مجله آبیاری و زهکشی ایران
سال پانزدهم شماره 6 (بهمن و اسفند 1400)

Determination of agricultural water consumption, as the main consumer of the country's water resources, is very important in order to plan and manage resource consumption and establish food security, water security and improve the livelihood of the growing population. Water consumption or actual evapotranspiration is the part of water used or delivered to the agricultural sector that is out of reach and cannot be reused. Estimating the spatial distribution of actual evapotranspiration (ETa) based on valid satellite data is a new approach in planning and determining water balance. In the study, amounts of actual evaporation, transpiration and evapotranspiration in the country and agricultural, horticultural and rainfed land uses were extracted using the methodology introduced by Food and Agriculture Organization (FAO), which is presented in the WaPOR database. The results showed that the highest actual evapotranspiration about 2500 mm occurs on the north coast and Lake Urmia. The results showed that the average amount of actual evapotranspiration in irrigated horticultural lands was 299.30 mm and in irrigated agricultural lands was 301.52 mm in a 12-year period. Accordingly, the amount of actual evapotranspiration of irrigated lands on a national scale and for the year 2018-2019 was calculated to 28.84 billion cubic meters, which is equal to 20.78 and 8.06 billion cubic meters for agriculture and horticulture, respectively. Furthermore, 72.1% of that belongs to transpiration and the other of that 27.9% belongs to evaporation.

This study aimed to calculate the crop water stress index (CWSI) of Quinoa. This study was conducted in a completely randomized design with four irrigation levels of 100 (T1), 75 (T2), 50 (T3), and 25 (T4) % of crop water requirements in three replications, and experimental treatments and measurements were mainly carried out during Quinoa growing season at 2017-2018 years. The results revealed that the highest of leaf, stem, root, inflorescence dry weights, and biomass by 11.3, 8.8, 2.8, 16.8, and 39.7 g were in the T1 treatment. Using the T2, T3, T4 compared with T1 were decreased grain yield (by 37.6, 52.5, and 64.8%), harvest index (by 30.4, 34.5, and 30.7%), Biomass (by 16.4, 29.7, and 51.1%). But, using these treatments was increased WUE (by 19.4, 36.6, and 77.4%) compared with T1. CWSI correlated significantly (P < 0.01) and negatively with grain yield and biomass. The results revealed that increased CWSI values with reduction of quinoa grain yield. Also, the results showed that the highest and lowest quinoa grain yield at average CWSI values of almost 0.05 and 0.61. Therefore, to achieve the highest grain yield in irrigation, the quinoa crop should be irrigated at 0.05 of the CWSI. The lowest CWSI values were observed in T1(by 0.04) and the highest in T4 (by 0.72). In this study, the average CWSI was calculated in the days before irrigation in T1, T2, T3, and T4 treatments, and its values were 0.05, 0.19, 0.48, and 0.72, respectively. The results also revealed that with crop water requirement change from 100 to 75 percent, the CWSI was about 3.8 times higher. Accordingly, the CWSI can be used to plan irrigation. The best irrigation time is based on T1 treatment when (Tc-Ta)a=2.41-0.21 VPD (5≤VPD≤20).

Due to technical limitations, most satellites cannot simultaneously collect images with high spatial, temporal, and spectral resolution. In this paper, the possibility of using DisTrade and TsHARP downscaling methods and STI-FM method in order to achieve high spatial resolution for MODIS and Landsat8 images was investigated. The RMSE value for sharpened images of 1 km to 30 meters was less than 3.93 ° C. In this study, the surface energy balance algorithm (SEBAL) was investigated to estimate the actual evapotranspiration distribution using a combination of Landsat 7 and MODIS satellite images based on the T-Sharp downscale method. The results showed that the integration of satellite images improved the accuracy of estimating actual evapotranspiration compared to Landsat 7 images. The mean squared error of estimated evapotranspiration during the growth period was determined in comparison with lysimetric data for Modis images of 1.24-2.91 mm / day and for integrated images of 0.81-1.1 mm / day. In general, the results of this study showed that the estimation of evapotranspiration using SEBAL algorithm and based on the combination of images with different temporal and spatial accuracy can provide acceptable results.

