جستجوی مقالات مرتبط با کلیدواژه « evapotranspiration » در نشریات گروه « اکولوژی »

This research aims to investigate the impact of climate change based on the sixth report (CMIP) under two scenarios SSP3_7.0 and SSP5_8.5 on forecasting temperature, wind speed, evaporation-transpiration (ET), and the amount of extractable water (Q) by two CNRM models and ESM was at 16 meteorological stations during the future period of 2025-2044 and 2045-2064. The statistical analysis results showed that the impact of climate change under two scenarios on temperature, ET and Q was significant. CNRM model performed better than ESM in temperature estimation (CC=0.96-0.98). From examining the results of the CNRM model, the maximum and minimum RMSE of temperature in Khormadreh and Zanjan stations were 8.30 and -0.5 , respectively; Also, the RMSE value of wind speed fluctuated between 0.82-0.5 m.s-1. The examination of ESM model showed the fluctuation of RMSE between 2.55-8.45  in temperature parameter and 0.62-0.68 meters per second in wind speed. The maximum and minimum values of Q and ET in the seasonal survey occurred in summer and winter, respectively. Both models had poor performance in predicting wind speed. The maximum ET under the SSP5_8.5 scenario by the CNRM model (first period) at Khorramdare station is equal to 104.29 mm.month-1 and the minimum value by the ESM model (first period) under the SSP3_7.0 scenario at Firuzkoh station is equal to 25.60 mm.month-1 was estimated. The maximum Q under the SSP3_7.0 scenario by the ESM model (first period) at Malair station is equal to 20.70 Lit.day.m-2 and the minimum value by the CNRM model (second period) under the SSP3_7.0 scenario at the Astara station is equal to 0.3 Lit.day.m-2 were estimated.

In this study, drought was investigated on water use efficiency (WUE) in different climates and uses of Tehran province. To calculate the efficiency of water consumption, the products of Gross primary production (GPP), Evapotranspiration (ET) and Palmer drought severity index (PDSI) obtained from the MODIS meter are used. Then the trend of changes in the index of primary gross production, evaporation and transpiration, water consumption efficiency and drought in the period of 2001-2021 using linearity and Mann-Kendall and slope tests, and then the response of water consumption efficiency to drought in different climates and consumptions with Use. It was evaluated from correlation analysis. By dividing annual rainfall into potential evapotranspiration (PET), the Aridity index (AI) was calculated and climate classification was done with the help of this index. The results showed that the indices of evapotranspiration, primary gross production and drought increased by 81.15, 86.86, and 99.99% respectively, and the water consumption efficiency index decreased by 76.24% in this 20-year period. Is. These results were confirmed by the slope test. Examining the relationship between the efficiency of water consumption and drought in different climates and applications showed that in dry climates, agricultural land and bushland had a negative ratio of 91.86 and 78.93, respectively, and pasture consumption had a positive ratio of 51.96. Agricultural lands, pastures and bushland related to semi-arid climate have increased by 85.38, 66.22, and 64.27 percent, respectively, and forest use has decreased by 84.87 percent. In semi-humid climate, respectively, 47.53, 60.48, 73.41% of the study area has a positive relationship in the use of agriculture, pasture and shrub land, and 91.30% of the use of forests has a negative relationship. In the climate, the negative impact of drought has been in 66.04, 61.15 and 50.56 percent of agricultural, pasture and forestry lands. In general, according to the mentioned results, drought has had a negative effect on water consumption in Tehran province, and it can be said that the resistance of the ecosystem against drought is determined by our correlation between drought index and water consumption efficiency.

