جستجوی مقالات مرتبط با کلیدواژه « نیاز آبی » در نشریات گروه « آب و خاک »

Evapotranspiration variations (ET0) were investigated and analyzed using Minitab16 software for the 2010-2019 period using the Nizab system's data in Yazd province, and then ET0 was predicted until 2027. Based on the results, the increase of ET0 in cities of Yazd province was affected by the enhancement in wind speed and weather temperature, and the decrease in relative humidity from 2010 to 2019. To determine the appropriate model, Ardakan, Abarkooh, and Taft cities were selected as a representative in each climatic group, and ET0 data for the years 2010 to 2015 were considered as the input data of the software and ET0 data for the years from 2016 to 2019 were used to validate the determined model. The prediction of the determined models showed an increasing trend of ET0 for cold seasons in Ardakan and Abarkoh by 2027. Also, the model prediction showed a decreasing trend of ET0 for hot seasons in Taft by 2027. Also, the ET0 will not change significantly in cold seasons. In Abarkoh and Ardakan cities, autumn-spring crops such as wheat and in Taft city, spring-summer crops such as sunflower will be more affected by ET0 variations.

Salinity stress causes reduction of crop evapotranspiration (ETc) and yield. An unsuitable seed planting date can result in negative atmospheric effects, such as temperature stress, during the crop growth period. Consequently, salinity stress and unfavorable climatic conditions during this period interact to reduce crop water uptake. The mentioned conditions effect, should be investigated on crop transpiration amount (actual water requirement) and soil surface evaporation losses. This research results will have a determinative effect on the optimal use of water resources.

The studied crop in this research was S.C 704 maize. The crop planting was conducted in mini-lysimeters with a diameter of 40 cm and a height of 70 cm. The experiment factors included soil salinity stress and seed planting date. Soil salinity treatments were selected at four levels of 1.7 (S1), 2.5 (S2), 3.8 (S3), 5.9 (S4) dS.m-1. Seed planting date included of 5 May (P1), 25 May (P2) 14 June (P3) and 4 July (P4). Crop growth period for all planting date treatments, was 140 days (FAO-56). Experiment was conducted as factorial based on completely randomized design with 16 treatments and three repetitions. Variance analysis and average comparison of data was done by SPSS software and with Duncan's multi-range test (at 5% probability level). Daily soil moisture amount was measured by a moisture meter. Irrigation time was determined for without water stress conditions. Readily available water limit was determined 0.4. Irrigation volume was calculated according to soil moisture deficit (up to FC limit), soil density, root depth, leaching fraction and soil surface area. To separate the evapotranspiration components, all treatments were performed in two series of mini-lysimeters. In the first series, soil moisture reduction was related to crop evapotranspiration amount. But in the second series, the plastic mulch was placed on soil surface. Soil moisture reduction in the second series, was only related to crop transpiration amount. Difference of data in the first and second series was equal to the evaporation amount. Linear function of Mass and Hoffman (1977) was used as the function of evapotranspiration-salinity, transpiration-salinity, and evaporation-salinity.

As salinity increased from S1 to S4 levels, evapotranspiration, transpiration, and evaporation amounts were measured on the planting dates P1, P2, P3, and P4. The measurements were as follows:Evapotranspiration (mm): 619-548 (P1), 621-549 (P2), 624-547 (P3), and 625-544 (P4) Transpiration (mm): 429-309 (P1), 421-295 (P2), 418-281 (P3), and 412-265 (P4) Evaporation (mm): 190-239 (P1), 200-254 (P2), 206-266 (P3), and 213-279 (P4) These ranges reflect the measured amounts for each variable under increasing salinity levels across the different planting dates. Under the influence of salinity stress, soil water potential decreases, leading to a reduction in water uptake by the crop and subsequently decreased crop transpiration. As a result of this reduction in crop water uptake, the remaining water in the soil is utilized for evaporation. In S4 level and on dates of: P1, P2, P3 and P4, crop transpiration portion decreased to 12.9%, 14.1%, 15.6% and 17.2%, respectively, and evaporation portion increased to the same amount. By adjusting the seed planting date to optimize the utilization of favorable atmospheric conditions during crop growth stages, the increase in the portion of evaporation is prevented. In initial stage of growth period, only 0 to 10% of soil surface is covered by crops (FAO-56) causing the evaporation component to have a dominant portion in the crop evapotranspiration parameter. As a result, placing of initial growth stage in warm days of year caused an increase in evaporation losses. It seems that S1P1 treatment was the optimal condition for transpiration increase and evaporation decrease. The estimated functions showed that (in salinity stress conditions) crop transpiration decreased more than ETc. Therefore, the transpiration rate should be considered as the crop's net water requirement instead of ETc (crop evapotranspiration). According to the Mass-Hoffman function, under stress conditions, the decreasing slope of transpiration and evapotranspiration and the increasing slope of evaporation become more pronounced. For instance, in planting dates of P1, P2, P3, and P4, for each unit (dS.m-1) of increase in soil salinity, the evapotranspiration rates decreased by 2.51%, 2.82%, 3.3%, and 3.65%, respectively. Similarly, the transpiration rates decreased by 6.1%, 7.34%, 8.42%, and 9.2%, respectively, while the evaporation rates increased by 5.5%, 6.7%, 7%, and 7.82%.

Salinity and atmospheric temperature stresses had interaction effects on evapotranspiration and components rates. Postponing the seed planting date and not utilizing optimal weather conditions, especially during spring, can lead to damage to transpiration, which is a favorable aspect; however it is unfavorable in evaporation,. Therefore, in irrigated crops, it is advisable not to plant seeds during the warm months of the year, especially in July and August. Consequently, by controlling soil salinity and selecting the appropriate planting date, water can be optimally utilized.