In the arid regions of Iran, the construction of Bandsar has been one of the methods of runoff harvesting. However, despite the large extent of these structures in some mountainous catchments, so far, no study has been done in Iran on the effects of mountainous Bandsars on the river flow regime and other components of the water cycle in a catchment. In the present study, the effects of mountainous Bandsars on the Marandiz river, located in the southwest of Razavi Khorasan province, and its effects on downstream water resources have been investigated. Based on field studies and satellite images more than 150 Bandsars were identified in the study area. The area of agricultural lands behind the Bandsars was determined based on satellite images, which is equal to 4.8 km2 (2.2% of the total area of the river basin). In order to estimate the runoff from rainfall on a daily basis, the Curve Number Method (SCS) was used for the period 1998-2018. The average annual runoff volume in the Marandiz river basin was estimated about 2.6 MCM and the average annual runoff coefficient was estimated as 12.4%. The minimum and maximum storage capacity of the Bandsars (SCB)were estimated to be 0.95 to 1.43 MCM, respectively. If the daily runoff volume is more than SCB, the flood can reach the watershed-outflow point and enter the downstream plain. The results showed that a maximum and minimum numbers of floods reached the watershed-outflow point were 14 (5% of days with runoff) and five floods (2% of days with runoff) during the 15-year period. Therefore, the mountainous Bandsars in the Marandiz river basin have been reduced significantly the floods entering the downstream plain which has resulted in a decrease in the downstream alluvial aquifer recharge and increasing the groundwater salinity.

Optimal operation of dam reservoirs is one of the important issues in the field of water resources management. In this study, optimal operation of dam has been investigated in a deterministic and probabilistic manner in order to supply maximum water demands of the dam downstream. The optimal allocation conditions of the system are examined by considering the probabilistic inflow and investigating the effect of cumulative distribution function on meeting the water demands. The chance constrained linear programming method has been used in the uncertainty approach for reservoir inflow. The study area is considered in Gheshlagh Dam located on Maryam-Negar River in Kermanshah province. Water supply optimization of water demands on downstream has been presented by using coding in LINGO software environment in two different modes. The results of optimization by deterministic approach show that the supply in the agricultural, domestic, and environmental water demands are 92%, 95% and 95%., respectively. In the probabilistic approach, considering the uncertainty in the inflow to the reservoir in two different ways, the results showed that not only is it not necessary to choose the best statistical distribution model of the inflow to the reservoir and the experimental distribution of Weibull is sufficient for this purpose, but also due to the reduction of the inflow volume to the reservoir, the optimal volume of the dam reservoir with a confidence level of 60% was estimated to be equal to 27.3 MCM. In this volume, the dam reservoir is fully able to supply the downstream demands of Gheshlagh Dam. Therefore, due to the uncertainty of the precipitation phenomenon, consequently the inflow to the dam reservoir and the obtained results, this approach is essential in the design and optimal use of dam reservoirs.

In the current study, economic analysis of deficit irrigation was conducted for a Thomson orange orchard in Sari in two scenarios of considering applied water including 1-only irrigation water, 2- irrigation water plus rainfall. Production and cost functions were modified in water and land limitation conditions using English method. These functions were determined for without and 4 days irrigation interval using mathematical analysis and aimed to obtain the maximum net income. Results showed that when rainfall occurs, irrigation water plus rainfall should be considered as applied waer in production and cost functions. In addition, when there is no water limitation, the highest net income per unit of land is obtained from Wm that is 277.4, 315.6 mm for without and 4 days irrigation interval. Production for this situation is 51.3 and 57.4 ton/ha, respectively. In water limiting condition, the optimum water depth (Ww) is 257.6 and 287.9 mm that causes more than 26% saved water. If there is also land limiting in this situation, the net income per unit of land decreases 3.3 and 4.1 percent. However, the net income per unit of water increases 4.2 and 5.1 percent. If there is no land limiting in this situation, by irrigation equivalent to full irrigation, the net income per unit of land increases 7.5 and 9.2 percent. This status obtains the highest net income per unit of water use. According to the current resutls, having an irrigation schedule causes 12% increase in production and if it is associated with deficit irrigation, causes 5% more increase in net income.