Evapotranspiration is a complex phenomenon that depends on many factors and data, so determining it is very difficult and costly. In most methods mainly aimed at estimating evapotranspiration, point measurements have been used to estimate this variable. Therefore, it is only suitable on a local scale and cannot be extended to large basins due to the dynamics and regional changes of evapotranspiration (ET). One of the remote sensing algorithms for estimating real evapotranspiration is the Surface Energy Balance Algorithms for Land (SEBAL). In this algorithm, by estimating all energy components on the land surface such as pure radiation flux, soil heat flux, and tangible heat flux, using the energy balance equation, evapotranspiration is used. The aim of this study is to compare the estimation of real evapotranspiration using SEBAL algorithm in wheat and rapeseed crops with the results of estimating evapotranspiration by Penman-Monteith-FAO method in the field of Esmaeil Abad Agricultural Research Station in 2019-2020. Single-sample T-test of ground surface temperature reflection index showed that the spectral reflection of wheat and rapeseed crops during phenological growth period had a significant difference. The results showed that the computational values of the two models are relatively good and the mean value of square root of error (RMSE) in estimating real evapotranspiration for wheat and rapeseed plants was 3.04 and 2.09 mm/day, respectively, and the coefficient of explanation (R2) was 0.78 and 0.81, respectively. The results showed that SEBAL algorithm model in comparison with Penman-Monteith-FAO model (based on up-to-date meteorological data) The amount of evapotranspiration for wheat and rapeseed plants is lower.

In this study, Iran's water consumption has been estimated in all provinces of Iran using the actual evapotranspiration product WaPOR which is developed by FAO. To considering the plains which have the main agricultural water consumption of Iran, the amount of water consumed was estimated for every province in the year 2010 to 2016, then the slope of changes in agricultural water consumption was determined for every one of them separately. The volume of water consumption in the agricultural area of Khuzestan, Tehran and Gilan provinces has the highest increasing trend in the period 2010 to 2016, respectively, and in other words, they have a positive slope changes. Hormozgan and Kermanshah provinces also had the largest decrease in the amount of water consumed in the agricultural area. The results of this 7-year statistical period illustrate that water consumption of agricultural and the volume of irrigation has been increasing in Iran since 2013. To evaluate the accuracy of WaPOR product, its values were compared with evapotranspiration from SEBAL algorithm and Lysimeter station statistics in Miandoab plain. The results present that in most areas, the evapotranspiration values of SEBAL algorithm are higher than the WaPOR, which reaches its maximum value by moving to an altitude of 2000 meters. The actual evapotranspiration values of the lysimeter of Tabriz University were in good agreement with the calculated values of the SEBAL algorithm, therefore the volume of water consumed calculated with WaPOR is less than the actual value.

Today, rapid population growth and economic development have increased demand for food, and climate change has affected food security worldwide. Climate change processes, including increasing the atmospheric carbon dioxide concentration, rising temperature, and fluctuation of precipitation, could directly affect agricultural products. Climate change also causes drought, which indirectly influences agricultural systems as water is the most important for grain yield and its quality. Arid and semi-arid regions are limited in terms of water resources and they are the most fragile regions faced with drought caused by climate change. Khuzestan province is one of the hot and arid regions in Iran which its agricultural crops (especially maize) are very sensitive to climate change. Irrigation schedules and various cultivars can be considered as the adaptation strategies according to the climate change conditions. In agricultural ecosystems, water consumption should be reduced, and grain yield should be increased as much as possible. Optimizing water consumption by improving water use efficiency (WUE) is essential for achieving agricultural sustainability in arid and semi-arid regions. Accordingly, modelling approach has been considered as a time-saving and low-cost way to study the effects of climate change and different treatments. The current study was conducted to investigate the effects of different irrigation management practices on maize grain yield and WUE under climate change conditions in order to optimize water consumption and WUE by using modeling approach.

The current study was carried out in several locations of Khuzestan province, including Dezful, Izeh, Bostan, and Ahwaz. The long-term climatic data of the studied locations were collected from the Iran Meteorological Organization. These data included minimum and maximum temperatures (°C), rainfall (mm), and solar radiation (MJ m-2) from 1980 to 2010. Angstrom equation was used for calculating the radiation based on sunshine hours. The climatic data were modified using WeatherMan software embedded in the DSSAT package. The future climate of Khuzestan province (2040-2070) was predicted by the MIROC5 general circulation model under the RCP4.5 climate scenario and using AgMIP methodology. According to the previous studies, the MIROC5 climatic model showed the highest accuracy in predicting the future climatic data of Khuzestan province. Two adaptation strategies, including cultivar and irrigation regime, were considered to mitigate the negative effects of climate change. The cultivars consisted of SC704 (late-maturity) and SC206 (mid-maturity), which had the highest area under cultivation in Khuzestan province. Irrigation regimes included three levels: 12-time irrigation (as farmers’ common practice), 10–time irrigation, and 14-time irrigation per growing season.

