observed for the situation of very wet years, that when there is high amounts of precipitation and the drought index show values higher than 1.5, the yield of the crop does not show much change. Thus, the SPI must be greater than one in order to achieve the desired yield and not be at risk of rainfed wheat yield, which in this study is considered to be a standardized yield values greater than zero. Because in this range of SPI, the joint probability of yield risk is estimated to be very close to zero. Therefore, this threshold can be introduced as the rainfed wheat yield safety threshold, but depending on the situation of the region and the drought index, the drought threshold (SPI<0) contains cumulative probability about 33% of the rainfed wheat yield risk.

This research focused on the application of Support Vector Machine (SVM) and Boosted Trees (BT) algorithms for simulating precipitation and runoff in two stations, Akhula and Pole Senikh, in the Tabriz Plain, Iran. Meteorological and hydrometric data were collected from 24 stations in the Tabriz watershed, obtained from the Regional Water Company and East Azerbaijan Meteorological Organization. Precipitation and runoff values were used as input to the model with a one-day time lag, and monthly runoff values were estimated and compared with monthly observations using evaluation criteria. The results showed that for both study periods, SVM model performed better than BT model for Akhula station, while BT model performed better than SVM model for Pole Senikh station. Additionally, the cross-correlation coefficient for the two study periods was found to be 0.83 and 0.82 for Akhula station, and 0.83 and 0.77 for Pole Senikh station, respectively. In the time series results, there was no clear trend in precipitation over the observation period. However, river flows at the Ahvaz and Pole Senikh stations, particularly after 1995, showed a significant decline, mainly due to factors such as runoff, agricultural expansion, and industrial development

Water is a key element in hygiene during the COVID-19 pandemic. The present s tudy aimed to survey the opinions regarding the possible impact of Coronavirus on water and wastewater sources and facilities.

The experts and managers of the Regional Water Organization and the Water and Wastewater Company were surveyed using a checklist  (ranking-descriptive) in the present cross-sectional descriptive s tudy. One-sample and two-sample chi-square tests and non-parametric Mann-Whitney test were used for s tatis tical analysis.

In total, 70.9% of participants believed that the outbreak of COVID-19 affected the water resources and facilities in terms of consumption and supply while increasing the consumption (93.2%) and creating a significant challenge in supply (83%) had des tructive effects on other uses, especially agriculture (22.7%). Also, 92.3% believed that managing urban water consumption during the Corona outbreak and modifying the consumption pattern is necessary. The need for more preparation (79.6%), funding (86.8%), and training (96.8%) was recommended. Regular monitoring of water was emphasized by 70.9% of the participants. It is noteworthy that only 50.4% of the respondents believed that the treatment done on the water in the water treatment plants can control the coronavirus.

The performance of managers and experts regarding water sources and facilities is a function of their beliefs regarding the impact of the COVID-19 outbreak. About 50% of the participants failed to believe in the effectiveness of the exis ting water treatment in deactivating the coronavirus. Also, specialized training is recommended to increase knowledge.

Estimating runoff due to rainfall is a very important step in planning water resources, especially in watersheds without hydrometric stations. In this study, the rainfall-runoff simulation of Akhola station located in the Ajichai basin was discussed and the most suitable rainfall-runoff model was presented by using data mining methods and comparing their performance. For this purpose, the desired data (rainfall, discharge, temperature) for this study were received monthly from the water and meteorological organizations of the East and West Azerbaijan provinces. Random Forest and Artificial Neural Network data mining models were used for simulation. The comparison of observed monthly runoff values with monthly runoff estimated by models was done using evaluation criteria. In this study, CC values ​​(correlation coefficient) for test sets in the random forest model and artificial neural network were determined as 0.77 and 0.86, respectively. The analysis of the results showed that the ANN model has a higher performance and efficiency than the RF model for the Akhola station. Among other results of this research, we can mention the time series of rainfall and runoff of the station during the last 20 years. According to the obtained graphs, during these 20 years, there was no clear trend for precipitation in the Ajichai basin, and the time series graphs showed that the precipitation in these areas was fluctuating. But the time series for Ajichai discharge at Akhula station showed that a completely downward trend was recorded for the river water flow, which is the reason for the decrease of the discharge entering Lake Urmia and the lowering of the lake water level.

