جستجوی مقالات مرتبط با کلیدواژه "تبخیر-تعرق" در نشریات گروه "جغرافیا"

Reducing the effects of drought and optimal management of water resources is affected by the forecast of regional planners of areas affected by the risk of drought, so the evaluation and study of this phenomenon can be very important. Therefore, this study was conducted to Monitor temporal-spatial changes of meteorological drought and trend analysis of climatic variables in Khuzestan province during the period 2000 to 2020 using the SPEI index and ArcMap, XLSTAT, and RStudio software. Two non-parametric methods including Mann-Kendall and Sen's estimator slope methods were used here to analyze the annual trends of data. After calculating the drought, the effect of this phenomenon on the water area of Horul Azim and Shadgan wetlands in 2000, 2006, 2015, and 2020 was investigated. The results showed that there is a direct relationship between the changes in the wetlands cover and the problem of drought, and with the increase of drought, the water cover of the wetlands decreases and with the increase of drought, the area of water in the wetlands increases. The results also showed that the analysis of the trend of changes resulting from Sen’s slope for precipitation and temperature in the stations varied between -1.87 and 3.38 and 0.016 and 2.25, respectively. The highest slope of changes with increasing rainfall was observed in the western and central regions of the province and the slope of negative changes in rainfall has often occurred in the southern regions. Also, temperature analysis with this test showed that the temperature in all stations with a relatively slow slope in the study period had a positive and increasing trend. It is worth mentioning that the existence of increasing and decreasing trends indicates the existence of climate change, so it is necessary to study this issue and provide solutions to water resources management in times of crisis. The increasing and decreasing trend indicates the existence of climatic changes and fluctuations; Therefore, investigating this issue and providing solutions to manage water resources in times of crisis seems essential.

Introduction:

Global warming due to greenhouse gas emissions is leading to changes in the spatial and temporal distribution of water resources on a global scale. On the other hand, as Iran is located in an arid and semi-arid climatic region, about 75% of rainfall in the country is directly returned to the atmosphere through evaporation. Since potential evapotranspiration is one of the most important components of the natural water cycle and is the identification of plant water requirement, its exact estimation plays a key role in the planning related to the type of cultivation and irrigation. Based on the literature, the Mann-Kendall test has been used repeatedly to examine the trend of changes in meteorological components. Considering the importance of determining the trend of evapotranspiration changes in water resources planning, the purpose of this study is its investigation in a monthly timescale using Mann-Kendall test and the Sen’s estimator slope in Iran. In addition, by analyzing the spatial distribution of evapotranspiration using the GIS, the trend of evapotranspiration changes was also examined.

The study area in this research includes 79 appropriately distributed synoptic meteorological stations with acceptable data quality which belong to the Irainan Meteorological Organization. Their common statistical period is 22 years (1995 to 2016). From a geographical point of view, Iran is located in the northern hemisphere between 25 and 40 degrees north latitude and between 44 and 63.5 degrees east longitude. It has a dominant arid and semi-arid climate with low rainfall and high evapotranspiration. After selecting synoptic stations, the required data including geographical coordinates of stations, altitude, daily temperature (minimum, maximum, and average), wind speed, and sunshine hours were collected for the common time period (1995 to 2016). Then, the potential evapotranspiration was calculated using Hargreaves-Samani method and the total monthly evapotranspiration was extracted for the desired time period. By performing the Mann-Kendall test, the trend of evapotranspiration variation has been estimated and the significance of this trend has been analyzed using the Sen’s estimator slope.

The results of this study obtained by the analysis of the evapotranspiration trend during 1995 to 2016 and implementing the Mann-Kendall test and the Sen’s estimator slope on a monthly time scale show that the trend does not follow the same pattern during different months of the year. In terms of time, in spring and summer, significant increasing trends have been seen in most cases where its highest were in June. In July, different climates of Iran have a significant increasing trend. Due to low rainfall in this month and sensitive conditions, this increasing trend of evaporation can raise the demand for water resources and in some cases reduce the yield of agricultural products. In August and September, despite the oppressive heat, in most of central and southern parts of the country, with a hot and dry climate, there was a decreasing trend of evapotranspiration. At the beginning of autumn and in October, the central parts of Iran had a significant downward trend, but in November and December, the existence of significant trends is much less. In winter, there is no trend in most stations. Generally speaking, the most significant increasing trends have occurred in the warm months of the year. Due to the decrease in precipitation oscillations and increase of temperature in these months, increase of evaporation has raised the water needs for agricultural products. Thus, the failure in its management will lead to a shortage of available water and damage to agriculture by the reduction of crop efficiency and yield. From spatial viewpoint, there is a more increasing trend in the cold regions and mountainous areas of the country and a negative trend has appeared in the tropical, central and eastern regions. In general, the percentage of non-trending stations varies from about 68% in summer to about 86% in autumn, and on average, about 78% of stations have a steady state about the evapotranspiration. Of the remaining 22% of stations, most (about 15%) have an increasing trend, and this goes back to the spring and summer seasons. This means that the plants’ water requirement is increasing when there is less rainfall, which is consistent with the conditions created by climate change, which leads to more severe drought events in arid areas.