The results of the current study indicated that climate change had negative effects on maize grain yield as well as positive effects on average temperature during the growing season, evapotranspiration, and corn water use efficiency across the whole province. The results showed that the average grain yield and corn WUE in Khuzestan province in 2050 under the RCP4.5 scenario was -2% and -5.7%, respectively, compared to the baseline. In addition, mean temperature during the growing season and evaporation and transpiration increased by +12.6% and + 0.9% compared to the baseline. The results also showed that with the application of an optimal amount of irrigation regime (10-time irrigation), an increase in WUE and decrease in evapotranspiration were observed, which resulted in acceptable grain yield. Results also portrayed that applying the optimal irrigation level (10-time) along with a late maturity cultivar (SC704) showed the best performance in terms of grain yield (9433.9 kgha-1) and WUE (19.57 kgha-1 mm-1) in the province Khuzestan.

The results illustrated that by 2050, the average grain yield and WUE were reduced compared to the baseline period. However, the mean temperature and evapotranspiration over the growing season were increased. Totally, the results of the current study revealed that an optimal irrigation level 10 and suitable cultivar SC704 could mitigate the negative impacts of climate change on maize in the agroecosystems of Khuzestan province.

In semi arid regions that are affected by drought, maintaining and developing vegetation and green space is facing by serious challenges of waterless. The purpose of this study is to compare the water requirement of Fraxinus rotundifolia and Morus alba as common species in Robat Karim, located in the southwest of Tehran province. This research was carried out in greenhouse and field and saplings of two tree species were planted in a completely randomized design in the field and inside the pots. This research has two stages and each stage consists of several phases. The results showed that in Fraxinus rotundifolia and Morus alba species, the fastest time to reach the MAD point respectively was 4 days (from 6 to 9 July), And 4 days (from 6 to 9 July, 10 to 13 July and 29 July to 1 August) in the greenhouse, And the fastest time to reach the

Evaluation of evapotranspiration is one way to prevent water loss and water resource management. Therefore, in this study, an attempt has been made to calculate the actual evapotranspiration rate in the east of East Azerbaijan province using the SEBAL algorithm. For this purpose, first, based on two Landsat 8 satellite images dated 2017/08/22 and 2017/08/09, the values of Net radiation, soil heat flux, and sensible heat flux are estimated. Then, based on the difference, the amount of instantaneous heat flux was calculated and 24-hour evapotranspiration was obtained for each image. Finally, the amount was compared with the values obtained from the Penman-Monteith method. Also, for processing and analyzing images ENVI4.8 software was used. The results indicated that the amount of evapotranspiration in the Penman-Monteith and SEBAL method on 2017/08/22 was about 6.15 and 7 mm per day, and on 2018/08/09, respectively, about 7.38 for Penman-Monty and 7.94 mm per day for SEBAL. Overall, the amounts of SEBAL actual evapotranspiration and Penman-Monteith potential evapotranspiration have a mean absolute difference (MAD) 0.705 mm per day which indicates that the estimated values are consistent with the SEBAL algorithm and the Penman-Monteith method.

Stochastical analysis can increase decision-making reliability, meanwhile increasing the flexibility of decisions. The critical role of climatic factors in land zoning on the one hand and the stochastical nature of climatic variables, on the other hand, causes the uncertainty of land suitability grading for plant cultivation, especially in dryland conditions. Golestan province has the third rank among the Iran provinces with about 400,000 hectares of cultivated land and production of more than one million tons of wheat, of which about 57 and 50 percent are allocated to rainfed cultivation, respectively. The present study was conducted to examine changes in various climate variables affecting wheat growth under the influence of different occurrence probabilities and zoning agricultural land in Golestan province for the rainfed wheat cultivation under these conditions.

