جستجوی مقالات مرتبط با کلیدواژه « evapotranspiration » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

Evapotranspiration (ET) is one of the most important components of the hydrological cycle and an important factor in determining water demand, its spatial distribution and accurate estimation for many studies such as water balance, crop production simulation, program Irrigation planning and water resources management are very important. Also, using of geostatistical methods is one of the ways to estimate evapotranspiration in places without stations. In this study, SWAT hydrological model was used to simulate evapotranspiration of Samalghan watershed . To evaluate the simulation results, indices R2 , bR2 , NS was used. In the calibration stage, the coefficients of R2, bR2 and NS were equal to 0.74, 0.71 and 0.68, respectively, and in the validation stage, they was equal to 0.69, 0.62 and 0.59. .Then, using the results of spatial analysis of data in this study, the exponantial model was selected as the most appropriate model for zoning due to the lower RMSe value and higher correlation.

Many of the environmental problems are caused by the changes in the main components of the hydrological cycle. However, water balance modeling can help to better understanding the components of the hydrological cycle in order to develop appropriate management options. The purpose of this study is to calculate three important components of surface water balance using the WetSpass model and evaluate the model in Hamadan-Bahar Watershed located in Hamadan Province on a monthly time scale. The results of the model evaluation in the study showed that the coefficient of determination between the observed and simulated runoff in the calibration and validation period is equal to 0.79 and 0.83, respectively. Groundwater nutrition assessment was also performed according to manual calculations of the variable for 2012-2013. Then, the results of Kramer correlation coefficient between spatial distribution maps of runoff, actual evapotranspiration and groundwater recharge were investigated with input maps of the model. In general, due to the importance of evapotranspiration in water balance calculations, the evaporation and transpiration maps of the model were evaluated separately for different uses. The evaluation results confirmed the capability of the WetSpass model in simulating runoff, evapotranspiration and groundwater feeding with an acceptable accuracy. The results of spatial distribution maps of runoff, actual evapotranspiration and groundwater recharge indicate a high correlation between evapotranspiration component with land use (0.54), soil texture (0.45), evapotranspiration potential (0.42) and temperature (0.31). Also, these results indicate a high correlation between runoff components with land use (0.62) and soil texture (0.58), and average correlations between groundwater recharge component with land use (0.32) and soil texture (0.34). Therefore, land use and soil texture were the first and second factors affecting the distribution of surface balance components, respectively.

Sustainability of groundwater resources means ensuring the permanent availability of essential groundwater services for a long-time. This research was conducted to investigate the sustainability of groundwater resources in the prohibited plain of Behshahr- Bandar-e-Gaz by using water expoliation and green water scarcity indices. Initially, the green water deficit index was calculated based on the concept of water footprint. The water exploitation index was obtained according to the long-term average of annual fresh water resources based on the components of well and qanat discharge, total recharge and return flow. The indices were calculated for the common cropping pattern of the region (spring wheat and rice) for a 33-year period (1982- 2015). The green water deficit index was 2.68 and 2.54 for spring wheat and rice cropping system, respectively. Also, the water exploitation index was 18 percent and 17.8 percent, respectively. Increase in evapotranspiration under spring wheat cropping reduced soil water content and ultimately led to excessive instability of groundwater resources in the study area. Based on the results, the use of water expoliation index can improve the sustainability of groundwater resources in Behshahr Bandar-e-Gaz plain rather than the green water scarcity index.