The use of accurate and continuous data series is a necessary condition for most statistical and hydrological studies. Due to the importance of precipitation as one of the most important climatic and hydrological variables, in the present study, in order to predict the daily precipitation of Tabriz, Copula functions were used and the results were compared with intelligent methods and classical statistics. To predict precipitation in Tabriz station, precipitation data of Sarab, Sahand, and Maragheh stations were also used as auxiliary stations. Based on the obtained results, among all the methods studied, the M5 method with RMSE values of 3.14 mm, and the MAD method with 2.13 mm and the RF method with RMSE values of 5.18 mm and MAD 3.04 mm have the highest and lowest accuracy in estimating precipitation events, respectively. Among Archimedean copulas, the RMSE and MAD values for the Gambel function are 3.89 and 2.51 mm, respectively. Despite the range of estimation data is still very close to other methods, considering the capabilities of Copula functions, including the ability to apply multiple conditions and its probabilistic nature, which considers the behavior of the phenomenon, it can be acknowledged that in similar circumstances, the ability of Copula functions to estimate the missing data of phenomena such as rainfall is acceptable.

Climate change is one of the main issues in the 21st century and has been felt in many regions of world. The greatest impact of climate change is on the water resource sector. Ajichay, as one of the main agricultural areas and a source of water consumption around the Lake Urmia, has lost its efficiency as the supplier of water and is considered as the center of crisis due to changes in the climate, lack of precipitation, and human factors. Therefore, the current study aims to investigate the impacts of water resources management scenarios for adaptation of climate change on water resources, cropping patterns and profits of farmers using a hydro-economic model. The HadCM3 model and LARS-WG downscaling were used to generate daily climatic data under the emissions of A2 scenario. The results showed that the average rainfall decreased in 38% under A2 emission scenario during 2018-2050 period. In the next period of 2018-2050, the average annual temperature will also increase by 2.5 °C compared to the baseline period. Changes in the cropping area due to climate change show that among the studied crops, bean had the highest reduction in cultivation, which stemmed from its high-water requirement. Results showed the profit in all the sub-bases had a rise after increasing irrigation efficiency scenario. Thus, applying increasing efficiency scenario, in addition to more useful and efficient use of allocated water, will also increase farmers' profits which offer a better situation than the other scenarios. Overall, the findings of the current study revealed that without changing the management strategies there would be a considerable reduction in water resource in near future. The analysis of scenarios revealed that policies alone cannot compensate for water problems and there is a need for plenty of scenario for optimum results.

Hydraulic conductivity and Specific storage are known as the most important hydraulic characteristics of aquifers. Recently, due to software advances, the use of numerical models in the operation of groundwater aquifers has expanded. Modeling is one of the best tools for studying and simulating the state of water resources. One of the advantages of modeling is the simultaneous determination of several parameters such as hydraulic head, flow path and etc. Likewise, via modeling, it is possible to simulate the reaction of the basin against changes such as natural or artificial recharge and the amount of pumping, and by applying appropriate solutions, determine the best performance of the system then use it to manage the basin. In the present study, MODFLOW numerical model and GMS user interface were utilized to simulate and calibrate the model. Accordingly, the hydrodynamic properties of the Shabestar plain aquifer were evaluated regionally. As a result, the RMSE values of hydraulic head for the steady-state and non-steady-state models were 0.59 (m) and 0.95 (m), respectively. The obtained results demonstrated that the more heterogeneous the aquifer, the more diverse the hydrodynamic coefficients will be, and this variation does not follow a specific trend due to the existence of geological formations, the density and the porosity of the formations.