 First, dates of planting and occurrence of each phenological stage of rainfed wheat were determined by daily data of precipitation and minimum and maximum temperatures for 33 weather stations in Golestan province in a 26-year typical statistical period. Then, by fitting different probability distribution functions and selecting the best distribution, the values of these variables were estimated at five occurrence probability levels of 25, 50, 75, 85, and 95 percent. Next, the average air temperature, the possibility of occurrence of adverse temperatures, precipitation and ratio of effective precipitation to potential evapotranspiration of wheat for each growth stage and total growth period were calculated for whole weather stations at different occurrence probability levels. Finally, by providing zoning maps of these variables and other features including elevation, land slope, land type, soil salinity and overlaying 22 layers for each occurrence probability level, agro-ecological zoning of agricultural lands of Golestan province for rainfed wheat cultivation at different occurrence probability levels was performed.

 Results showed that increasing occurrence probability level from 25 to 95 percent due to delaying suitable planting date from late autumn to early winter and its effect on the climatic-environmental conditions and the length of the plant growth stages improved the degree of land suitability grade for rainfed wheat cultivation in terms of mean air temperature in stages of flowering, maturity and total growth season, the occurrence possibility of temperatures higher than 14 and less than 9 °C in germination and flowering and maturity stages, respectively, and the amount of precipitation in the germination stage. Adversely, it resulted in degradation in the degree of land suitability in term of mean air temperature in the germination stage, the occurrence possibility of temperatures higher than 25 and 30 °C in flowering and maturity stages, respectively, and the amount of precipitation and ratio of effective precipitation to potential evapotranspiration in stages of flowering and maturity and the entire season. The results of agro-ecological zoning showed that the extent of suitable and moderate zones was between 50-56 and 44-50 percent of the agricultural land, respectively, for the occurrence probability levels of 50, 75 and 85 percent and the occurrence probability did not have a significant effect on zoning. In comparison, at the occurrence probability levels of 25 and 95 percent (equal to the early and late planting dates, respectively), about 91 and 78 percent of the province's agricultural land was located in a suitable and moderate zone, respectively. These results are accordant with the findings of Hoseini et al. (2018), who showed that the maximum extent of suitable land for cotton cultivation in Southern Khorasan province occurred in the early planting date. Considering the majority of agricultural land of Golestan province is located in the middle strip of the province, most changes of zoning maps by occurrence probability level have also occurred in this region.

A low reduction in cultivation risk (increasing the occurrence probability from 25 to 50 percent) significantly degraded the land suitability for rainfed wheat in Golestan province while more reduction in the farming risk (increasing the occurrence probability up to 85 percent) led to no significant effect on land suitability. However, if the minimum risk (95% probability) be selected as a management decision for rainfed wheat farming, the lowest land suitability for rainfed wheat cultivation will occur.

There are various methods for estimating evapotranspiration, in which the performance of these equations varies in different climatic conditions. The purpose of this study is investigate different methods of evapotranspiration of reference plant in different climates of Iran and validate these methods by FAO-Penman-Monteith method. For this, 30-year weather data (1988-2017) were used in nine cities (Shahrekord, Urmia, Mashhad, Zahedan, Bandar Abbas, Ahvaz, Gorgan, Rasht and Sari). Initially, evapotranspiration was obtained by the FAO-Penman-Monteith method on a daily basis. Then reference evapotranspiration values were calculated with 24 other methods. Using RMSE, (MAE), (MR) and (PE) with the method FAO-Penman-Monteith. The results showed that in cold and semiarid, cold, moderate, warm and dry, cold and dry, warm and humid conditions, there were Urmia, Shahrekord, Zahedan, Mashhad and Ahwaz, modified Makking models, in warm and humid climate of Bandar Abbas, respectively. The Voluntzas model and in the Mediterranean, semi-wet and humid climates including Gorgan, Sari and Rasht, the Druggerz and Allen model had a better and closer estimate by the FAO-Penman-Monteith method.Regarding the scores given to each method based on the MAE and RMSE evaluation index, modified Makking models, Derrgger and Allen, Valiantzas and Hargreaves Samani and based on the index PE models and Reynolds and Allen, McQueen modified, Valiantzas and Hargreaves Samani were selected as superior models.