There are many methods for calculating evapotranspiration that require a lot of data, but a few require only air temperature. One of these methods is Trontwait. The Sistan region in the southeast of Iran is one of the regions that is unique in Iran due to the 120 days of winds. The purpose of this research is: 1) to evaluate 6 different Trontwait methods available in the sources compared to the Fau-Penman-Monteith method and 2) to modify the equation for the windy region of Sistan. The results showed that the original Trontwhite equation underestimates the amount of evaporation-transpiration. Among the existing methods, the use of coefficient k=0.72 had the best results. In order to recalibrate the Trunthwaite equation, the effective temperature coefficient of the equation (k) must be modified. The results showed that the optimal value of k varies between 0.755 and 1.04. The annual average value of the root mean square error (RMSE), according to the variable k values, was equal to 0.14 mm per day. Also, by minimizing the square of the error, we considered the k value to be 0.802 as a constant, and the RMSE value was equal to 1.19 mm per day. It can be concluded that after correcting the Trontwhite equation, it can be used in the Sistan region.

 Reference evaporation and transpiration is one of the important elements of the hydrological cycle, which plays an important role in agricultural studies, water resource management plans, irrigation and drainage network design and water structures (Nuri et al., 2013, Volume twenty, number five, page 12). Due to the small amount of precipitation and the limitation of water resources in Iran, the correct management of water resources is very important and it is necessary to be careful in using water.
Data and

In order to carry out this research, daily climatic data during the years 2014 to 2015 of East Azerbaijan (four stations of Maragheh, Midane, Jolfa and Ahar) were prepared from the regional meteorological organization. After normalization and determination of correlation, the data were used in MATLAB software with artificial neural network method with Lunberg-Marquardt training to 70-30 combination for training and simulation. The input data for the simulation of evaporation and transpiration (temperature, sunshine hours, humidity, wind speed) and the work evaluation criteria are RMSE, R2 and MAE, which we gave priority to the data with less error.

In this research, the method based on artificial intelligence (ANN) and three experimental models (Penman Monteith Fau (PMF56), Blaney Kridel (B-C) and Kimberly Penman (K-P) were used to model the non-linear transpiration evaporation system of the reference plant. The results showed that the artificial intelligence method has better accuracy and speed in estimating ET0 compared to experimental

The results showed that the artificial intelligence method has better accuracy and speed. Also, comparing the method of artificial neural networks with classical methods, the results indicate the appropriateness of the performance of artificial neural networks.

Due to technical and financial limitations, it is not possible to simultaneously provide high spatial and temporal resolution by a sensor. There is always a trade-off between the spatial and temporal resolution of the sensors. For studies such as estimating evapotranspiration, land surface temperature with high temporal and spatial resolution is required; however, estimating actual evapotranspiration with high temporal and spatial resolution by a single sensor is not possible. Since high spatial and temporal resolution together increase the reliability of analyzing and extracting information from the image, so the best way to overcome this problem is to downscale images to high temporal and spatial resolutions. Downscaling is the process of converting images with low spatial resolution to images with high spatial resolution. So far, several methods have been proposed for downscaling. These methods differ for downscaling of the reflectance and thermal bands. Many studies that have been conducted so far on the actual evapotranspiration estimation, indicate the efficiency of SEBAL algorithm for this purpose. Therefore, in this study, in order to calculate the actual evapotranspiration, the SEBAL model was used and the products of different downscaling methods were given as input to this model. Assessing the accuracy of actual evapotranspiration ​​calculated using remote sensing data indicates the efficiency of products obtained from different methods. According to the studies conducted in this field, so far no study has been done on the combination of downscaled bands obtained from different downscaling methods applied on thermal data and non-thermal data in order to calculate the actual evapotranspiration. In this study, STARFM, ESTARFM and Regression algorithms were used to downscale the reflectance bands and SADFAT, Regression and Cokriging algorithms were used to downscale the thermal bands. Then the accuracy of the results was evaluated.