In this study, based on precipitation amounts, precipitation time intervals occurrence and evapotranspiration, rainfed Potential Index (RPI) was introduced to assess the capacity of dryland farming areas Which is very important in potential of rainfed issue due to containing the impact of precipitation remaining in soil; since precipitation remaining related to soil water content capacity and will be effective on yield production, therefore, behavior of rainfed wheat yield was discussed against RPI index various in the East Azerbaijan province and a model were developed to estimate the rainfed wheat yield using PRI. The results showed that the highest and lowest mean rainfed potential index ((RPI) ̅) and frequencies of RPI with more than (RPI) ̅ amount were in Maragheh and Sahand plains, respectively. Investigations showed that the precipitation occurrence multiplicity is not representing a high potential alone for rainfed farming. Since, Bostanabad area with the highest occurrence value (945 times) due to high frequency of trace rains (less than 1.4 mm/d) was not showed good yield production in during the study years. Generally, according to that the southern and western regions of province have high and low rainfed farming potential and RPI, respectively. Also, the proposed model calibration coefficients, both in the province scale and all stations except Sahand with P-value less than 0.01 or 0.05 were valid to estimate the wheat yield based on the new presented index.

Prioritizing different types of irrigation systems is essential for proper management of soil and water resources in the south of Ahar (9000 hectares). For this purpose, the physical and chemical properties of 44 soil profiles (soil texture, depth, lime, gypsum, salinity and alkalinity) were used and the ability of the soil to be irrigated using the limitations system as well as the suitability of the study area for the drip, sprinkler and surface irrigation systems were determined by parametric method. The application of the limitation system results showed that soil and topography were the most important limiting factors and the irrigation capacity of the study area was in classes III (arable land) and IV (limited arable land) with approximate extension of 75% and 25% respectively. Based on the results of the parametric method for surface irrigation application, only 4% of the land is classified as S1 (highly suitable) and S2 (suitable), S3 (relatively suitable), N1 (almost non-suitable) and N2 (non-suitable) with extension of about 31%, 46%, 17% and 2% in the study area. In addition, the southern parts of the area were not suitable for surface irrigation due to the high slope, and the lands for sprinkler and drip irrigation classified in S2 and S3 classes and covers 70% and 25% of the study zones and so the rest of the lands are more susceptible to sprinkler irrigation than drip ones. Based on prepared maps, about 5000 hectares of lands

More than half of the agricultural lands in arid and semi-arid climates are rainfed. Many climatic variables affect the yield of rainfed crops, among them rainfall is the most important variable. The aim of the present study is to determine the yield functions of rainfed wheat in Tabriz, Sarab and Maragheh stations located in the east of Lake Urmia basin, considering the changes of climatic variables during different stages of rainfed wheat growth. In order to model the yield using multivariate regression method, some precipitation variables such as, number of effective precipitation events, vegetation precipitation deficit, reference precipitation and evapotranspiration deficit in rainfed conditions during six stages of rainfed wheat growth including germination; End of germination until the beginning of flowering; Flowering stage; Finishing flowering until the seeds start to fill; Seed filling stage and whole growing season were used. In general, based on the obtained results, precipitation fluctuations have the greatest effect on wheat yield. Therefore, identifying the precipitation regime and analyzing its characteristics is important for assessing yield fluctuations of rainfed crops. Among the growth stages, the fluctuation of the proposed traits in the whole growth season has a greater role in determining yield functions. Yield functions were determined using variables that had a significant correlation with yield. For this purpose, 22-year and 3-year data were used for calibration and validation, respectively. The results of the model efficiency coefficient and normalized root mean square error indicated better effeciency of Enter method in the Sarab (EF=0.55 and NRMSE=0.19) and the Moderate accuracy of Stepwise method in estimating the rainfed wheat yield in Maragheh and Tabriz. In Maragheh and Tabriz, the Stepwise method with average relative error values of 21% and 15.6%, respectively, and in Sarab, the Enter method with an average relative error of 16.5% had better results in yield fitting.