Evapotranspiration the catchment area is one of the main components of the water cycle and estimates the need for irrigation. The purpose of this study is to estimate the daily evapotranspiration and forwarding (ETo) using a neuro-fuzzy comparative inference system (ANFIS) and compare it with the experimental model of Tork. The input data of the turquoise model, including sunshine, air temperature, relative humidity and wind speed, were obtained from the Meteorological Station of Poldokhtar from the Lorestan Meteorological Station, and evapotranspiration was obtained using this method. Input data (ANFIS) including average temperature, mean humidity and latent evaporation rate were calculated using the corresponding and were given to the data model. The results of each method were compared separately with evaporation calculated at the station location using a vapor pan. In this study, the performance of the ANFIS based on the optimization algorithm (PSO) was satisfactory and the results were satisfactory. The efficiency of the compared methods was obtained using root mean square error (RMSE), mean square error MSE And the R2 determination coefficient was evaluated. The ANFIS-PSO method, with only three parameters, is the average of average humidity and the latent evapotranspiration rate, which can predict daily reference evapotranspiration and is more accurate than the empirical model of tork. So that the value of R2, RMSE, MSE for ANFIS model is 0.90, 2.65, 13.7 and for the experimental model of Tork is 0.63, 6.26, 39.24, respectively.

Actual evapotranspiration is one of the main variables in calculating the water balance and land surface energy. Different methods for calculating actual evapotranspiration have been presented so far. The purpose of this study was to investigate and compare various existing methods for estimating actual evapotranspiration in the Urmia Lake basin in order to select an optimal algorithm. Using the ETLook, SEBAL, SEBS and S-SEBI algorithms based on the energy balance equation, the results obtained by comparing the results of different algorithms showed that the ETLook method has been able to utilize the latest methods of estimation of evapotranspiration. Many The failings of other algorithms are covered. This two-source method analyzes vegetation and soil separately, using soil moisture images, has not even been able to withstand its efficiency in calculating evapotranspiration, even on cloudy days. However, the commercialization of this algorithm and the great difference in the results of the global WaPOR product (produced with ETLook) with ground observations in the Urmia Lake basin has made it less and less convenient to use. Considering all the conditions, including having a suitable physical base, ease of implementation and comparison with ground values, it can be admitted that the SEBAL algorithm is the most suitable option for estimating the actual evapotranspiration of the Urmia Lake basin.

Water is a scarce resource in the Middle East region and climate change is expected to exacerbate this situation. Developing countries are vulnerable to these changes, primarily due to their limited adaptive capacities in dealing with extreme events. Therefore, investigation of this phenomenon will be very crucial in such areas. In the past decades, water shortage in Yazd province which is located in arid regions of Iran has resulted in transferring the water from Isfahan. But recently, due to increasing in water demand, inadequacy of this project clearly has felt. Evapotranspiration and agricultural water requirements are two crucial issues of this area which affected by climate change. Thus, considering climate change projections and future agricultural water requirements is necessary to determine water stress risks in the study area, Hence, this study aims to answer the following research questions:
Currently, how much irrigation water do we need in the Yazd-Ardakan region?
How does future climate change impact future irrigation requirements?
How does future climate change influence sustainability of the agricultural water consumption? The data used in this analysis represented into two time periods, including (i) present (values for the period 1971–2005), and (ii) future, called year 2070 (values for the period 2021–2070). To evaluate future climate changes, daily climate data from Yazd Synoptic station for 1971-2005 period have been used. Data, including precipitation, maximum and minimum temperatures and sunshine hours. To investigate the climate changes of Yazd-Ardakan plain in the future period of 2021-2070, RCP 4.5 scenario has been used through SDSM 4.2.9 software. The effect of climate change on reference evapotranspiration and agricultural water needs were estimated. Crop evapotranspiration and irrigation requirements for two periods, were estimated following the standard procedure described in the FAO Irrigation and Drainage Paper 56 (UN-FAO, 2007) and CROPWAT software. Two indices considered to evaluate the sustainability of the agricultural water consumption in the study area. These indices including the ratio of evapotranspiration to the precipitation (EPR) and the ratio of maximum agricultural water deficit to the amount of agricultural water need as deficit index (MD). These indices estimated under present and future climatic conditions. To evaluate the amount of water used for main agricultural products, questionnaires were completed in the area. The results of statistical validation of the predicted values, showed no significant differences between historical and predicted values of precipitation, maximum and minimum temperatures and sunshine. Therefore, suitability of LARS-WG model to simulate climatic data of the study area is confirmed. Investigation of the precipitation in the Yazd station showed that in spring season, precipitation will be declining and in autumn will be increasing. In other words, the distribution of precipitation in the future will have significant changes and as winter precipitation decreases the spring precipitation will have increasing trend. Results showed that monthly minimum and maximum temperature will increase in almost all months. Results of estimating agricultural water requirements showed that due to higher temperature, reference evapotranspiration, crop evapotranspiration and irrigation requirements will be increased up to 4% under climate change conditions. The EPR and MD indexes will increase by 24% and 13% respectively. The results revealed the imbalance between agricultural water use and the precipitation in the study area. In the other hand, results of the questionnaires showed that, the water used in irrigated agricultural areas is not in accordance with the requirements of products and therefore leads to water stress and, consequently, yield reduction of products. Therefore, in these conditions, appropriate management strategies and planning should be implemented to ensure the sustainability of water resources inthe Yazd-Ardakan plain. This work focused on the climate change impact on cultivated area in the Yazd-Ardakan plain considering the possible alterations of crop evapotranspiration and irrigation requirements. According to this study by increasing in maximum temperature in the future, water needs of agricultural section will grow significantly. Therefore, planners and authorities should consider this fact for the future water resources allocation and strategies.