The constraints of water resources and the imperative to enhance water efficiency in the production of vegetables and summer crops, on one hand, along with the economic importance of cucumber production in the country, on the other hand, reveal the necessity of investigating management indicators in cucumber production. The present study was conducted on a national scale with the objective of directly determining the applied water and water productivity indices in cucumber production fields across the country during a single crop year (1399-1400) in more than 180 selected farms, including about 70% of the cultivated area of cucumbers in the country. The results of the study revealed a highly significant disparity in various parameters among the selected provinces, including the volume of irrigation water, applied water (the sum of irrigation and effective precipitation), yield, and water productivity indices. The volume of applied water for cucumber cultivation exhibited notable variation, ranging from 4158 m3/ha in Hormozgan province to 8898 m3/ha in Razavi Khorasan province. The weighted average of applied water volume was calculated to be 7043 m3/ha. Similarly, the average yield of cucumbers displayed considerable diversity, ranging from 12750 Kg/ha in Zanjan province to 32956 Kg/ha in Razavi Khorasan province. The weighted average yield stood at 25219 Kg/ha. The calculated water productivity indices for both irrigation water and applied water were 4.27 Kg/m3 and 4.20 Kg/m3, respectively. Notably, the province with the lowest applied water productivity was Zanjan (2.21 Kg/m3), while the highest was observed in Fars province (6.59 Kg/m3). Based on the results, the total water requirement for cultivating cucumbers across an area of 55000 hectares in the country was estimated to be 330 MCM.

Water is one of the most important resources needed by human society and the first and most important factor for the production of agricultural products, more than 90% of this vital liquid is consumed in this sector. One of the most important factors that affect the performance of a water conveyance and distribution network is the water distribution and delivery program. In order to obtain turnouts’ discharges, the water requirement of the eastern Aghili area was estimated using the Global Land Data Assimilation System (GLDAS) and controlled using the results of the NETWAT model. For this purpose, three-hour evapotranspiration was estimated with GLDAS, and the six-hour discharges of turnouts were calculated according to the cultivated area of each turnout and irrigation efficiency. The hydraulics of the eastern Aghili canal were simulated using the above-mentioned data for six hours. The results showed the appropriate accuracy of GLDAS so that at a maximum of 12.7%, GLDAS underestimated the evapotranspiration values compared to NETWAT. The minimum values of efficiency and adequacy indicators of 0.95 and 0.94, respectively, were obtained, which are in the "good" performance class.

In recent decades, the use of groundwater for irrigation, drinking, and industry has increased in developing countries such as Iran. This increase, in turn, improves food security and reduces poverty in these areas. However, reducing the level of the water table and sustainable development are concerns. These concerns have increased, especially regarding the alluvial aquifer of the Ajabshir plain, which plays a significant role in providing water in the area. Considering the growth of the population and the water needed, it is very important to study the water quantity and quality for the future and the well deepening. There are several methods to determine the maximum depth of deepening. However, this study emphasizes the fluctuations of the groundwater level as a result of them instead of the relatively complex studies of modeling and water balance. For this purpose, after collecting the data, the maps of the groundwater isodepth, isolevel, fluctuations, and aquifer bedrock were drawn in the GIS software. Then, the unit hydrograph of the plain was prepared to determine the amount of groundwater level drop. Population growth and water demand were determined for the horizon of 1420. The findings of this research indicate that the overexploitation of groundwater resources will have consequences such as a drop in the groundwater level (equivalent to 6 m), a decrease in the quality of the groundwater, and subsequent land subsidence. The minimum level for well deepening in the Ajabshir aquifer varies between 1250 meters and 1290 meters.

Because safflower contains more than 90% of unsaturated fatty acids, it can play an important role in expanding the area under cultivation of oilseeds and providing oilseeds in the country. Considering the lack of water and the need to investigate the behavior of the safflower plant in low irrigation conditions, it is necessary to have a proper estimate of its performance under water stress conditions. This oilseed plant needs areas with little winter and spring rainfall during the flowering period and is drought tolerant and has long roots with a high ability to absorb water from deeper soil profiles.

In order to estimate the yield production function and yield components of safflower plant variety Sina under water stress conditions, an experiment was carried out in a research farm located in Kermanshah province. This research was conducted using the data collected in two crop years in a research farm in Kermanshah. The yield response factor was implemented at three levels of 70, 60 and 30% of water requirement based on soil moisture balance in three iterations. Based on the data of the first year, the two production functions of Raes and Tafteh, yield response factors of the plant were determined and evaluated using the data of the second year. To calculate the growth degree day (GDD), two methods of direct calculation and modified average were used. The maximum possible temperature for growth is about 30 degrees and the minimum temperature for growth is 0 degrees as the recommended and acceptable low limit (no trend). In this research, the maximum value of 30 degrees and the base temperature value of 4 degrees were taken from the water requirment system database(niwr.ir). Then different periods of phenology were calibrated with this index. Also, the relationship between GDD index and transpiration evaporation coefficients and yield response factors and irrigation requirement were investigated.

The findings showed that the yield response factors of safflower plant to water stress varies between 0.5 and 1.2 in different growth periods and the highest sensitivity is in the flowering period and the middle period of this plant. Also, the results of the investigation of the two production functions showed that the values of the statistical indicators for both functions are the normal error value of 5% and the efficiency value of both functions is about 97%. The results show that the lowest average evapotranspiration in different treatments was related to the 30% water requirement treatment with 189.8 mm and the highest was related to the 100% water requirement treatment with 632.7 mm.