Despite studies on the performance of superabsorbents in improving soil physical conditions, as well as increasing the yield and productivity of water consumption, economic issues have received less attention from researchers. Therefore in this study to investigate the effects of water stress and superabsorbent polymers on yield and yield components of wheat in 2015-2016 growing years, a factorial experiment was carried out in a randomized complete block design with three replications. Treatments consisted of combination of three levels of irrigation to supply 100, 70 and 50% crop water requirement (FC, 0.7FC, 0.5FC respectively) and three levels of superabsorbent (Stockosorb) with the amount of 0, 50 and 100 kg.ha-1 (S0, S1, S2 respectively). The results of economic indicators showed that the highest net income was allocated to S0,FC and S1,0.7FC treatments. The highest gross income to production cost ratio was allocated to the S0,0.7FC treatment, which had a significant difference with the control treatment (S0,FC) at the 5% level. The maximum (+44.2%) and minimum (-11.7%) of net income to irrigation water amount ratios were belong to S1,0.7FC and S2,0.5FC  treatments, as compared to control treatment (S0,FC), respectively. Therefore, in the best (S1,0.7FC treatment) condition, compared with control treatment, superabsorbent and water stress interaction effects increased gross income and net income equal to 12.2 and 1.1%, respectively. The investigating interaction effects of treatments showed that the superabsorbent application is recommended only in S1,0.7FC treatment condition due to increasing yield and cultivation area  (leading of reducing water consumption) and economic justification.

Annual and seasonal rainfall distributions are the main determinants of yield in rainfed conditions, of which seasonal rainfall is more important. Therefore, it is necessary to provide precipitation indicators that have a significant conceptual relation with crop performance fluctuations. In the present study, the relation between rainfall uniformity indices and rainfed wheat yield in Tabriz plain was evaluated in 19-years period. Also, in order to examine the effect of precipitation more accurately, the Rain-Time Index [M1] [M2] (RTI) was used, which could indicate the effect of simultaneous changes of the two factors of rainfall time and rainfall amount on crop yield fluctuations. The results showed that the correlation between rainfed wheat yield and slope of uniformity line (ratio of cumulative precipitation per length of growing period) was significant at 1% level. However, there was no significant correlation between the uneven distribution index and yield. Also, according to the obtained results, the first effective rainfall event is the most effective rainfall event on the yield of rainfed wheat. It seems that the inadequacy of effective spring rainfall, which is one of the main reasons for the low yield of rainfed lands, prevented the explanation of the positive effect of late season rainfall on yield. Therefore, in order to evaluate the effect of intermittent precipitation and Rain-Time Index [M3] [M4] on yield more accurately, a single supplementary irrigation should be applied at the stage of grain filling and its effect on the studied indicators and yield should be investigated.

Rainfed cultivation is one of the best ways to rich the sustainable development with optimal use of green water. About 75 percent of the world's cultivated areas are rainfed, which forms important part of the international economy. For a long time rainfed cultivation has been a common method in low-rainfall areas of Iran and mentioned method is one of the main ways of producing crops yet. Rainfall is an important factor in rainfed agriculture, so its limitations and non- conformity with planting season can reduce the production efficiency. Wheat growing period consists of three seasons of the year and rainfall in spring, fall and winter is effective on wheat growth. Cereal grains, especially wheat, are the most important food source in the world. After cereals, legumes are considered to be the main human food source and have significant nutritional and agricultural importance. In addition to being high in quality and valuable, suitable and complementary protein for cereals in the nutritional pattern, lentils are also among the legumes that stabilize the air nitrogen in the soil, which lends itself to crop rotation. Thus, intermittent cultivation of rainfed wheat with rainfed lentil is an important factor in stabilizing production in the developing countries. Given that Iran is in the arid and semi-arid regions and its population is growing, it is important to plan and evaluate the past in order to predict the future. Zanjan province is the fifth country with 6.9% of total grains production. In this study the effect of precipitation in water requirement of these two important products and their water stress in the climatic conditions of Zanjan plain has been studied.