Nowadays, global climate change has been observed which had an impact on both surface and groundwater resources management. The main objective of this research is change detection of groundwater fluctuation caused by climate change in Borkhar Plain, Isfahan Province. In this way, both Mann-Kendal and Sen’s slope non-parametric analysis were used using 19 piezometric wells data for the period of 1991-2019. Pearson correlation matrix along with correlation between climatic elements including temperature, precipitation and evapotranspiration (Thornwhite) with water table levels were determined. Based on this, a multivariate regression model was developed to model the annual time series at a confidence level of 0.95. Climatic factors of 2080-2099 period were simulated using the output of HadCM3 model through Lars-WG downscaling model for Maymeh Station under two scenarios A2 and A1B and based on the developed regression model, the water level of Borkhar Plain was simulated. The results showed that in the base period, the water table in the study area has been decreased with an annual slope of 47 cm per year. Correlation analysis showed that the three climatic elements of precipitation, temperature and evapotranspiration in a linear composition modeled 0.75 of the annual groundwater changes in the plain. The results of the exponential microscale model implemented on HadCM3 data showed that in the period 2080-2099 under both scenarios, the groundwater level of the region will decrease between 15 to 17 meters compared to the base period.

Drought is a long-term natural phenomenon when the average precipitation rate is less than that of the normal periods. As a natural phenomenon, drought has turned into a  natural disaster occurring throughout Iran in recent decades with all its associated consequences. On the other hand, although rainfall is considered as the main indicator of water availability, the temperature is also an important factor in this regard, as it controls the evapotranspiration rate. Therefore, parameters such as precipitation and temperature can be used as indicators for analyzing the drought. Moreover, identifying drought trends based on previously recorded data, noting their occurrence in different times and places, and studying their variation over time play a significant role in managing water resources. It should be noted that the purpose of trend analysis is to determine the decreasing or increasing nature of trends in a series of observations performed for a random variable over time.

The Standardized Precipitation Evapotranspiration Index (SPEI) is a meteorological drought index that considers the variability of both precipitation and temperature in predicting drought conditions in a region. Enjoying a multi-scale ability to monitor and analyze drought in different scientific disciplines, the index fulfills the requirements of a drought index, being recently used in a variety of drought analyses. This study measured SPEI using precipitation and temperature data from eleven meteorological stations in Sistan and Baluchestan Province, Iran, during the study period.  The Drought events were then identified via the Standardized Precipitation Evapotranspiration Index over both 3 and 12-month timescales. The total geographical area of Sistan and Baluchestan Province is approximately 187,000 km2, located at 25° 03 N to 31° 28 N (latitudes), and 58° 47 E to 63° 19 E (longitudes). The province has an arid and semiarid climate with a mean annual rainfall of about 100 mm. The monthly precipitation and temperature data recorded at the stations were obtained from the Sistan and Baluchestan's Meteorological Organization. One of the commonly used tools for detecting changes in climatic and hydrologic time series is trend analysis. Mann-Kendall is a non-parametric trend test commonly used to assess the significance of trends in time series. This study used both nonparametric trend tests (Mann-Kendall) and graphical Mann-Kendall model trend analysis (statistical significance at 95% confidence level) to explore the drought trends in each station. The purpose of trend analysis is to determine whether the time series of a random variable's observations generally increases or decreases over time. While parametric trend tests are more powerful, it is non-parametric trend tests are widely used, as they can accommodate outliers in the data and require independent data.

The study's results indicated no negative trend in precipitation but revealed a significant trend in temperature. The SPEI values measured for the short-term time scale (SPEI 3) showed a statistically significant downward trend for all stations, which corroborates the occurrence of more critical drought periods in recent years. Moreover, the study of the frequency of drought occurrence in the stations during 10-year periods suggested an increasing trend in the occurrence of drought in recent years. As for the maximum drought index, it could be said that the index's value has typically increased in recent years, that is, more severe droughts have occurred. According to the results, the most severe drought belonged to the Khash station, and the wettest period was found in the Chabahar station.

This study sought to identify possible drought trends in Sistan and Baluchestan province using the Mann-Kendall test, considering the fact that detecting such changes offer valuable information for future water resources management. Accordingly, the analysis of previous drought events showed that more severe droughts are expected to occur in the years to come. Although this study did not seek to find possible causes of decreasing trends, the results presented herein could be used as a benchmark for further analysis of the consequences of climate change. It could be argued that low precipitation and high potential evapotranspiration (PET), especially the PET caused by rising temperature, are the main factors that could influence drought in the future. Therefore, the influence of the PET should not be ignored in drought analysis, and it is suggested that more comparative studies of different drought indices be conducted on analyzing future climate change-induced droughts.