Based on the obtained results, the Sina safflower plant is most sensitive to dehydration in the middle and flowering stages, and the yield response factors reaches its maximum in this stage (about 1.2) and water stress is not recommended at this stage. On the other hand, Rees and Tafteh function with the presented yield response factors can estimate the results with acceptable accuracy in water stress investigation based on the presented coefficients. On the other hand, in the absence of plant data and complete meteorological data, only by using the GDD index can evaluate the values of plant coefficient and plant sensitivity to water stress and plant irrigation requirement  with appropriate accuracy.

Due to the limitation of water resources, proper use of water is necessary, and the use of appropriate irrigation methods in fields is an appropriate strategies to use water. Water stress can affect crop yield in the field. Therefore, the correct method of irrigation and management of water consumption is one of the basic issues in farms. The deficit irrigation strategy with the water requirement supply approach can be considered as a practical and efficient technique to ensure more crop yield, without compromising the physiological processes and yield. Therefore, the scope of this research is to estimate the amount of water consumed and the amount of evapotranspiration of the bean plant with the aim of evaluating the field conditions and comparing it with Tafteh, Pasquale and Raes methods.

The present study aims to determine the amount of water use and evapotranspiration of bean using Tafteh, Pasquale and Raes methods and based on the inverse solution of the yield production function in Markazi Province and at the Khomin Bean National Research Station at an altitude of 1930 meters above sea level with a length of 49 degrees and 57 minutes of latitude and 33 degrees and 39 minutes of latitude were implemented in 2016 and 2017. In this experiment, the irrigation treatment including furrow and drip-tape as the main factor and, the values of water requirement including 100, 75 and 55% of water requirement as a sub-factor and in the form of split plots in the form of randomized complete blocks design were done in three replications. Cultivated variety was of native type and its planting time was on the 10th and 9th of June respectively in the first and second year. Drip irrigation tapes were placed on the stacks and irrigation was carried out in the same way until the seedling was fully established in the stage of emergence of the third three leaves.

The highest seed yield with an average of 2683 kg/ha was obtained in the furrow irrigation method and by providing 100% of the water requirement. In evaluating evapotranspiration, the root mean square error (RMSE) in Tafteh, Pasquale and Raes methods were 0.160, 117.8 and 0.185 mm respectively and the root mean square normal error (RMSEn) were 0.448, 0.330 and 0.518 percent respectively. The index of agreement or compatibility (d) in Tafteh, Pasquale and Raes methods were 0.295, 0.600 and 0.081% respectively. In the investigation of irrigation water amounts, the root mean square error (RMSE) in Tafteh, Pasquale and Raes methods was 156.7, 117.5, and 181.3 mm, respectively, and the root mean square normal error (RMSEn) was 0.446, 0.335 and 0.516 percent respectively. The index of agreement or compatibility (d) in Tafteh, Pasquale and Raes methods were 0.324, 0.602 and 0.118% respectively.

In general and according to the statistical results, Tafteh, Pasquale and Raes methods had an acceptable estimate of the amount of irrigation water and the amount of evapotranspiration in the furrow and drip conditions under different amounts of water requirement. Therefore, they can be used as appropriate tool in the estimation of water use in the studied area.

For reduction of water deficiency effects in agricultural sector, it is needed to management of optimal water consumption. Irrigation scheduling should be based on the actual water requirement during the crop growth period. So that the crop growth stages sensitivity is considered in the water uptake process. The application of water uptake reduction functions (α(h)) in water stress conditions, is one of methods for irrigation scheduling. In past researches, the calibration and evaluation of water uptake reduction functions have been done by constant coefficients in the crop growth period. But the aim of this research, is to compare the water uptake reduction functions by application of constant and separate coefficients, in crop growth stages. Therefore, the accuracy of estimation of actual α(h) data, is investigated in crop growth period. This research was conducted on maize S. C 704, in Qazvin region. The mini-lysimeter with diameter of 40 cm and height of 70 cm was used for crop cultivation. The main factor was defined as soil water depletion at levels of 45%(I1), 55%(I2), 60%(I3), 65%(I4), 70%(I5), 75%(I6), 80%(I7) and 85%(I8), relative to total available water. Sub main factor was selected as the sensitivity to water stress in growth stages of initial (P1), development (P2), mid (P3) and late (P4). So that, the effect of soil water depletion (water stress) on water uptake amount, was investigated in maize growth stages (as separately). The experiment was performed as factorial and in a completely randomized design, with 32 treatments and three repetitions. Daily soil moisture was measured by moisture meter (HH2 model and made by ΔT company). For simulation the water uptake reduction (in water stress conditions), were applied the models of Van Genuchten (1987), Dirksen et al (1988) and Homaee et al (2002). The actual data of α(h) in I1, I3, I5 and I7 treatments, were used for models calibration. For this work, the models coefficients were estimated constantly (in whole growth period) and variably (in 4 growth stages). The models evaluation were performed for estimation of α(h) actual values in I2, I4, I6 and I8 treatments. The statistics indicators of CRM, EF, R2, RMSE and ME were used for models evaluation. The effect of soil water depletion and crop growth stages sensitivity on water uptake, was significant at the level of 1%. From I1 to I8 treatments, the water uptake amount in the whole of growth period, was decreased by slope of 7.4%. But the water uptake amounts in the initial, development, mid and late stages were decreased to 5%, 6.9%, 9% and 4.6%, respectively. As a result, the most sensitive growth stage of maize (relative to water stress) was included the mid, development, initial and late, respectively. The models calibration showed that in a specific model, the function coefficients amounts were different in growth stages (compared to whole of growth period). The best priorities for optimal model choosing, was assigned to application of separate coefficients in the crop growth stages. Among the different models, the Van Genuchten model with statistical indices of CRM=0.032, EF=0.928, R2=0.942, RMSE=0.057 and ME=0.1, was determined as the optimal model. The results of this research showed that the modeling accuracy was increases, by application of variable coefficients in water uptake reduction functions. Due to different sensitivity in crop growth stages, is done a better estimation of actual water uptake amount, in water stress conditions. As a result, the actual crop water requirement is calculated by more accurately. Also, the water consumption amount is considered according to actual crop needs, which will cause to better management of water resources.