Today, efficient management and optimal use of wastewater resources in agriculture play an important role in reducing environmental hazards and surface water resources. In this study, in order to Evaluation of Treated Wastewater Irrigation Effect on yield components and yield of maize (single cross 704), an experiment carry out in factorial experiment based on a completely randomized design with treatments included; Water source factor (Wastewater (A1), Well water(A2)), Irrigation (subsurface method (I1) and (drip method (I2)) with three replication in 2018-2019 under lysimetric conditions, at the Sari Agriculture and Natural Resources University (SANRU). Based on the results, the effect of irrigation water source on grain yield, biological yield, biomass yield, 1000-seed weight, number of seeds per row and harvest index was very significant (P≤ 0.01). So that the average of the mentioned traits in irrigation with treated wastewater was higher than well water with the values of 918.66 kg/ha, 1319.55 kg/ha, 4421.02 kg/ ha, 302.13 g, 13.66 and 81, respectively. Also, the effect of irrigation method on grain yield, biological yield, biomass yield and number of grains per row of corn was very significant (P≤ 0.01). Based on the results, the subsurface irrigation method showed Superior results than the drip irrigation method. Irrigation with wastewater provides more nutrients especially nitrogen to the plant, compared to well water, which will increase the growth of plant organs. Therefore, plant yield increases with increasing the efficiency of the plant photosynthetic system. Finally, according to the findings, the increase in yield and yield components can be attributed to the superiority of using the wastewater source in the subsurface method compared to the well water source in both irrigation methods (subsurface and drop bar tape), and recommended it as a suitable alternative in irrigation of crops, especially corn.

Due to the limited access of water resources, population growth and hygiene, maintaining a groundwater resources with good quality is important. Agriculture and the continued use of fertilizer in cultivated lands lead to contamination of groundwater resources. In order to investigate the effect of forage maize biochar and urea fertilizer application on cultivating bell pepper, a factorial experiment in a completely randomized design with three replicates and nine treatment was conducted. The treatments consisted of three levels of forage maize biochar (zero, 2, and 5% Soil weight) and three urea fertilizer (75% 100%, and 120%). One bell pepper was transferred in 4- leaves pots containing 5 kg of soil and biochar, then in three stages and in each stage, 236, 314, and 376 mgkg-1 N of urea fertilizer was added to the pot. In the different stages of cultivation, drained water nitrate including the initial, middle, final, and the soil nitrate and fruit nitrate were measured final stage of the experiment. The results indicated that the forage maize biochar increased nitrate concentration from the soil the treatment the amount of 2% in the application urea of 376 mg kg-1 by 66.4%, Compared to the control. Nitrate leaching content in final stage all treatments decreased during the cultivation period and the highest decrease nitrate concentration occurred in obsevesion in 5% biochar and 236 mg kg-1 urea fertilizer 72%. Biochar decreased the uptake and concentration of N in fruit treatment in 2% biochar and 236 mg kg-1 urea fertilizer 44.4% as compared to the control.

Climate affects agriculture and the main effect of climate change on agriculture largely depends on two variables: temperature and precipitation. In this study, the effect of climate change on biomass and evapotranspiration of maize in Qazvin plain has been investigated. For evaluation, from the general circulation models in the LARS-WG model (EC-Earth, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR) and the scenarios of RCP2.6, RCP4.5 and RCP8.5 in the base period 2015-1986 and used in the following periods: 2040-2021, 2060-2041, 2080-2061 and 2100-2081. Evapotranspiration and corn biomass in baseline and future periods were calculated with Aqua Crop software. In this study, the results of the scenarios were compared with the data of Qarvin station for maize crop by statistical error criteria including explanatory coefficient statistics (R2), root mean square error (NRMSE) and absolute mean error (MAE). The simulation results of LARS-WG model in the base period showed that the model has more minimum and maximum temperature simulation accuracy than precipitation. Studies also show that the temperature will increase in future periods. Rainfall changes were seen as both decreasing and increasing. The simulation results showed that the biomass decreased compared to the baseline period in the following periods and transpiration evaporation increased in most of the models used.

Although walnut is one of the most important products in the world and in Iran, but so far little research has been done on irrigation and especially its water productivity. In this study, the yield, volume of applied irrigation water and irrigation water productivity of walnut orchards in three major regions producing this product in Fars province and in drip and surface irrigation systems were measured and studied. Net and gross water requirements of walnuts from the national document Water requirement, Penman Montieth method in the year of research and for long-term, estimated and compared with the amount of water applied in orchards by t-test. The results for a total of three areas and regardless of the type of irrigation system showed that the applied water was less than the gross water requirement of about 1500 cubic meters per hectare and this difference was not statistically significant. But compared to the long-term gross water requirement, this difference was about 3,000 cubic meters per hectare, which was significant. The amount of water applied in walnut orchards under drip irrigation systems was about 1600 cubic meters per hectare less than surface irrigation systems. However, comparing the amount of applied water with the gross water requirement of orchards showed that in drip irrigation systems, 1800 cubic meters per hectare was more than needed and in surface irrigation systems, 3600 cubic meters per hectare was less than required. In general, no significant difference was observed between yield values, applied water volume and water productivity in drip and surface irrigation systems. But in the study areas, yield values, water productivity and applied water volume were different.