 The accurate estimation of actual evapotranspiration (ETA), i.e. crop water requirements, is an important issue for irrigation water allocation at fields and improving water efficiency. In the present study, ETA for Sorghum crop was estimated using surface energy balance algorithm for land (SEBAL) and by employing Landsat8 satellite images; meteorological data and DEM map and then compared with the measured values of lysimeter.

 For carrying out the sensitivity analysis, the key parameters of SEBAL algorithm was altered at the range of ±10 , ±20 , ±30 , ±40  , ±50  and resultantly the variation of ETA corresponding to decrease and increase of these parameters was investigated. The changes of key parameters on the days of 206, 238 and 254, based on Julian days calendar, were evaluated at eight points with different vegetation densities. Albedo parameters have moderate to high sensitivity, so that the albedo parameter has medium and high sensitivity in the areas with ET> 10 and ET <10, respectively.

 The results of SEBAL showed the value of accuracy indices were acceptable at a significant level of 95%, while compared with those of lysimeter measurements. The results of the sensitivity analysis also showed the surface temperature and input shortwave radiation are more sensitive especially at the areas having low ETA values. The wind speed and

In general, in addition to high economic efficiency compared to other conventional methods, the SEBAL algorithm has a good efficiency in estimating ET. Also, performing sensitivity analysis and determining the key input parameters, while increasing the accuracy of measuring those parameters, can greatly improve the modeling results.

Accurate estimation of reference crop evapotranspiration (ETo) is important in hydrological studies and water resource management that can influence the planning and policies for optimal allocation of agricultural water resources. For this purpose, in the present study, sensitivity analysis was employed to evaluate the effects of the changes in meteorological parameters (vapor pressure deficit (VPD), Mean Temperature (Tmean), net solar radiation (Rn), wind speed (u) and actual vapor pressure (ea)) on reference crop evapotranspiration (ETo) within the possible range of ±20% on a daily and growing season scale. ET0 was calculated by The Food and Agriculture Organization of the United Nations (FAO) 56 Penman-Monteith approach using long-term climate data from 13 meteorological stations of Khorasan Razavi province in northeast Iran. The sensitivity analysis indicated that ETo changes positively with vapor pressure deficit, mean temperature, net solar radiation and wind speed, while it changes negatively with actual vapor pressure. Also, over the whole period, ETo was most sensitive to vapor pressure deficit (VPD), followed by mean temperature (Tmean), net solar radiation (RN), actual vapor pressure (ea) and wind speed (WS). In the the warm growing season, ETo was most sensitive to vapor pressure deficit (VPD), followed by mean temperature (Tmean), net solar radiation (RN), wind speed (WS) and actual vapor pressure (ea) while, in the cool growing season, ETo was most sensitive to vapor pressure deficit (VPD), followed by actual vapor pressure (ea), Mean Temperature (Tmean), net solar radiation (RN) and wind speed (WS). The results showed that the sensitivity of ETo in different stations and different growth periods is different. The findings of this study showed that the importance of effective parameters on the reference crop evapotranspiration (ETo) was different between the hot and cool growing season of the region, which should be considered in sustainable planning of water resources and management of agriculture in Khorasan Razavi regions for development of adaptation strategies in arid climatic conditions.