In Iran, pressurized irrigation systems cover a large area of agricultural land, but water use efficiency remains low because farmers tend to do deficit (over) - irrigation due to their lack of knowledge of crop water requirements. To address this issue, irrigation systems can be automated, and it is important to estimate crop water requirements accurately. This can be done based on soil moisture deficit or meteorological data. The water required can then be applied using a volume meter or by determining irrigation time based on the sprinkler flow rate. The study aimed to compare crop water requirement estimates based on soil moisture deficit and meteorological data, as well as the amount of water applied using volume and time-based methods.The study was conducted in the research farm of Razi University, Kermanshah, Iran, on a sprinkler irrigation system equipped with pressure and flow measuring devices, pressure switches, and electrical valves. The field was under corn cultivation, and four types of irrigation management were evaluated, which included a combination of two methods of determining crop water requirement (soil moisture deficiency and meteorological data) and two methods of irrigation application (time or volume). The four treatments were soil moisture - time (MT), soil moisture - volume (MV), weather - time (WT), and weather - volume (WV). The crop water requirement was calculated using the Penman-Monteith formula based on daily weather data. Soil moisture was measured at different depths one day before irrigation, and the soil moisture deficit was calculated to determine the crop water requirement based on soil moisture. The irrigation volume for each sprinkler in the irrigation cycle was calculated using equations that written in the paper.In the volumetric-based method (treatments WV and MV), the volume of water applied was measured using a water meter with a precision of 0.1 liters, and irrigation was stopped after passing the required volume of water. In the time-based method (treatments WT and MT), the irrigation time was calculated by dividing the irrigation volume by the average flow rate of the sprinklers (3 liters per second), and irrigation was stopped after the calculated duration. The actual sprinkler flow rate was calculated based on the volume of applied water and irrigation time in each treatment and irrigation round. Crop yield was measured at the time of harvest in the studied treatments and a control treatment managed by the Faculty of Agriculture. The irrigation treatments were not applied in the first month of the growth period due to field limitations.The results show that the crop water requirement calculated based on meteorological data at the beginning and end of the growing period was more than the method based on soil moisture. In total, the amount of crop water requirement calculated based on soil moisture was 8% more than the meteorological-based method. The volume of applied water in treatments of MT and WT was 14 and 8% more than in MV and WV treatments, respectively.The actual flow rate of sprinklers was different from the design flow rate due to irrigation situations in other parts of the farm. The average discharge of sprinklers (12 irrigation events) in WT, MT, WV, and MV treatments was 2.79, 3.03, 3.27, and 3.12 l/s, respectively. The irrigation time in volume and time-based methods also showed a significant difference. The irrigation time in MT and MV treatments was 10 and 18% longer than in WT and WV treatments, respectively. The study found that due to the non-uniformity of sprinkler discharge, applying irrigation by volume method is better than the time-based method. The results suggest that the MV treatment, which determined the amount of irrigation based on soil moisture deficit and applied it using a volumetric method, is a suitable option for automating sprinkler irrigation systems in the studied region.

The deficit irrigation method with the aim of saving water consumption can be presented as a useful strategy in low water conditions and with the proper use of the amount of water consumption. Optimum use of water and proper use of fertilizer, in addition to increasing plant yield, increases the water productivity and fertilizer. Nitrogen is one of the main elements in plant nutrition, because of its importance in the plant's vital processes; its deficiency reduces performance more than other elements. The present research was conducted with the aim of investigating the effect of water stress and different levels of nitrogen fertilizer on the yield and productivity of Williams cultivar soybeans in Hormozgan province.

This experiment was conducted in the form of split plots in the form of randomized complete blocks in three replications in Hajiabad city (Hormozgan province) in two crop years 2021 and 2022. The main factor was irrigation in 6 levels without irrigation and providing 40, 60, 80, 100 and 120% of water requirement and the secondary factor was the amounts of nitrogen fertilizer (urea source) in four levels including zero, 50, 100, 150 and 200 kg/ha. Each experimental unit had dimensions of 5×20 m2 and had 10 cultivation rows.

The interaction effect of irrigation and nitrogen fertilizer on biological, pod and seed yields, harvest index, thousand seed weight, number of seeds per plant, pod length, water consumption efficiency in biological, pod and seed were significant at 1% level. The interaction effect of irrigation and fertilizer showed that the highest amount of biological, pod and seed yields in the conditions of 100% water requirement and 150 kg N/ha consumption were 6051, 4941 and 3049 kg/ha respectively. The maximum harvest index due to the interaction effect of irrigation and nitrogen fertilizer was in the conditions of 100% water requirement and with 100 and 150 kgN/ha fertilizer with an average of 0.43%. The interaction effect of irrigation and nitrogen fertilizer showed that the maximum thousand seed weight was with 120.8 g in the condition of 100 percent water requirement and fertilizer consumption of 200 kg/ha. The highest efficiency of water consumption based on biological, pod and seed yields were observed in conditions without irrigation and 150 kg N/ha in the amount of 5.61, 3.71 and 2.28 kg/m3 respectively.

According to the results, the availability of water and sufficient nitrogen are two very important factors that affect the growth and yield of soybean. Therefore, in addition to the lack of water, the lack of nitrogen also causes stress on the growth and yield of soybean. With the upward trend of nitrogen fertilizer consumption, the yield decreased and if there is not enough water, the increase in nitrogen fertilizer consumption aggravates the effect of moisture stress and as a result the yield of the plant decreases, therefore, in water shortage conditions, Excessive use of nitrogen fertilizer is not recommended. According to the results, full irrigation and nitrogen consumption up to 150 kg/ha are suggested for the studied area.