The study area is Amirkabir agro-industry located in the south of Khuzestan province, one of the seven companies for the development of sugarcane cultivation and ancillary industries (longitude 48.287100, and latitude 31.029696 degrees). The gross land area of this agro-industry is 15000 hectares and its net area is 12000 hectares which is divided into several 25-hectare plots. In this research, the images of MODIS located on Terra satellite and the images of OLI and TIRS sensors of Landsat 8 satellite were used. It is worth noting that the Landsat image for time 2 was used to evaluate the simulation results. The downscaling algorithms used in this research included STARFM, ESTARFM, and REGRESSION algorithms were applied on reflectance bands and SADFAT, Regression and Cokriging algorithms were used for thermal band downscaling. In order to conduct this research, first, various downscaling methods were applied on MODIS images to be downscaled to the images with Landsat spatial resolution. Then, using MODIS downscaled images, evapotranspiration values were calculated for different combinations of downscaled data using SEBAL method and the results were compared and evaluated with evapotranspiration obtained from Landsat images acquired at the same date as MODIS data.

In order to evaluate the results, the downscaled bands were visually and quantitatively compared with the corresponding bands of the Landsat image acquired on the same date. In order to compare these data quantitatively, the root mean square error (RMSE) and the coefficient of determination (R2) were used. According to the RMSEs, it can be concluded that the STARFM, ESTARFM, Regression, SADFAT and Cokriging downscaling algorithms all perform well. Among the methods applied to the reflectance bands, STARFM with the RMSE of 0.0180 had the best performance, followed by ESTARFM with the RMSE of 0.0186 and Regression with the RMSE of 0.0479. Among the methods applied to thermal bands, the SADFAT algorithm with the RMSE of 0.0224 had the best performance, followed by Cokriging with the RMSE of 0.0234 and Regression with the RMSE of 0.0464. It should be noted that the difference in outputs is very small, and given that the study area of ​​this study is a homogeneous area of ​​agricultural land cover including a single sugarcane crop. This issue can be the main reason for the close performance of downscaling methods and the high accuracy of their outputs. Moreover, according to the results obtained for evapotranspiration, ESTARFM / Regression, ESTARFM / SADFAT, STARFM / Regression and STARFM / SADFAT had the best performance with the lowest difference and the Regression / Cokriging method had the weakest performance, respectively.

This study can be concluded as follows:All downscaling algorithms used in this research had an acceptable performance in simulating Landsat bands.Among the reflectance band-related downscaling methods, STARFM had the best performance, followed by ESTARFM and Regression, respectively.Among the thermal band-related downscaling methods, the SADFAT algorithm performed best, followed by Cokriging and Regression.The use of STARFM algorithm for reflectance bands and SADFAT algorithm for thermal bands in homogeneous areas is recommended.The difference between the different combinations of methods for estimating actual evapotranspiration is small.

The study of climate change effects on crop growth and irrigation water requirement is crucial in maintaining food security. As a direct consequence of warmer temperatures, the hydrologic cycle will undergo significant impact with accompanying changes in the rates of precipitation and evaporation. Water scarcity and climate change pose a big threat for Iran’s food security. Climate change is projected to increase temperatures, spatio-temporal variability in rainfall pattern, and water stresses to crops. Due to the significant role of water in crop yield, inadequate soil water in crop producing regions can result in substantial yield drops. Agriculture, which accounts for 80 percent of freshwater consumption worldwide and the researchers, examined trade through the lens of what they call “virtual water” — a measure of how much water goes into the production of a bushel or a kilogram of a given crop. Upon release of new scenarios based on Radiative Forcing which are known as Representative Concentration Pathway scenarios (RCP scenarios), by Intergovernmental panel on climate change (IPCC) in fifth assessment report (AR5), a new set of 42 global climate models (GCMs) have been proposed for future climate projectionsThe current study was aimed to investigate the possible impacts of climate change effects on evapotranspiration and virtual water of several major crops of Wheat, barley, potato and tomato in there region in Kerman province, south of Iran.