Due to climate change and changes in plant water needs, it is necessary to evaluate climate change in the coming decades with the aim of appropriate environmental planning to adapt to future climate conditions. The main factor of water resource consumption in arid and semi-arid regions is agriculture and consequently evapotranspiration, so knowledge of the change and its prediction plays an effective role in the planning, development, and management of water resources. The present study uses the Lars WG Model. Using this model, the temperature in three time periods (2011-2030, 2046-65, and 2081-2100) with four general atmospheric circulation models (IPCM, INCM3, HADCM3, and NCCCSM) in three different scenarios (world with sustainable development, rich world, and the isolated world) has been calculated, then the evapotranspiration changes were examined in the Southeast of the country in the three mentioned periods for eight stations. For this purpose, the Thornthwaite equation was used to calculate evapotranspiration. The results show an increasing trend of temperature followed by an increase in evapotranspiration in the coming period. The average increase in evapotranspiration in the NB1 model is less than other models and has the lowest value and the highest value in Kerman and Iranshahr, respectively. The relative changes of evapotranspiration until 2099 in Kerman and Iranshahr stations are 10.692 (mm / day) and 23.194 (mm / day), respectively

In this study, water use efficiency index (WUE) was used to assessing the effect of drought on the carbon and water cycle. To calculate this index, we used the gross primary product (GPP) and evapotranspiration (ET) products obtained from the MODIS sensor, and the trend of their changes and reaction of this index to drought were calculated for the period 2017-2001 in Fars province. Finally, we assessed the land degradation and desertification in different land uses for study area. The results showed that the indices of evapotranspiration, GPP, water use efficiency, and drought increased by 75.25%, 29.9%, 78.51%, and 67.23%, respectively. The effects of drought on evapotranspiration in agricultural lands and grasslands showed more than 67% positive relationship and also, in these land uses, we observed a significant positive relationship (33.4% and 12.5% for the agricultural lands and grassland, respectively). However, in shrubs lands, and savannas, it is more than 66.6% and 87.5%. The effect of drought on water use efficiency in grassland showed that more than 87% of these areas have a positive relationship. The effectiveness of water use efficiency in plants shows a positive relationship in 40.9% in this area, of which only 0.9% has a significant positive relationship. The negative relationship of this land use is about 59.1% of it. Of this negative amount, only 1.6% of the area had a significant negative relationship. The study of this relationship in the use of savannas shows 75% of this area, which includes 1.5 square kilometers.

Evapotranspiration is one of the most important components of the hydrology cycle for planning irrigation systems and assessing the impacts of climate change hydrology and correct determination is important for many studies such as hydrological balance of water, design of irrigation irrigation networks, simulation of crop yields, design, optimization of water resources, nonlinearity, inherent uncertainty, and the need for diverse climatic information in estimating evapotranspiration have been the reasons why researchers have used artificial intelligence-based approaches. In this study, to estimate accurately the daily reference evapotranspiration between 2009-2018 in Zabol city, north of Sistan and Baluchestan province,  first was used a standard FAO-Penman-Montith method and Zabol synoptic station meteorological data- the ETo reference transpiration is calculated and then presented by various scenarios of meteorological parameters including: maximum, minimum and mean temperature, maximum, minimum and mean humidity, precipitation, sunshine, wind speed and evaporation as inputs for deep learning models, Random forest and generalized linear model were attempted on a daily time scale More accurately. In estimating daily evapotranspiration in these models, 25 scenarios were selected from meteorological data combination and FAO-Penman-Monteith method was used to evaluate the models. Among the investigated scenarios, the M5 scenario (maximum, minimum and mean temperature, maximum, minimum and mean humidity, wind speed, pan evaporation) for deep learning model with minimum error (0.517) and highest correlation coefficient (0.517). 0.996 had the best performance among the above models. The deep learning model showed more accuracy and stability than other models. Hence, this study is recommended a deep learning model for estimating reference plant evapotranspiration in Sistan plain.