Different factors are effective in increasing wheat production, one of the most important of which is water. Determining the actual consumed water of wheat in arid and semi-arid regions is of particular importance and the economic use of water is a serious and very important issue for farmers and researchers who cultivate and produce wheat under irrigation. The season of wheat cultivation has a direct effect on its water requirement due to the change in the energy pattern affecting evapotranspiration, and it will definitely have a lower water requirement in winter than in spring and summer. Therefore, the present study was conducted in order to investigate the water requirement system in determining the actual amount of irrigation water and wheat plant yield based on the inverse solution of the production function under water stress conditions for Alvand variety wheat in Qazvin province.

The research was conducted in 2017-2019 crop years in Qazvin province on a land of 600 square meters in Esmailabad research station (49º 52' N, 36º 15' E, 1285 MSL). The experimental design was in the form of split plots and in the form of a randomized complete block design with three replications. So that the main factor of irrigation management includes providing water requirements of 20 (I1), 40 (I2), 60 (I3), 80 (I4) and 100 percent (I5) and secondary treatment includes irrigation until the end of the flowering stage (S1) and The pulping of the seed was (S2). The country's using NIAZAB system was provided by the Soil and Water Research Institute (SWRI). This system is designed to determine the water requirement of farmland and Orchard products, which has the ability to estimate and determine the water requirement, Consumed water and plants irrigation planning at the level of the region, city, catchment and plain. One of the prominent points of this system is its location-based nature, and the user can extract their regional needs by referring to the system and can allocate the water used for the cultivation pattern under different usage options to the beneficiaries of the agricultural water stakeholder with the ability to provide an update.

The results showed that the root mean square error in Tafteh, Pasquale and Raes methods was 122, 83 and 126 mm per day, respectively, and Pasquale method had a better estimation than other methods. In Pasquale's method, the best normalized root mean square error was observed with 0.18%. The index of agreement or consistency in Tafteh, Pasquale and Raes methods was 0.95, 0.98 and 0.95%, respectively, and the Coefficient of Efficiency of the model was 0.77, 0.91 and 0.73, respectively. The results of the statistical analysis showed that the measured and simulated values are close to the 1:1 line and have a good relationship, and the coefficient of determination values in the studied years showed 0.98. The results of estimation the amount of wheat plant evapotranspiration in the using NIAZAB system in the Qazvin plain with the methods of Tafteh et al. (2013), Pasquale et al. (2017) and Raes et al. (R2=0.98) were high and the root mean square error in Tafteh, Pasquale and Raes methods was 120, 83 and 126 mm per day, respectively, in which Pasquale's method had a better estimation than other methods.

In general and according to the statistical results, a good approximation was observed between the real data and the using NIAZAB system in determining the amount of irrigation water under water stress conditions, which indicates the appropriate evaluation of the water requirement system and the ability to simulate the wheat yield function in relation to different treatments. It was irrigation and this system can be used as a suitable tool in estimating water needs to improve water management in wheat.

The lack of water resources and increase in water demand are among the effective factors in the imbalance of the water resources in each region, and it is necessary to manage the proper use of available water resources in all activities. Water in the agricultural sector is one of the main factors of production, which should be conveyed by irrigation systems to the field level and made available for the plant roots. The necessity of macro-planning in water management and consumption imposes a comprehensive study of the amount of water consumed in the agricultural sector. Hence, this study was conducted with the objective of directly measuring and field-assessing the applied water, water productivity, and water footprint associated with the primary crops cultivated in Markazi Province, all managed by local farmers.

For this purpose, 141 farms were selected in the major production areas of the main agricultural and horticultural crops of Markazi province with the coordination of the Agricultural Jihad centers. Then, the volume of water applied was measured without interfering in the irrigation scheduling of the users. To do so, first, the flow rate of the water source (canal, well, aqueduct or spring) was measured with a suitable device (flume and meter) in each of the selected farms. Then, by carefully monitoring the irrigation schedule of the farm, including the time of each irrigation, the number of irrigation throughout the year, as well as measuring the area under crop cultivation, the amount of water used by the crop was measured for each of the selected farms during the season. Also, based on the measured data, the amounts of blue, green and gray water footprints were determined for each of the examined crops. For this purpose, the blue, green and gray water footprints of different crops were calculated using the framework provided by Hoekstra and Chapagain (2008), and Hoekstra et al., (2011).

The irrigation intervals in the studied fields varied between 3 and 15 days with an average of 8 days and the average irrigation depth varied between 26.2 and 99 mm with an average of 67.8 mm in different crops. The results showed that the average volume of applied water for the studied crops in Markazi province was 10782 cubic meters per hectare. Also, the minimum and maximum amount of applied water for the evaluated crops was as follows: barley 3783 and 7232, alfalfa 10382 and 19797, beans 8280 and 17840, watermelon 5333 and 7174, walnuts 4420 and 29600, almonds 3850 and 13932, peaches 6872 and 17727, cherries 7050 and 14645, pomegranates 7156 and 20790, and grapes 5937 and 18168 cubic meters per hectare. Furthermore, the average value of irrigation water efficiency index and water footprint was as follows: barley 0.46 and 1642, alfalfa 0.92 and 700, bean 2924 and 0.24, watermelon 9.37 and 117, walnut 0.1 and 6706, almonds 0.16 and 6857, peach 2.48 and 242, cherries 0.73 and 875, pomegranates 1.33 and 636, and grapes 11.2 and 322. Based on the obtained results, the average total water footprint index was equal to 2102 cubic meters per ton. On average, the almond with a water footprint of 6857 cubic meters per ton had the highest share in allocating the water footprint in the crop production of the province. Whereas, the lowest water footprint related to the watermelon with a water footprint of 117 cubic meters per ton. he average values of the irrigation application efficiency index, irrigation water productivity, and water footprint for the examined farms were 72.5%, 1.79 kg/m3, and 2,102 m3/ton, respectively. In summary, the results indicate that the combined volume of irrigation water and beneficial rainfall in the irrigated fields within Markazi Province surpasses the actual water demand of the crops. This underscores the substantial impact of irrigation management on water utilization in the region.