The estimation of evapotranspiration is one of the most important parameters in irrigation planning. In this research, drainage lysimeter data and three single-source energy balance, SEBAL, METRIC and SSEB and a two source energy balance algorithm, TSEB have been evaluated. Satellite imageries of MODIS, ETM + sensors were used in the years 1379-1382 according to the lysimeter data loading and OLI & TIRS sensor images in 1392-1395. It should be noted that, the mismatching of the OLI & TIRS images timing with the lysimeter data timing, cause to try to evaluate the results of OLI images with Hargreaves Sarmari equation as a superior experimental method. According to the statistical indices, the results obtained from single-source algorithms showed that the SSEB algorithm with the lowest root mean square error in MODIS, ETM + and OLI & TIRS (RMSE = 0.87, 0.41 and 0.92 mm per day), and a large correlation It was introduced with lysimeter data as the best method in this area (R = 0.97, 0.99, 0.96). Among the sensors examined, ETM +, OLI & TIRS sensitivity is high on the two sensors, but the ETM + sensor also has better results

Golestan Province is one of the main areas of wheat production in Iran. In 2015, it ranked third among all the provinces of the country in term of acreage and yield (Anonymous, 2016). Given the strategic importance of wheat, it is necessary to identify suitable areas for its rainfed cultivation based on meteorology, agronomy, soil and land properties. This process is known as agroecological zoning. In addition to analyzing ecological factors affecting rainfed wheat production based on the consolidation of scientific references, this study will also identify suitable zones in Golestan for rainfed wheat cultivation.
Firstly, six factors were determined in 30 weather stations in the concurrent period 1991-2015 including: planting date, dates of each phenological stage of wheat based on growing degree-days (Ahmadi et al., 2016), precipitation, air temperature and the ratio of effective precipitation to crop evapotranspiration in each stage, and total growing season of wheat. These parameters were then estimated by the occurrence probability level of 75% (Sys et al., 1991). The possibility levels of higher and lower temperatures than the tolerable threshold of wheat in various stages of growth were also calculated. Next, a zoning map of the parameters and characteristics of elevation, slope, soil type and salinity were prepared in five classes. Finally, by overlaying these data layer (layer 26), the agroecological zoning of agricultural land of Golestan for the cultivation of wheat was performed.
Average air temperature during germination, flowering and seed filling stages of wheat in Golestan with occurrence probability of 75% were 8 (moderately suitable), 10.9 (moderately suitable) and 22.7 °C (suitable), respectively. Also, the occurrence probability of temperature less than the tolerance threshold in the germination stage of wheat (10 °C) was considerable in the province, but the occurrence probabilities of higher and lower temperatures than the tolerance thresholds of wheat in other growth stages were low in the dominant area of the province. The results showed that in terms of the ratio of effective rainfall to potential evapotranspiration during the total growth period, 92 percent of the province area was located relatively equally in moderately suitable (29%), suitable (9%), and very suitable (20%) classes for rainfed wheat cultivation. Also, soil salinity in 72 percent of the agricultural land was less than the tolerance threshold of wheat (6 dS.m-1). According to the results, total area of very suitable, suitable and moderately suitable zones for rainfed wheat cultivation in the