Study consists two sections. In part one for climate change detection, trend analysis of temperature, rainfall and evapotranspiration variables were performed using Mann-Kendall and Sen’s slope estimator test in three study stations namely Bam, Jiroft, Kerman during three future periods (i.e. 2018-2039,2040- 2069, 2070-2100). In second part, for projection of virtual water of selected crops under RCP4.5 and RCP8.5 climate change scenarios (IPCC Fifth Assessment Report) during period of 2018-2100 in three study stations, crop evapotranspiration were worked out using downscaled outputs of CNRM-C5 climate model.The first step in impact assessment studies is selecting suitable climate models from those recommended by IPCC for obtaining required climatic data under certain scenarios. The results of uncertainty analysis performed in previous studies by authors were used choosing different models of CMIP5 project which are approved in fifth assessment report (AR5) . Also crops yield were simulated using Aqua Crop model. By choosing new date of sowing, temperature, rainfall and evapotranspiration during projected growing season were determined. Based on the maximum simulated yield for the study crops, the optimum date of sowing for future periods were chosen. Finally the crops virtual water (evapotranspiration divided by yield) was calculated.

The results of study showed that the air temperature, in all month in study stations, would increase comparing to baseline period 1990-2017, such that in three study stations under RCP 8.5 scenario the air temperature will increase 0.66,0.77,0.68 ◦C, respectively. Similarly under RCP 4.5 scenario, the corresponding values are 0.42, 027, 0.45 ◦C. The Maize crop yield would decrease in all three stations (with highest decrease in Jiroft station with 52 and 56 percents under RCP 4.5 and RCP 8.5  in 2018-2039 period comparing to baseline period, respectively.) The virtual water of all selected crops is projected to increase, but this increase would be higher for wheat and barley crops. The lowest increase in virtual water was observed in tomato crop during the future period of 2018-2100.In Bam station, the highest amount of virtual water belongs to barley crop during the period of 2040-2069, i.e. 4853 and 5153 cubic meter per ton under two RCP scenarios, respectively. In Jiroft wheat crop has the highest virtual water during the period 2040-2069 projected to be 4984 m3/ton. In case of Kerman station, largest amount of virtual amount under RCP4.5 belongs to wheat during the period 2040-2069 and under RCP 8.5 corresponds to barley with amount of 4256 m3/ton.

The virtual water of all selected crops is projected to increase; this increase would be more for Barley and Wheat. According to results it is recommended to estimate the virtual water of currently cultivated crops in the region for coming years. Continuous cropping of wheat and barley is not advisable Alternative low-water-use crops may be an option for producers. Further studies on major crops’ virtual water in the agricultural regions of the country are recom

Evapotranspiration is significantly affected by global climate changes as an essential component of both climate and hydrological cycles. Comprehensive analyses of the spatiotemporal changes of ETo enhance the understanding of hydrological processes and improve water resource management. The main objective of this study is to investigate and predict the temporal trend and spatial distributions of the mean maximum temperature (Tmax), the mean minimum temperature (Tmin) and reference evapotranspiration (ETo) during 1961-2014, 2021-2050 and 2051-2080 over Khorasan Razavi Province using CRUTS3.23 dataset and the outputs of four CMIP5 climate models. The results were as follows: (i) the ability of CRU dataset in simulating monthly mean of Tmax and Tmin is suitable, (ii) generally, ETo increased from north to south across the province (ii) from 1961 to 2014, annual ETo exhibited an increasing continuous trend across the area under study (iii) the mean annual minimum temperature projected to increase by 1.6 under RCP4.5 and RCP8.5 scenarios during two future periods. During 2051-2080, this variable will have an increase by 3ᵒ C under RCP8.5 scenario. The maximum temperature will increase by 4ᵒ C during the middle future period under RCP8.5 scenario. (v) The difference between mean annual ETo values of two periods was statistically significant in all grid points covering this province. The results showed that these increases may lead to the increase in crop water requirements and aggravate the water shortage in this area in view of the increase in ETo in response to ongoing climate change.