On average, the total volume of irrigation water and effective rainfall in irrigated fields and gardens in Markazi Province is more than the actual water requirement of the plant. In general, the results showed that irrigation management has a great impact on the amount of water use in the region. Based on the obtained results, considering that most of the farms and gardens receive water in an intermittent manner, in principle, no special attention is paid to the need for water and even effective rainfall, and the amount of water availability has the greatest impact on water consumption. Therefore, in order to reduce water consumption and improve water efficiency, it is suggested to manage the delivery of water to farmers during the season and according to their crop water needs. Also, the results of the water footprint can be used to improve water resource policies at the province level, land use studies, cropping pattern modification, and environmental sector policies.

Crop water productivity (CWP) is defined as the crop yield produced per unit of water consumed, which can be improved by increasing the crop yield with a given water usage or reducing water usage with a given yield. Increasing CWP can thus help to alleviate the water crisis while ensuring food security. Physical productivity alone is not enough to determine the crop pattern and economic productivity should also be considered. Economic water productivity (EWP) expressed as the gross income in USS per unit of water consumed, is relevant for farmers to pursue higher net benefits. Both CWP and EWP terms are important indices for water resource managers to consider when formulating planning policies. The simultaneous consideration of CWP and EWP allows for a more comprehensive and robust exploration when planning the process for developing regional agricultural water-saving measures, such as modifying the regional cropping distribution. This allows farmers to reduce irrigation water use and shift the area of water-intensive crops to ones with efficient water use or higher economic value. Determining crop pattern-based water productivity is especially important in countries with dry climates, whose agriculture depends solely on irrigation and also has low water consumption efficiency. Therefore, instead of consuming scarce water resources, in the production of products that consume a lot of water, it is possible to produce products with lower water consumption and avoid excessive pressure on water resources. Knowledge of crop-water requirements is crucial for water resources management and planning to improve water-use efficiency. Crop water requirements in the growing period depends on the crop growth stage, cropping technique, and irrigation method. About 99 % of the water uptake by plants from soil is lost as evapotranspiration (ET), so, it can be stated that the measurement of actual crop evapotranspiration (ETc) on a daily scale for the whole vegetative cycle is equal to the water requirement of the given crop. Evapotranspiration is defined as the water lost as vapor by an unsaturated vegetative surface and it is the sum of evaporation from soil and transpiration by plants. Knowledge of the exact water loss through actual evapotranspiration is necessary for accurate and effective water management.

For this purpose, in the first stage agricultural condition of the aquifer was investigated through a questionnaire by farmers and experts. To calculate the reference crop evapotranspiration we used the Penman-Monteith equation in this study crop coefficient curves have been prepared according to the agricultural calendar of the Basht aquifer. Net water requirement is calculated from the difference between effective rainfall and evapotranspiration. Water productivity per crop ( ) (kg.m-3) is an important index for determining the agricultural production system efficiency. Water productivity is defined as the proportion of crop yield (kg.ha-1) to irrigation water consumed by crops in the field (m-3.ha-1). Likewise, water economic productivity is measured about or with the economic benefits in a monetary value of outputs over the number of necessary inputs such as water depleted. To calculate the value of each cubic meter of water, the production costs (minus the water) need to be deducted from the income and the remainder needs to be divided by the volume of water. The calculation results are calculated separately for each product. To determine the suitable pattern crop in Basht aquifer, different cropping patterns were evaluated (eight different scenarios).

Based on the results of the Penman-Monteith method, it can be concluded that the gross water requirement (the amount of net irrigation requirement divided by the irrigation efficiency) in dominant crops of aquifer including rice, alfalfa, citrus, watermelon, corn, wheat, rapeseed, legumes, barley respectively were 20234, 14083, 9291, 9170, 7863, 5630, 5411, 5225, and 4821 m-3 ha, respectively. The amount of effective precipitation that provided a part of the crop’s water requirement through soil moisture (green water) for water crops such as Rice and Corn is close to zero. Autumn crops such as canola, citrus fruits, and cereals use green water. To determine the amount of irrigation per hectare of the current crop pattern of the aquifer, the hydro module of each crop was determined. As it is clear from hydromodule, the average required water flow (l s-1 ha-1) for rice, alfalfa, citrus, watermelon, corn, rapeseed, wheat, beans, and barley, equaled 0.63, 0.44, 0.29, 0.29, 0.24, 0.18, 0.17, 0.16 and 0.15 (l s-1 ha-1) respectively. In total, the amount of water consumed by the agricultural products in the aquifer's Basht is 45 millm3, that approximately equivalent to one m3 m-2 of the aquifer cultivation area and this amount is much more than the aquifer agriculture programmable water. The economic productivity of the aquifer’s current cultivation is 45,000 IRR m-3, on average. Also, most aquifer products' physical productivity was less than one. the comparison of different patterns showed that scenarios eight and twohad the highest and lowest amount of water consumption, 45 and 22 millm3, respectively.