agricultural zones of the province was 602,000 hectares, that is 51% and 117% more than the current acreage of total wheat and rainfed wheat, respectively. Furthermore, the sum of moderately to very suitable zones for rainfed wheat cultivation was calculated at 64.8 of the province and 85 percent of total agricultural land. In the entire country, the highest percentage of very suitable areas were located in Gonbad (24.7%) and Kalaleh (20.9%), suitable areas in Maravehtapeh (18.2%) and Gorgan (16.4%), and moderately suitable areas in Gonbad (22.8%), Aghghalla (19.7%) and Gomishan (17.7%).
Suitable areas for rainfed wheat cultivation in Golestan Province are generally located in the middle strip of east-west. The extents of these zones in the occurrence probability level of 75% are over the current wheat acreage of the province. This result is consistent with the Bidadi et al. (2015) findings.

Obviously, in any planning for qualitative and quantitative management of water resources, ýestimating the water balance and values of the input and output components that will play an ýimportant role. Several studies in the field of evapotranspiration most complex component of ýthe water balance in the world and many models offered and developedþ.þý Remote Sensing due to ýthe superiority of meteorological methods based on measuring point and water balance is more ýin the works. In this study, performance of Surface Energy Balance (SEBS) model to estimate ýactual evapotranspiration in Sistan plain is studied. For this purpose data from Zehak ýmeteorological stations and the technology of remote sensing and MODIS sensor images used. ýSurface flux of energy balance is calculated for each image pixel and actual evapotranspiration ýwere estimated by the remaining amount of the energy balance at the level. The results were ýcompared with results of two point ground-based data consist of the hay grown on the sidelines ýof Zahak synoptic station and water level of reservoir of Chahnime1. Model showed good ýperformance for both land and water based on correlation coefficient value with 0.78 and 0.89 ýrespectively.ý

APSIM model was used to investigate yield and water requirement of maize in different planting dates under two emission scenarios (RCP4.5 and RCP8.5) at the three locations of Kermanshah province (Kermanshah, Kangavar and Eslamabad-Gharb). Climatic parameters were predicted using the AgMIP methodology. Results of this study indicated that in the future, average maize grain yield will be reduced in all locations, scenarios and planting dates (70 percent) compare to the baseline. Reasons for yield loss are increasing temperature over growing season (15.7%), decreasing length of growing season (4.7%) and is likely to concurrency time of flowering with extreme temperature. In addition, maize water requirement, on average, will be increased 14 percent is comparison to the baseline in all locations, scenarios and planting dates mainly due to rising temperature. In conventional planting date (4 May), crop water requirement of maize on average increased 12 percent under two emission scenarios compared with the baseline while on earlier and later planting dates, crop water requirement increased 15 and 7 percent, respectively. Due to the amount of higher cumulative rainfall during the growing season (54.27) on earlier planting dates (4 and 19 April) as well as lower yield loss compare to other planting dates (56 percent), earlier planting dates can be explained as adaptation strategy in order to achieve appropriate yield. The results also showed that among study locations, Eslamabad-Gharb and Kermanshah were the most suitable areas in terms of grain yield (4221.8 Kg.ha-1) and water requirement (1489.2 mm), respectively.