In order to study the effect of deficit irrigation and plant density on antioxidant enzymes activity, compatible ‎Osmolytes, relative water content and yield of baby corn (Pashan cultivar) a field experiment based on ‎randomized complete block design (RCBD) arranged in split-plot with three replications was conducted at the ‎Education-Research Farm (With geographical position: 37°33' north, 59°11' east), Mashhad Branch, Islamic ‎Azad University, Mashhad, Iran, during in cropping season 2018-2019. Irrigation deficit at three levels (0 (Full ‎irrigation), 20 and 40% less than the irrigation requirement) was considered as the main plots and plant density ‎at three levels (100, 150 and 200 thousand plants/ha) were considered at the sub plots. Analysis of variance ‎showed that the effect of deficit irrigation on all variables, effect of plant density on relative water content, ‎husked cob yield, dehusked cob yield and dehusked standard cob yield and interaction between of two factors ‎on all variables (Expect: relative water content and superoxide dismutase activity) were significant. The results ‎showed that with increasing deficit irrigation (increasing stress) and increasing plant density, the relative water ‎content decreased. Also, with increasing deficit irrigation, superoxide dismutase activity increased. Mean ‎comparison of traits under influence of two factors showed that with increase of deficit irrigation and plant ‎density proline content, soluble carbohydrates and the activity of catalase and peroxidase enzymes increased ‎due to increased drought stress and intraspecific competition. Husked cob yield, dehusked cob yield and ‎dehusked standard cob yield decreased due to of deficit irrigation. But at all levels of deficit irrigation, cob yield ‎increased with increasing plant density. In general, the results showed that drought stress increased the content ‎of compatible osmolytes and the activity of antioxidant enzymes in the tested cultivar, but this increase was ‎not sufficient to reduce the effects of stress on yield.‎

Livestock manures are a source of pathogenic microorganisms that cause contamination of water surface and groundwater. The aim of this study was to simulate the effect of cow manure granulation on the transmission coefficients of Escherichia coli in a column of sand under saturated flow. Cow manure with particle sizes of 0.25, 0.5, 1 and 2 mm equivalent to 30 (ton/hec) in terms of dry weight was used. The effect of fertilizer treatments on the transmission of Escherichia coli in the soil was investigated by measuring the number of bacteria and chloride detector in the drainage water, up to 20 cm3 of pore volume. In order to determine chloride, Levenberg-Marquardt algorithm and nonlinear optimization were used, and to determine bacterial retention and transfer, a two-site kinetic Attachment-Detachment equation and inverse solution were used. The results showed that the bacterial transfer simulation was performed well for all fertilizer treatments by HYDRUS-1D using a two-site kinetic model (average of mean deviation and coefficient of determination was 0.056 and 0.905 respectively). The 0.25 mm treatment had the best agreement with the simulation results. The highest concentration of wastewater bacteria was obtained in the fertilizer treatment of 2 mm, which is due to the coarseness of fertilizer particles and faster and earlier removal of bacteria from its particles. The lowest attachment coefficient rate, was obtained in the fertilizer treatment of 2 mm (5.59*10-6 s-1) due to the release of more bacteria in this fertilizer treatment and as a result of increasing the rate of detachment coefficient (3.61*10-1 s-1). Also, with increasing soil depth, the amount of bacterial retention increased, which is probably due to the accumulation of bacteria on the surface of soil particles at lower depths.

Due to the lack of availability of synoptic stations, the high costs of their construction, or the possibility of the inaccuracy of their data or inaccurate calibration, it is better to find alternative tools, which meteorological datasets are one of these suitable devices. In this study, two datasets, GPCC and AgMERRA, were evaluated. The purpose of this study is to investigate the accuracy of these two datasets in calculating the water footprint of maize for a specific crop in a specific region as case studies. For comparison of the estimations, the average estimation, R2, RMSE, and maximum error (ME) were used. The results showed that GPCC is more efficient than AgMERRA in estimating the water footprint of maize. The average blue, green, and the total water footprint of maize in this province were 242/58, 149/47, and 392/05 m3/ton which was 207/58, 143/78, and 351/35 m3/ton for GPCC and 149/06, 110.58, and 259/64 m3/ton, respectively. According to the results, both datasets were more efficient in estimating the green water footprint than the blue water footprint. This study shows that datasets can be suitable tools in meteorological studies in agriculture, and if they are validated and calibrated, they can be used in various water management, such as irrigation management, water resources management, and agriculture management.