The purpose of this study is to investigate the changes in land surface temperature and evapotranspiration in relation to the standard vegetation cover index using GIS in Minoodasht city. In this study, we used satellite images of the Terra Modis satellite for the years 2001–2016. The satellite image is from January 1, 2005 to January 31, 2016. To evaluate the Seabull model, evapotranspiration was calculated using Penman Monteith and Hargreaves Samani methods and calculated using vegetation growth coefficient and compared with the evapotranspiration obtained from the Seabull algorithm and also to estimate the ground surface temperature of the images. Landsat 5 band 6 satellite which is thermal or thermal band was used. The results showed that the parameter of the coherent vegetation and the surface temperature of the earth changes in the opposite direction to evapotranspiration. So that in areas with good and dense vegetation and low ground temperature, evapotranspiration is more than other areas.

The increasing shortage of the renewable water resources in the country has made the farm water needs estimation to become as one of the important priorities in agricultural water management. Farm water needs are normally controlled by climatologic factors. It equals to the reference evapotranspiration which is corrected by a scaling factor associated to the crop kind and to local characteristics. In this research, using Landsat satellite imagery, we estimated and compared the crop coefficients for main agricultural crops in the Moghan cultivation industry, from two procedures: the first based on evapotranspiration measuring, and the second based on NDVI measuring. The comparisons in the case of the five main crops showed that the Root Mean Square Errors are within an acceptable range, leass than 0.28. In the following, the evapotranspiration based crop coefficient has been used in order to estimate farm water needs. Farm's water needs are indeed estimated by six methods a combination of two actual evapotranspiration and three reference evapotranspiration ways. Among the six methods, the Metric/PenmanMonteith method was selected for final step, i.e. farm irrigation needs. The farm irrigation needs is equivalent to farm water need minus effective rain. We compared four different ways for estimating the effective rains but preferred the FAO method assigned for low slopes. Based on our results, farm irrigation needs in the Moghan cultivation industry range from 270 mm (for rainfed barley) to 1500 mm (olive groves). Statistical investigation in three years data revealed a dependency between yield performance and evapotranspiration rate. In addition, it showed that yield performance is correlated with crop spectral indices such as NDVI, LAI and SAVI. The primary goal of this research is to estimate local agricultural crop coefficient in the Moghan cultivation industry. The second goal is to investigate of relationships between crop coefficient and crop spectral indices in order to make the crop coefficient estimable directly from spectral indices.

Water and food security are serious challenges in climate change studies. the purpose of this study is to investigate the effects of climate change on water requirements of apple during the growing season. For this purpose, the ECMWF database has been used for observation data of Semirom and Urmia stations during the 20-year period (1996-2001).To check this quantity in the next 20 years, the daily  Downscaling dynamic data of the CORDEX project with a precision of 44% * 44% for the output of the ICHEC-EC-EARTH model under the two lines of 4.5 and 8.5 (RCP) was used for the period (2017-2037). In order to reduce the errors in the model estimates, the post-processing action of the estimated events was fulfilled. Then, minimum temperature data, maximum temperature, relative humidity, wind speed and radiation, potential evapotranspiration have been calculated using Penman-Monteith FAO method, which is more accurate than other models, and using the non-parametric Man-Kendall test and the Sen’s Slope estimator nonparametric Method in the confidence range, 95% evapotranspiration was determined. In the end, the water requirement was also examined during the growing season of apples. The results showed that evapotranspiration in both stations is increasing during the growing season. The ETo increase in the growing season of the apple tree stations was predicted from the base period for the trajectory of 4.5 and 8.5 for the Semirom 4.14.7 and 7.99.7, respectively, and for Orumiye Station, 26.5 and 11.8, respectively, and however, this increasing process will raise the apple's need for water. The highest amount of evaporation and water requirement in the observed and estimated data has occurred in the bud break periods, growth fruits. At this stage, the lowest effective rainfall and the highest average temperature have occurred but generally, the percentage of upcoming changes of germination stage was more than other stages.