Plants may be exposed to various stresses and water deficit is the most important limiting factor of growth and yield in many parts of the world and Iran. Stress induced growth decrement can be because of cell development decrease due to decrement of turgor pressure and meiosis and photosynthesis decrease due to stomata closure. Determination of desired planting density is one of the success factors of plant growth and production. Garlic (Allium sativum) has been an important medicinal plant over centuries in human life. According to the importance of medicinal plants and studying the effects of drought stress on them, the goal of this research is to investigate the effect of drought stress and planting density on growth and morphological characteristics of two ecotypes of garlic and determining the preferable ecotype and density from the perspective of these traits.
This experiment was performed in 2012 in a farm in south east of Semnan. It was conducted on a split-plot factorial arrangement based on randomized complete blocks design with three replications. Three levels of drought stress with 60, 80 and 100 percent of crop evapotranspiration (ETc) were the main plot factors and factorial combination of three planting density (30, 40 and 50 plants.m-2) and two ecotypes of Tabas and Toroud were the levels of sub plot factors. To estimate water requirement of garlic, daily measured meteorology parameters of Semnan synoptic station were used and water requirement was calculated based on FAO-56 instructions. From mid-January, the sampling of leaf area, bulb and leaf fresh and dry weight was started with destructive method every other week and continued until middle of Jun. three plant were selected randomly from each plot in each turn. From middle of May, height and number of leaves were measured. Leaf area measurement was done by leaf area meter (Delta-T). To estimate growth indices, dry weight of aerial and underground organs and leaf area from measured samples of treatments were used.
The results showed that the highest value of maximum leaf area index (LAI), maximum total dry matter accumulation (TDM), maximum crop growth rate (CGR) and maximum of net assimilation rate (NAR) were observed at 100% ETc with the value of 5.537, 387.53 gr.m-2, 10.47 gr m-2day-1 and 4.92 gr.m-2leaf.day-1 respectively; and by applying the irrigation treatment of 80% ETc these values decreased to 3.745, 262.60 gr.m-2, 6.31 gr.m-2day-1 and 3.71 gr.m-2leaf.day-1 respectively. Drought stress can decrease cell development and division and plant photosynthesis, and thus, it can decrease leaf area index and consequently decrease light absorption, photosynthetic area, dry matter and crop growth rate. Difference between ecotypes in terms of number of leaves, maximum total dry matter accumulation and maximum crop growth rate was significant. Maximum crop growth rate (CGR) in Toroud ecotype was higher than Tabas ecotype but number of leaves and maximum concentration of total dry matter (TDM) in Tabas ecotype were higher than corresponding values in Toruod ecotype. The effect of planting density on maximum leaf area index (LAI), maximum total dry matter (TDM) and maximum net assimilation rate (NAR) was significant. The highest value of maximum leaf area index (5.017) and maximum total dry matter (358.57 g.m-2) concentration were obtained from 50 plant.m-2 density. The highest value of maximum net assimilation rate (4.61) was obtained from 30 plant.m-2 density. It could be because of having leaves exposed to more light and less shading.
Applying drought stress at the irrigation treatment of 80% ETc decreased studied growth characteristics of garlic. Therefore, it is recommended that garlic should be avoided from facing drought stress and its water requirement must be met as much as possible. In general, under drought stress, two studied ecotypes did not have any preference related to the studied growth characteristics. Higher planting density, due to higher active photosynthetic area over unit area, increased the dry matter in unit area.

The governing factors of drought are non-linearly correlated. Therefore, researcher needs to apply nonlinear methods such as CA to model and predict the drought. CA and its derivatives are among novel methods of drought simulation that rarely used for predicting the drought. While such methods have simple structures; they provide high visual capabilities for drought monitoring. This paper investigates drought in Najaf Abad plain using Markov, CA Markov and Landsat satellite images. At first, satellite image time series of transpiration were classified for 1995, 2008, 2015, and the land zonation of drought condition were estimated. Then, the drought in 2020 was predicted using CA Markov. The Kappa index is 0.63 and the agreement between actual and predicted map (M (m)) is 0.85. Our findings showed that our proposed model can suitably predict the drought. In addition, the drought distribution map showing the possibility of changes in 2020, suggests that if the situation continues and no changes in the type of cultivation and cropping pattern happen, all areas in danger of drought in 2015, will face drought more intensely and more widely, in 2020.