Today, due to limited resources, increasing the productivity of inputs, especially water inputs in the agricultural sector to achieve food security in the country is a fundamental strategy. In this regard, the objectives of the present study were to determine the physical and economic irrigation water productivity in the production of crop production under research conditions in Seed and Plant Improvement Institute (SPII) research farm in Alborz province based on 2016-2019 dates in 2020. In this study, in order to estimate irrigation water productivity used physical and economic productivity. According to the results, during 2016-2019 years, The mean of sale return percent of irrigated wheat, barley, canola and forage were estimated 13.4, 39.3, 38.9 and 19.5 percent and means of investment return percent of irrigated wheat, barley, canola and forage were estimated 15.5, 64.6, 63.6 and 24.8 percent. The means of physical productivity of irrigation water for wheat, barley, canola and forage were estimated 0.56, 0.51, 0.33 and 2.8 kg/m3 and means of economic productivity of irrigation water based on gross income for wheat, barley, canola and forage were estimated 8996.8, 10431.8, 18750 and 5915.9 rials/m3 and means of economic productivity of irrigation water based on profit for wheat, barley, canola and forage were estimated 1191.1, 10750, 7291.7 and 1312.2 rials/m3.

Estimation of evapotranspiration, which is one of the components of the hydrological cycle and also an effective parameter in irrigation planning, is very important, but often the limitation or lack of meteorological data prevents to use of the proposed method of FAO Penman-Monteith. In the present study, Artificial Neural Network (ANN) and Adaptive-Network-Based Fuzzy Inference System (ANFIS) are discussed in Improvement of estimates the ETo data in the absence of data. Climatic data in this study include radiation hours, wind speed, minimum, maximum, and average air temperature, which were used as model inputs based on the FAO56-PM equation in three stances. The data were obtained from 12 synoptic stations in arid and semi-arid climates. The results of evaluating the models showed that artificial intelligence methods provide better results than experimental methods. Also, both ANN and ANFIS models provide the best results with average temperature and wind speed input data, followed by minimum and maximum temperature inputs, medium temperature inputs and irradiation hours, respectively. Between ANN and ANFIS models, the ANFIS model Showed better results.

Groundwater quality assessment of this vital resource is of great importance. Therefore, the present study investigates the quality of Tabriz plain water using MI and PoS indices along with the normal distribution and Pearson correlation. The results obtained from the analysis of water samples taken in Tabriz plain show that the concentration of all heavy metals for irrigation consumption is less than the WHO limit, while for drinking the average concentration of arsenic and cadmium is higher than the limit and is close to the specified range. According to the PoS index, 20% of the samples are highly contaminated and 47% are highly contaminated. The results of MI index showed that 34% of the samples are in the range of low and medium pollution. Be. Agricultural and industrial activities along with non-compliance with environmental issues can have an adverse effect on water quality in the region, while the main water pollution in the region can be considered due to improper use of fertilizers and pesticides and inadequate drainage of agricultural activities.

Supplementary irrigation in rainfed agriculture causes the increasing of crop yield and better using of water resources. The objective of this research was to investigate the effects of using of unconventional saline waters on supplementary irrigation of rainfed barley. The treatments included a rainfed (D) treatment and four water salinity levels with EC of 0.5 (S0), 6.7 (S1), 8.7 (S2) and 12 (S3) dS.m-1. When the barley grains filling, was performed the once spring irrigation based on deficiency of soil moisture. The yield amounts in D, S0, S1, S2 and S3 treatments were measured equal to 4005.8, 6449.08, 4918.32, 4260.08 and 3063.72 kg. ha-1 (biomass yield), 1973.18, 3174.16, 2438.48, 2112 and 1651.32 kg. ha-1 (straw yield) and 2032.62, 3227.92, 2479.84, 2148.08 and 1412.4 kg. ha-1 (grain yield), respectively. The results showed that for one dS.m-1 increasing of water salinity in supplementary irrigation, biomass, straw and grain were decreased (relative to rainfed), equal to 7.2%, 6.7% and 7.7%, respectively. Therefore, supplementary irrigation of barley up to salinity level of S2, was recommended for rainfed cultivation conditions. Also, water productivity in D, S0, S1, S2 and S3 treatments were calculated equal to 1.941, 2.618, 2, 1.73 and 1.243 kg.m-3, respectively. Typically, water productivity in rainfed agriculture is more than irrigated crop cultivation. However, the results of this research showed that in supplementary irrigation of barley up to salinity level of S1, the amount of water productivity will be more than rainfed cultivation conditions. Therefore, in addition of quality water, the using of saline water (at the crop tolerance level) for supplementary irrigation of barley, causes the increasing of crop yield, food security and optimal management of water resources.