Zanjan province is located at 47 degrees 10minutes to 50degrees 5minutes east longitude, 35degrees 25minutes 37degrees 10minutes north latitude, with areas of about 39369 square kilometers. According to the De Marten climate classification, the tropical, temperate and subtropical climatic zones can be identified at the applied level. Average rainfall over the past decade has been reported at 301 mm. For conducting this study, statistical data including meteorological and crop yield data 2004-2014 obtained from the Meteorological and Agriculture-Jahad Organization, respectively. Zanjan synoptic station with latitude and longitude 48degree 31minute east and 36degree 39minute north, 1663 meter above sea level. In the last 50year, the annual precipitation trend has been decreasing and this trend is affecting the water availability of rainfed plants in the region and can decrease yield of crops. Although in the long term, the average temperature trend is somewhat constant, but with decreasing rainfall, the yield has also decreased. in this study, due to the importance of wheat and lentil as two main crops of rainfed and their placement in arid lands of Zanjan plain, investigated the regression relationship between yield and evapotranspiration with precipitation and water stress coefficient.

The results showed that the average evapotranspiration values of wheat and lentil for Zanjan plain during the study period were 398 and 262 mm and the mean temporal stress coefficients were 36 and 33%, respectively. Regression analysis showed the highest correlation between actual evapotranspiration and yield so, the highest correlation between temporal stress coefficient and yield of rainfed wheat. But in lentils this trend was different and the correlation between water stress coefficient (Ks) and yield is more than the precipitation and lentil yield. For 25% decrease in precipitation, wheat yield reduced almost 18%. Generalizing this issue, the response to water stress coefficient of the product or Ky become 1.14. The regression equation also showed that in case of being precipitation about 300 mm, wheat yield in the area will be near one tone. For 25% decrease in precipitation, wheat yield reduced about 22%. According to figures, the fitted model was significant and well acted; and during the growth period of these crops, lack of water supply caused water stress as well as severe yield loss. The occurrence of high tension time percentage of 25% for wheat and 20% for lentil in all years of study period confirms the climatic potential of the region does not rich the standard requirements of plants and it is not possible to achieve optimal performance, so new methods of tillage, conservation agriculture and supplemental irrigation are recommended for achieving high yield, as well as the expected cultivation method for crops.

Remote sensing techniques have been applied to estimate the spatiotemporal distribution of evapotranspiration as an alternative for field measuring methods. The objective of this study is to estimate the maximum daily demand of rain-fed wheat from green water sources in Ahar county using the SEBAL algorithm and MODIS images. First, the results from the SEBAL algorithm were evaluated by comparing them to the results from the Eagleman-Affholder method in rain-fed wheat fields and to the results from Fao-Penman- Monteith method in irrigated wheat fields and then the wheat maximum daily evapotranspiration values were calculated in the study area. MODIS surface reflectance and land surface temperature images were used to monitor the variation of normalized difference vegetation index during the wheat growth period, to map wheat areas and to estimate wheat evapotranspiration during the wheat booting stage until the wheat yellowing stage in 2010. After evaluating the SEBAL algorithm during the mentioned period, the maximum daily demand of rain-fed wheat from green water sources was estimated on the 17th of July 2019. By comparing the wheat evapotranspiration values from SEBAL and from computational methods, the average absolute error and correlation were calculated as 0.61 mm/day and 0.9 respectively. It was also found that the wheat highest evapotranspiration occurred when the vegetation index curve had reached its peak. In this time, the wheat maximum daily water demand from the green water resources throughout the county in 2019 was estimated almost equal to 0.93 million cubic meters.