Introduction Climate plays a key role in the successful production of horticultural products in the global trade. Horticultural activities are highly dependent on local weather conditions. The study of the phenomenological behavior of products as part of the impact of environmental conditions is important, because in order to achieve optimal production as well as more appropriate management, it is essential to know the phonological stages and changes to the product. Methodology In this study, the ECMWF database has been used for observation data of Semirom and Urmia stations during 20-year period (1996-2001).To understand and evaluate the accuracy of ECMWF data with the observation data of the Iranian Meteorological Organization during the common time interval with the nearest point of ERA-Interim to the stations studied, the Pearson Correlation Coefficient (R), Coefficient of Determination (R2), mean squared error (MSE), root mean square error (RMSE), and normalized root mean squared error (NRMSE). The most important factor in determining the need for water is the accurate ETo estimation in each region, so the potential evapotranspiration (ETᴼ) values were calculated using the Penman-Monteith FAO method. To investigate the effect of climate change on water requirement and duration of growth, the daily micro scale dynamic data of the CORDEX project with a precision of 44% * 44% for the output of the ICHEC-EC-EARTH model under the two lines of 4.5 and 8.5 (RCP) was used for the period (2017-2037). In order to reduce the errors in the model estimates, the post-processing action of the estimated events was fulfilled. The Water requirement and growth season length apples were also noted. Then, considering that the highest amount of apple cultivars in the studied areas is autumn, the type of late fall apple is selected for evaluation. According to correlate each step of growing apples with thermal operating temperature, length of growing season and vegetative stages of apple tree were calculated using GDD. Results The statistical results between ERA-Interim data and observational data at the stations were examined and the accuracy of the database data was confirmed for both stations In the next section, in order to select the best model for the studied areas, the data of the base year of the growth season of the CORDEX project models was compared with the observational data. The ICHEC-EC-EARTH model The ICHEC-EC-EARTH has a lower error rate than the other two. Do post processing of historical events has been able to greatly increase the model's performance data. The results of two man-Kendall and Sen's slope at the Semirom station on the ETo observations were reduced during the growing season, but in the Urumia station, the slope is positive and incremental. The evapotranspiration potential observed in the growing season, under the RCP4 / 5 and RCP8 / 5 trajectory for stations, shows an incremental trend. At the Uromiyah station, the results of the ETo on the growth stages of the apple tree indicate an increasing trend for observational data in all stages. . For estimated data, the effective rainfall season in Urumieh station is more than Semirom, therefore, during the growth season of the apple tree, the Semirom station will need more water in the observation period and years of forecasting than the station in Orumiyeh. At both stations, in the observation period and the estimated data, the rainfall level is effective in the germination stage was more than other stages. In the course of 8/8 for both effective precipitation stations will increase compared to the observation period. Considering the evapotranspiration and precipitation during the growing season of apples, the results of simulations showed that under climate change conditions compared to the base period, the need for irrigation of apple trees at Urmia and Semirom stations was increased under both scenarios. The results from the comparison of the growth period of the base period and the estimated data at the stations under both scenarios indicate a decrease in the growth period in the future, which their trend was not statistically verified. Earlier heat supply due to increased temperature has led to some shortening steps. Decreasing the growth period in the scenario is 5.8 more than the scenario of 4.5. Conclusions Based on the evaluation methods, the ECMWF data estimation error with observational data was negligible, and the database data for the studied stations can be verified. The results showed that evapotranspiration in both stations is increasing during the growing season. The ETo increase in the growth season of the apple tree stations was predicted from the base period for the trajectory of 4.5 and 8.5 for the Semirom 4.14.7 and 7.99.7, respectively, and for Orumiye Station, 26.5 and 11.8, respectively, and however, this increasing process will raise the apple's need for water. The highest amount of evaporation and water requirement in the observed and estimated data has been occurred in the period of growth. At this stage, the lowest effective rainfall and the highest average temperature have occurred but generally the percentage of upcoming changes of germination stage was more than other stages. Earlier heat supply will reduce the growth period of the apple tree, in fact, the plant will complete its growth and reproduction cycle earlier, resulting in reduced yield, reduced quality and color, increased temperature and increased water requirement. Earlier heat supply due to increased temperature has led to some shortening steps.

The agriculture is the sector that uses most of fresh water resources. Since the water resources are always subjected to severe depletion, the agriculture sector requires using the water with high efficiency and more effective ways One of the procedures leading to improvement of water management productivity and ultimately to increase of water efficiency is the accurate estimation of the evapo-transpiration or estimation of water use efficiency of the crops. The remote sensing by giving an estimation of the degree of evapotranspiration (with little use of ground data) has a high potential for modification of cultivation patterns and management of water resources This research aims to determine the actual evapo-transpiration (need of water) of maize, which is an indigenous plant in the northern Khuzestan province, using the image processing of Landsat 8 in four passes include: 13 Aug, 14 Sep, 16 Oct and 17 Nov 2013 and also using the required metrological data based on Surface Energy Balance Algorithm for Land (SEBAL). The results showed that the amounts of needed water estimated by SEBAL model for maize in the initial growth stage, development stage, middle stage and the end stage are 5.04, 8.23, 5.55, and 1.46 mm per day respectively. The values from remote sensing were compared for values assessed by FAO- Penman-Monteith and evaporation pan methods and it was observed that MAE and RMSE are 0.45 and 0.18 mm per day compared to FAO- Penman - Montieth method. In sum, the results indicated that the SEBAL model is able to give answers with high accuracy and in short time and can be used as a beneficial and efficient tool in organizing water resources and meeting the plant water needs.