Water Scarcity is one of the main problems for crop production in arid and semi-arid climates of Iran. In this study, in order to investigate the effect of two types of irrigation management on yield and growth indices of silage maize in arid and semi-arid climate, an experiment in the form of split-strip plots based on a randomized complete block design with three replications was conducted. The main factor included four levels of irrigation, supplying 120, 100, 80 and 60% of maize water requirement (I2, I1, I3 and I4) and the sub-main factor included two types of irrigation management: pulsed (P) and continuous (C). Experimental results showed that pulse management increased leaf area index, crop growth ratio, net assimilation ratio and relative growth ratio in I2, I1 and I3 treatments in the silk stage, while in I4 treatment due to the increasing intensity of water stress, reduced growth indices. The highest fresh and biological yield of silage maize was in PI2 treatment that was 29% higher than CI1 treatment. According to the results, in regions faced with water scarcity, by applying PI3 treatment, we can achieve a performance similar to CI1 treatment and save 20% of water consumption.

One of the most important and complex challenges facing Iran is the abuse of water due to its wrong valuation. In this regard, reforming the pricing system based on the economic value of water, as one of the most efficient tools of demand management, helps to regulate the water consumption pattern. This study tries to create a hypothetical market for Mashhad citizens in 2020, using the contingent valuation method (CVM) and logit model, to estimate the willingness to pay and investigate the factors affecting the public preferences of the economic value of water. The results show that the willingness of citizens to pay for each cubic meter of excess water has a negative relationship with the water bill per capita, household size and the bid variables and has a positive and significant relationship with the level of education. Also, the results show that the household size and ethical individuals variables had the greatest elasticity and impact on the willingness to accept an increase in the amount of water bill. The results also indicate that the average water consumption of Mashhad citizens for each household (average dimension of 3 people) is equal to 23.41 cubic meters per month and monthly willingness to pay of each household is equal to 14631.52 Rials per cubic meter of agricultural excess water. The results can be the basis of true pricing of water, get offenses related to water abuse, Detailed explanation of step-by-step payments, and finally targeted receipts are in line with the development of the country's water industry.

Wheat is a strategic crop in Iran. One of the main threats to wheat production in Iran is the decrease in the quantity and quality of water resources. In arid and semi-arid regions of Iran, more than 90% of wheat production is done through irrigation. Therefore, improving water use efficiency (WUE) in wheat production is essential. One of the basic ways to increase water use efficiency in the agricultural sector is to estimate the amount of water consumed at different stages of production. The water footprint suggests a new method for assessing the use of water resources in agricultural production. Therefore, the purpose of this study is to investigate the water use efficiency of wheat-based on the concept of water footprint. therefore, the water footprint of wheat production was calculated using the Hoekstra and Chapagain (2012) framework, the data envelopment analysis (DEA) method was used to calculate efficiency, and the fair ranking method (FRM) was used to determine efficiency rating. The study area of this research is Sistan and Baluchestan province and the research period is the crop year 1397-1398. The results of the water footprint showed that on average, 1415.8 m3 of water is consumed to produce one ton of wheat in Sistan and Baluchestan province, of which 83% of the total water consumption was through the use of groundwater and surface water and 17% through rainwater. The total water consumption for wheat production is 171.03 million m3. The highest water consumption was related to Zahak, Zabol, Delgan and Iranshahr cities and the lowest water consumption was related to Chabahar, Saravan, Zahedan and Sarbaz. DEA results showed that the average efficiency in wheat water consumption in Sistan and Baluchestan province is 50.92% that Khash and Delgan with an efficiency score of 1 were among the efficient cities.