Empirical and theoretical methods (energy balance) are widely used to calculate the Crop Water Stress Index (CWSI) and irrigation scheduling to describe crop water status. In this study, irrigation scheduling was performed at the research farm of College of Agriculture, Urmia University, using a manual infrared thermometer and the empirical method of Idso et al. (1981) for the black gram under different irrigation regimes using drip irrigation in 2017. The experimental design was carried out in a randomized complete block design with three levels of irrigation I1, I2 and I3 which were 50, 75 and 100 percent water requirement in three replications, respectively. Using the baselines obtained for each treatment, the average CWSI values during the growth season of black gram for I1, I2 and I3 treatments were calculated to be 0.37, 0.23 and 0.15 respectively. The relationship between CWSI and total irrigation depth (mm) was determined as CWSI = -0.0008 (I) + 0.58, and the relationship between black gram grain yield (ton/hec) and CWSI was determined as Yield = -1.8237 (CWSI) + 2.1435 which their correlation coefficients (R2) were 0.98 and 0.99 respectively, which shows the high accuracy of regression models. In general, if the amount of water decreases with stress during the plant growth, the CWSI value increases, and as a result of increasing CWSI, the crop grain yield decreases. Finally, the no stress treatment (I3) with CWSI=0.15 was the basis for irrigation scheduling and then some relationships were established for determining the irrigation time using CWSI in Urmia climate for four stages of black gram growth; flowral induction-flowering, pod formation, seed and pod filling, and physiological maturity as (Tc  ̶ Ta)C = 1.9498  ̶ 0.1579(AVPD), (Tc  ̶ Ta)C = 4.4395 ̶ 0.1585(AVPD), (Tc  ̶ Ta)C = 2.4676  ̶ 0.0578(AVPD) and (Tc  ̶ Ta)C = 5.7532  ̶  0.1462(AVPD), respectively.

Water as the most limiting factor in agricultural production plays an important role in providing food for population of the country. Therefore, it is necessary to use optimal water resources of the country and increased its productivity. So to improve irrigation efficiency, as well as the proper use of land and available water resources the best irrigation system should be used to supply plant water requirement. This selection is influenced by various factors such as cultivar type, available water content, water quality, soil characteristics, climatic conditions, selective cultivar pattern, labor force skill, and etc. The mentioned effective parameters depending on the region may change. Therefore, it is necessary to identify the homogenies areas for application of irrigation system. The study area is the Ajichay River Basin in East Azarbaijan Province. This basin is located between 37°  30' to  38 ° '30 northern and  45° 24 '   47°  53' eastern. In this study AHP method and GIS were used for identifying homogeneous zones of irrigated and rainfed areas. Analysis Hierarchical Process method is one of the most comprehensive systems designed for decision making with multiple criteria. This method was first proposed by Thomas El Saaty in 1980, which is based on paired comparisons. This gives managers the opportunity to study different scenarios. In the AHP model, we construct a matrix for comparing two factors. It has two important features, 1- Considering multiple quantitative and qualitative factors in problem solving and 2- The ability to analysis complex issues through hierarchical factors. In this study, to determine the homogeneous irrigation regions, first, the criteria was determined. In AHP method questionnaires were prepared, to score, these questionnaires were provided to the experts of this field. Then using the AHP method the criteria was compared with together. Finally, for each of the criteria, the interpolation maps in the GIS using geostatistical methods were obtained. These maps were divided into different zones using available tables and resources. The maps were combined in their scores in GIS and homogeneous irrigation areas (sprinkler, drip and surface irrigation systems) were selected. In this study, the agricultural lands, including under irrigation lands, dry farming and gardens, were distinguished from non-cultivated lands. In agricultural land of Tabriz plain, applying sprinkler irrigation system has moderate restrictions and some areas face severe restrictions. In the southern parts of Bostanabad plain, the implementation of the sprinkler irrigation system is suitable. The possibility of sprinkler irrigation in dry farming lands was also investigated. Lands that located in the Bostanabad, Heris and Sarab plains will be relatively suitable for sprinkler irrigation. But for the Tabriz plain, the underground water and soil quality are low, applying sprinkler irrigation system has moderate restrictions. However, in Sarab plain, the appropriate area is visible. Implementation of drip irrigation system in the study area, in a large part of the Sarab plain and the southern parts of the plain of Bostanabad were appropriately determined. But in Tabriz plain and lands near the Urmia Lake, the implementation of this system has severe restriction. Like sprinkler irrigation, agricultural land of Tabriz plain has a moderate restrictions. Most areas of Heris, Bostanabad and Sarab plains, for applying this system will be relatively suitable. According to expert, water SAR and land gradients have more effect on the implementation of surface irrigation systems. If we can correct these two parameters with management and planning tasks, the implementation of this system will be appropriate in many areas of the basin. Most agricultural land has a moderate restriction on the implementation of this system. The AjiChay Basin with an equivalent area of 12600 km2 is one of the largest sub basins in Lake Urmia basin. Since agriculture is important in this basin and also the quality of irrigation water in some parts of this basin is low, therefore, it is essential to pay attention to the type of irrigation method. Considering the parameters of water, climate and soil, suitable and unsuitable areas for surface irrigation, sprinkler and drip irrigation systems were determined. Thus, implementing irrigation system in agricultural lands in the margins of Lake Urmia and in some areas, will be severe restrictions. Getting away from Lake Urmia the groundwater quality, which is mainly used for agriculture, using irrigation systems is relatively appropriate.