The crop pattern will be influenced by parameters such as climatic compatibility of products, water, and soil potentials, needs, interests of agriculture producers, and production income. In the Basht aquifer, the availability of water and the amount of water consumed is one of the most important factors in choosing the cultivation pattern. In the current situation, due to the high temperature and increasing evaporation rate, and the use of seasonal rainfall, crops that spend their growth period in autumn and winter should be included in the cultivation pattern. The simultaneity of water requirements for crops planted together is one of the important parameters in choosing the cultivation pattern. In the Basht aquifer, the water requirement of corn, alfalfa, cucumber, and tomatoes coincide with the citrus water requirement during the time of high water consumption, and the cultivation of one of them may create water limitations for the other crop. In contrast, the cultivation of wheat, barley, and canola have a very small overlap with the citrus irrigation times. Choosing a combination of citrus, wheat, barley, and canola will optimize the cultivation pattern.

Figs are one of the main horticultural products in Iran due to their high nutritional value, high yield and economic value, and resistance to adverse climatic conditions. About one million tons of figs are produced annually in the world, Iran is the fifth largest producer of this product in the world (FAO, 2018). In addition to the above, the agricultural sector in Iran, like many countries, is the main consumer of water from renewable water sources. But there are not exact information on the volume of irrigation applied water and water productivity of this product in Iran. Therefore, this study was conducted with the aim of measurement of applied water at field scale and evaluation of water productivity of figs orchards at selected provinces in Iran.

The purpose of this study was to assess irrigation management and determine water productivity in olive orchards managed by local farmers in the country. To achieve this, the amount of water provided by gardeners and the yield of 102 olive orchards that underwent irrigation using various methods, surface and drip irrigation, were measured across the provinces of Qazvin, Fars, Zanjan, Gilan, Golestan, and Semnan. This data was collected during two consecutive years, 2018 and 2019. Measured values were compared with NETWAT-estimated net irrigation requirements as well as Penman-Monteith-derived values. Based on the results, it can be concluded that the average volume of irrigation water, yield, irrigation water productivity, and applied water productivity in the selected provinces are significantly different at a probability level of 1%. According to the study, the volume of irrigation water used in olive orchards varied from 2848 to 11463 m3/ha, with a weighted average of 6011 m3/ha. The average yield of olives in the production poles of this product has varied from 1500 to 11000 kg/ha over the two-year period, and its weighted average has been 4867 kg/ha. It is also worth mentioning that the water productivity ranged from 0.2 to 2.40 and its weighted average was 0.95 kg/m3. Furthermore, the applied water productivity in the selected provinces ranged from 0.18 to 1.45 and its weighted average was 0.63 kg/m3. Upon evaluating the efficiency of irrigation in the olive orchards, it was observed that the quantity of water delivered was approximately 27% and 17% less in comparison to the irrigation requirement calculated using recent 10-year meteorological data and NETWAT, respectively. In other word, forced deficit irrigation has taken place in the olive orchards

According to the effects of climate change on evapotranspiration and using of water resources, climate change prediction is vital due to water resources management improvement and decreasing damages of drought. The first rank of mango production in Iran belonged to Hormozgan province and the most amount of mango produced in Minab plain. In the present study, the amount of evapotranspiration of mango plants was calculated with FAO Penman-Monteith from 1985 to 2020 using meteorological data at Minab station. The evapotranspiration values of the plant were estimated from 2021 to 2100 with two optimistic and pessimistic scenarios using the last version of CMIP (CMIP6), atmospheric-ocean general circulation models, and performing statistical deviation corrections by the Python software. The results showed that the values of annual evapotranspiration will increase by 0.31 and 1.23 mm on average in the optimistic and pessimistic scenario, respectively in the future due to the increase in annual temperature.

The objective of the present study was to conduct field studies for direct measurement of canola under farmers' management in one crop season (2019-2020) in 27 farms in Behbahan, Khuzestan province. Water requirement was calculated based on the FAO Penman-Monteith model using the daily statistics of the Behbahan synoptic meteorological station. A T-test was used to statistically compare the results such as the depth of irrigation and applied water productivity in the field in different irrigation systems. Linear multivariate regression analysis was used to investigate the effects of the independent variable on the dependent parameter of water productivity. The volume of applied water in the fields ranged from 4085.5 to 7865.3 m3/ha. The results of comparing the average yield of two irrigation systems in the t-test showed that the two sprinkler and surface irrigation systems with yields of 2614 and 2330 kg/ha, respectively, were not significantly different. Applied water productivity in traditional and modern irrigation systems was calculated to be 0.386 and 0.486 kg/m3, respectively, which had significant differences. The results of the analysis of variance in the regression model showed that among the independent variables, yield with t-statistic (23.997) and equivalent beta coefficient (0.880) had the most significant positive effect at a 1% level on applied water productivity. After that, the volume of applied water (irrigation water + effective rainfall) with a t-statistic of (-11.702) and a beta coefficient of equivalent (-0.793) had the most negative and significant effect at the level of 1% on the applied water productivity. The results of the Pearson correlation coefficient showed that irrigation events had a positive and significant correlation at a 5% level with applied water and yield. These correlations were 0.455 and 0.380, respectively. By increasing irrigation events, the volume of applied water has practically decreased and has become as close as the plant needs, and has increased water productivity.

About three quarters of the country's sweet lime orchards are located in Fars province. Having sufficient information on the amount of irrigation water and water productivity of these gardens can lead to better management of water resources and increase water productivity. In this research, the water productivity and the amount of water given in 60 sweet lime orchards in six regions of Fars province were measured during 2021. Among the selected orchards, due to differences in irrigation management, soil salinity and other factors, the volume of irrigation water varied from about 10000 to 24000 m3/ha per year. The average total volume of irrigation water was 14712 m3/ha. In terms of the regional average, the lowest and highest amount of irrigation water was related to Ghir-Karzin and Darab regions with 13023 and 17079 m3/ha per year, respectively. The productivity of irrigation water in selected gardens was between 0.71 and 2.23 kg/m3 and on average 1.40 kg/m3. Comparing the volume of irrigation water with the gross water requirement showed that in the year of conducting the research, these differences were statistically significant in Lar and Darab regions. In general, the average difference between the volume of irrigation water and the annual gross water requirement in the province was 569 m3/ha, which was not statistically significant. But on average, the volume of irrigation water was 2288 m3/ha more than the long-term gross water requirement, which was a significant difference. Therefore, it is necessary to apply irrigation scheduling and accurately determine the required water to increase the productivity of sweet lime orchards in Fars province.