Satellites acquire data in low, medium, and high spatial resolutions. Freely-available high temporal resolution images are often acquired in medium (or low) spatial resolution and high spatial resolution images usually suffer from a low temporal resolution or from high costs. Moreover, high spatial resolution images are prevented to use in modeling of processes such as evapotranspiration due to the lack of thermal bands. Evapotranspiration mapping with a high spatial and temporal resolutions have been always one of the main subjects in the field of remote sensing. Daily evapotranspiration mapping with a 30 meter spatial resolution is the aim of current study. The case study of the research is Amir- Kabir agro-industrial farms. For this purpose, among 36 bands of MODIS image, those being more spectrally similar to Landsat bands were selected. Then, SADFAT and STARFM algorithms were applied on Landsat 8 and MODIS images to simulate visible and infrared bands with daily temporal resolution and 30-m spatial resolution. Afterward, the simulated bands were used as input for SEBAL algorithm to calculate actual evapotranspiration. Comparing the results with the actual evapotranspiration derived from FAO-Penman-Monteith equation indicated a RMSE of 2.53 mm/day and R2 of 0.69. Also, an RMSE of 0.68 mm/day and R2 of 0.94 were derived when the actual evapotranspiration derived from the downscaled bands were compared with that derived from the Landsat-8 bands. Accordingly, these results showed the efficient performance of the downscaling framework proposed in this study.

Evapotranspiration is significantly affected by global climatic changes as an essential component of both climate and hydrological cycles. Comprehensive analyses of the spatiotemporal changes of ETo enhance the understanding of hydrological processes and improve water resource management. The main objective of this study are to investigate and predict the temporal trend and spatial distributions of the reference evapotranspiration (ET0) during 1961-2014, 2021-2050 and 2051-2080 over Razavi Khorasan Province using observed grided dataset named CRU and four GCMs outputs. Data and methods: 2.1. study area
Razavi Khorasan Province is located in northeastern Iran. This province is located within the longitude and latitude of 56° 19” to 61° 16” E and 33° 52” to 37° 42” N. The climate of this area can be characterized as arid and semiarid with a long term annual precipitation of about 207.5 mm and a long term annual maximum and minimum temperture of 18.3°C and 9.3°C , respectivily.
2.2.data
Monthly maximum and minimum temperature data were collected from updated highr esolution (0.5°× 0.5°) gridded dataset of CRU initially released in 1999 by New et al., total 42 grid points in Razavi Khorasan province. After assessing the accuracy of the CRU data using 11 synoptic stations over this province, the monthly ETo values were calculated using Hargrives-Samani method to study the spatiotemporal variations in this variable. The impact of climate change on future spatiotemporal Eto, evaluated using four coupled atmosphere-ocean general circulation models (AOGCMs) under RCP8.5 scenarios. The parametric t-test and nonparametric Mann-Kendall test methods were used to analyze the temporal characteristics of annual ET during 1961-2005, 2021-2050 and 2051-2080. Results and Conclusions: The results were as follows: (i) generally, ETo increased from north to south across the province (ii) from 1961 to 2014, annual ET exhibited an increasing continuous trend across the area under study (iii) ETo also displayed a significantly increasing temporal trend during two future periods across Razavi Khorasan Province. (v). The difference between mean annual ETo values of two periods was statistically significant in all grid points covering this province. The results showed that these increases may lead to the increase in crop water requirements and aggravate the water shortage in this area in view of the increase in ET0 in response to ongoing climate change.
ETo play an important role in the agricultural and water resources management, and its accurate prediction will signify better planning and management of the water, agriculture and other sectors, hence, using outputs of GCMs can facilitate the sectors by reliably predicting the future climate change impact on ETo in this province.