The use of superabsorbent polymers is one of the effective solutions to increase water use efficiency and optimal use of rainfall in arid and semi-arid areas. In this study the effect of different levels of superabsorbent STOCKOSORB is investigated on wheat yield and yield components under rainfed and irrigated conditions. For this aim, an experiment was conducted in the Research Field of Agriculture Faculty, Tabriz University, in the growing season of 2015-2016, in which the superabsorbent STOCKOSORB was applied at three levels of 0, 50, and 100 kg/ha. Based on obtained results, application of superabsorbent at 100 kg/ha increased the seed yield and water use efficiency of both rainfed and irrigated wheat farming significantly. The application of 50 kg/ha increased rainfed wheat yield but not irrigated wheat yield, significantly. Results showed the effect of superabsorbent on yield and water use efficiency in irrigated wheat was larger than rainfed wheat. Also, the effects of superabsorbent application were significant in rainfed conditions at treatment of S1 (increase of water use efficiency equal 25.9 percent) and in irrigated wheat at treatment of S2 (increase of water use efficiency equal 19.2 percent). Due to ratio of the increasing benefit as a result of yield increase to cost, application of superabsorbent is not recommended in wheat farming.

Due to the impact of various factors, selecting the best irrigation method for different conditions of the field has become a complex issue (Montazar and Behbahani, 2007). In this study, the best irrigation system selection among the sprinkler systems (including solid set, hand move, wheel move, traveling gun, center pivot, and linear move), trickle systems (including row crop drip, drip, and bubbler) and surface irrigation systems (including basin, border strip and furrow) was done using Charles Burt scoring method (Burt et al., 1999) for Famenin, Qahavand and Razan plains of Hamadan province. Scoring of the systems were performed based on some related properties such as the type of production, type of water source, climate, land, soil, social structure and, conditions of the studied regions. According to the results, the best choices and suitable irrigation methods among the mentioned systems based on their priority in the studied area were; solid set, drip tape and basin methods in sprinkle, trickle and surface irrigation systems respectively. Despite increasing the labor costs due to sprinkler’s displacement, the solid set method with moveable sprinklers due to less investment was selected as an appropriate and advisable system. If surface irrigation system is identified as the suitable choice for an area, the use of low pressure distribution networks and gated pipe systems can improve the irrigation efficiency and reduce the infiltration losses, which should be considered in projects.