By evaluating irrigation systems, their performance can be improved. The purpose of this study was to evaluate the center pivot irrigation system in some fields of Semnan province. Also, the amount of water consumption in the field was compared with the water requirement and the national water document. For this purpose, center pivot irrigation systems were studied in three fields. Average potential and actual application efficiency (PELQ and AELQ), distribution uniformity (DU), uniformity coefficient (CU) and evaporation and wind losses were 69.1, 67.2, 76.7, 82.1 and 7.6% respectively. The average of the above parameters was good. The operation of center pivot systems was easier than other sprinkler systems due to the mechanization of center pivot systems. Technical problems in one system reduced uniformity and efficiency. The volume of water consumption in field 3 was less than the irrigation requirement thus deficit irrigation was done. Irrigation water productivity in alfalfa and wheat fields was 0.92 and 0.79 kg/m3, respectively. Considering appropriate irrigation frequency and time, night irrigation to reduce evaporation and wind losses and paying more attention to educating farmers on proper operation of system were the important factors in increasing irrigation efficiency and water productivity.

Optimal cultivation patterns are necessary for the sustainable development of agriculture and the protection of land and water resources, and the need for it has deepened. In the context of sustainable agricultural development, the optimization of the cultivation pattern, in addition to the economic benefits, should also follow the subsequent environmental effects. Due to the limitation of water resources in different regions of the world, joint use of surface and groundwater has become very important. Optimizing the joint use of surface and groundwater has become a necessary contribution to sustainable irrigation methods, and due to this, there is a need to improve methods of joint use of surface and underground water. The purpose of this research is to use a new comprehensive structure of multi-objective simulator-optimizer in order to simultaneously formulate the optimal cultivation pattern and the optimal allocation of surface and groundwater resources for the integrated management of the water resources system and solving complex water resources problems.  

The study area in this research is Shahriar Plain in Tehran Province, Iran. Shahriar Plain is located on the western outskirts of Tehran city. In this study, a multi-objective simulator-optimizer modeling pattern was prepared and for this purpose, it was first simulated using the groundwater modeling system (GMS) of the groundwater level. Then six scenarios including a 50 % increase in artificial recharge, 50 % increase in artificial recharge and 30 % reduction in consumption from exploitation wells, 50 % increase in artificial recharge and 40 % reduction in consumption from exploitation wells, 30 % reduction in consumption from exploitation wells, 40 % The reduction of consumption from exploitation wells, elimination of drinking and industrial exploitation wells and its impact on the aquifer was defined based on the groundwater level in order to optimally exploit the aquifer of the study area. After this step, the groundwater level was estimated using the artificial neural network (ANN) model. Finally, the two objective functions of income to cost and groundwater level changes were estimated based on the constraints related to the conditions of the desired area by a multi-objective genetic algorithm (NSGA-II).

The GMS model in a steady state was calibrated. The RMSE error was 0.71 meters and the maximum and minimum differences between observed and calculated values were calculated as 1.73 and 0.001 meters, respectively. The maximum amount of yield water in the calibration stage of the unstable state is 0.0976 and related to the northern regions of the area and due to the coarseness of the alluvial formations in these areas, and its minimum value is 0.0003 and related to the southern regions of the area. The results obtained from the model showed the RMSE error at this stage and the verification mode equal to 0.72 and 0.98 meters, respectively. Also, the budget resulting from the third scenario of the GMS was estimated to be 203 (MCM), which has increased by 313 (MCM) compared to the budget resulting from this model in the water year 95, and has caused an increase of the groundwater level by 13 meters. Therefore, the model has adequately simulated the groundwater flow in the aquifer. Also, the results of the optimization model showed the highest amount of optimal irrigation demand for Eslamshahr district at 66%, then Shahriyar at 20%, and finally Robat Karim at 14%. Optimal water demand volume and area under cultivation in the total state, have decreased by 36%, and the volume of groundwater consumption by 74 percent compared to the current conditions. The amount of optimal water consumption (surface water and groundwater) of agricultural products also shows the values of 36, 39, and 25% respectively in Shahriar, Eslamshahr, and Robat Karim districts, which according to this issue, water consumption in the agricultural sector is in optimal conditions compared to the current situation has decreased by 44 %. The highest parameter of the ratio of income to cost obtained is related to Shahriar district, then Robat Karim district and finally Eslamshahr district. The results of the simulator models show the groundwater level changes resulting from the third scenario compared to the neural network model by 11 m. Finally, Optimal cultivation pattern planning and exploitation of water resources compared to the third scenario of the model and the neural network model, was chosen as the pattern of optimal water planning.   

Products such as vegetables, alfalfa, onions, grapes, pears, and pomegranates can be used more in the study areas, because the amount of income to cost and volume of water consumed have been suitable, and these factors have been very effective in increasing the net profit and changes in the groundwater level, and prevent the occurrence of crime and water complex problems. Also, optimal cultivation pattern planning and exploitation of water resources compared to the third scenario of the GMS and the neural network model, was evaluated as the selected optimal planning pattern of water resources. Therefore, by applying the desired research policies and optimal management and control of the cultivation pattern of agricultural products and available water resources, in addition to preventing the occurrence of crisis in water issues, environmental and economic problems can also be reduced.