Regions Annual precipitation is one of the important factors for successful rainfed agriculture. Generally, cold and moderate climate regions with annual precipitation of 300 mm or more are suitable for rainfed wheat cultivation. Wherever, this amount is averagely 248.5 mm in Tabriz region over the last 30 years. In this research the possibility of rainfed wheat cultivation in the Tabriz plain based on precipitation amount and air temperature factors was investigated. For this purpose a set of 30 years data (1985-2015) was applied. The studied period was devided into 6 sub-perids of 5 years and the probability of success in wheat cultivation was evaluated in the rainfed condition. Results clarified that the supplemental irrigation was inevitable in the studied area. In order to determine the suitable time for supplemental irrigation practice, the autumn and spring precipitation amounts were calculated and subsequently these values were compared with corresponding crop water requirements. Finally, with investigation of wheat sensitive stages to water stress and comparison with seasonal rains, the suitable time of supplemental irrigation was proposed for June during filling stage. Over the recent 29 years the precipitation amounts of June have been less than minimum crop water requirement. Furthermore, the accurate management of the planting time can improve autumn precipitation utilization, as the autumn precipitations have been satisfactory in 3.8 years of each 5 years sub-period, averagely. The Growing-Degree-Days (GDD) index was applied for calculating the date of different growing stages of wheat. Also regarding to the importance of temperature in rainfed wheat growing process, the different phenological stages of the wheat from temperature view were investigated and the results were compared with required values.

In measurements of crop evapotranspiration by lysimeter, climate of cultivated field may be different from lysimeter point, also a lysimeter cannot be utilized for measurements of several crops during a limited time. For measurements of the standard maize evapotranspiration by the water balance method, soil water content was measured in a field experiment under furrow irrigation system during 2003 and 2004. Maize root depth was varied in respect to time and for reducing the error of measured soil moisture and calculating the stored water in soil profile, soil water content was only measured in the root zone until the root reached to its maximum length (1.8 m). In this study, the measured standard evapotranspiration of maize via water balance equation in the field, was compared with the estimated values using the methods of Penman-Monteith, HargreavesSamani and MSM2 model (Maize Simulation Model). The results showed that applying the water balance method for measuring maize standard evapotranspiration was simple and favorable in field conditions. The investigations confirmed that by use of MSM2 model, modified Hargreaves and Penman-Monteith’s equations, the standard maize evapotranspiration values could be estimated, with the errors of -2% , 5% and -25%, respectively. The results showed that with limited data condition, if only, the minimum and maximum air temperature were available, the maize standard evapotranspiration value could be estimated favorably, using the modified Hargreaves-Samani’s equation and crop coefficient.

The studies are needed to investigate the impact of these factors on crop yield and it requires a lot of time and cost. In recent years the agriculture production simulator models such as APSIM for irrigation management and fertilizer are used. These models taking into account several factors such as water management, physical and chemical properties of soil, water and nitrogen in the soil profile that can play an important role in modern agriculture. APSIM simulation model (Agricultural Production Systems Simulator) was first calibrated and validated using field data in 1392 and 1393. These data are including four irrigation levels 20 % more irrigation, equal to crop irrigation requirement, 20% and 40% less than irrigation requirement of maize and nitrogen fertilizer treatments are included 300, 150 and zero kg/ha. The cultivar of maize was hybrid SC704 of the late maturing type of corn varieties under furrows irrigation. APSIM simulation model was evaluated for predicting Maize yield, moisture and nitrogen of soil and by comparing simulated values with the measured data the validity of the model was confirmed. The maximum yield of maize was estimated 14593 kg/ha for irrigation and nitrogen amounts of 1400 mm and 450 kg/ha respectively. Comparing the results of simulation with measured data showed the relative average error (RAE) of soil moisture was in the range of 2-18% and RAE of soil nitrogen was 4-14%.