Climate change is the most important global challenge, particularly in semi-arid regions. The objective of this study was to investigate the effect of changes in climatic parameters on drought and desertification hazard in Kermanshah province, Iran, using precipitation, temperature, evaporation and relative humidity data during period of 1992 and 2018. Desertification risk was assessed through UNEP index. The results of this study showed that during the last decade, climatic elements in Kermanshah province have undergone significant changes. Among all climatic parameters, changes in air temperature were noticeable, so that the maximum, minimum and average temperature at most stations in Kermanshah province has increased significantly. Relative humidity decreased at most stations and precipitation decreased. These changes have been more evident and significant in Kermanshah city than in other parts of the province. The study of SPEI index showed that all part of the provinces impacted by drought and the southwestern areas are facing with more severe drought.The trend of drought changes in Kermanshah province in most parts of the province during the last decade compared to the decades also showed, an increase in the drought intensity and duration and a decrease in the length of wet duration. The desertification risk is observed in north. The highest desertification risk is observed in the southwestern regions of the province, mainly Somar, Naftshar and Ghasreshirin, but the trend of changes only in Kermanshah showed increased desertification risk due to significant changes in climatic elements.

Limitations of physical and experimental methods for estimating the evapotranspiration have been rationalized the employment of remote sensing technology to solve the energy balance equation in recent years. In this study, in order to investigate the evapotranspiration factor in the application of the HEC-HMS model and to optimize the flood estimation, using Landsat 8 Satellite Images (nine images) and the meteorological data related to the Kelestan Station and the SEBS Evapotranspiration Model for the period 2015-2017, ET values were calculated in the region of Kelestan Located in the Northwest of Shiraz, and the results were compared to the FAO Penman-Monteith equation to verify the accuracy of this model in the region of Kolding with water body. Evaporation in HEC-HMS including the direct evaporation of water, evaporation from soil surface, and transpiration of plants was estimated as an average elevation. In this study, we attempted to replace the actual evapotranspiration in the HEC-HMS model, The amount of runoff from the precipitation is calculated more accurately. The results showed that after scrutinizing the ET input, the simulated flood correlation with the measured flood was increased with R2 from 92 to 99%, and RMSE from 0.14 to 0.01, respectively. The results also indicated that the use of Landsat 8 Satellite Images and SEBS model is a suitable tool for estimating actual evapotranspiration in mountainous and field areas in hydrological studies. This research is for the performance of SEBS in determining the spatial and temporal distribution of evapotranspiration in a mountainous and hydrological area. Because the calculation of ET in hydrological models can improve the results and increase the accuracy of these models.

One of the most important issues in water resources management in agriculture is determining the plant water requirement by estimating the actual evapotranspiration of the crop. One of the empirical methods for determining the plants and crops evapotranspiration is the method mentioned in FAO 56's report. One of the main problems of this method is the KC coefficient estimation, especially when the percentage of crop cover, irrigation methods, and other factors in the region varies. The aim of the present study was to estimate the KC and pistachio plant's (Pistacia vera L.) KC-NDVI relationship in different stages of pistachio phenology in Pistachio orchards of Abarkuh desert margin in Yazd province. The KC-NDVI relationship has the main role in plant water management requirements. First, the actual daily evapotranspiration rate over the 16 different periods corresponding to a full pistachio's growth period is calculated. Then, by dividing the actual plant evapotranspiration to evapotranspiration of reference plant on the same day, the Kc maps were created. Finally, the relationship between KC and the NDVI index was obtained. Based on the results, there was a significant correlation between the pistachio plant coefficient and the NDVI index at a 99% level (P-value <0.01). At the beginning and end of the pistachio growth period, the lowest correlation was found between the pistachio plant coefficient and the NDVI index. The highest correlation was observed in the mid-growing season, which is coincident with the peak of heat and evapotranspiration. In general, the pistachio vegetation coefficient is between 0.3 and 0.9 concerning NDVI index in the study area. Relationship between KC and NDVI at the 1)beginning of growth season, 2) development stage, 3) mid-growth stage, and finally 4) harvest season were KC-1 = 1.66 NDVI + 0.261, KC-2 = 1.29 NDVI + 0.338, KC-3 = 2.10 NDVI + 0.147, KC-4 = 1.21 NDVI + 0.231, respectively.

Water balance and flow analysis within a basin is particularly important in terms of water development and utilization programs. Therefore, the purpose of this study is to evaluate and predict the outflow rate of Baghan watershed in Bushehr province. The data required for the implementation of the rainfall and discharge models were used to obtain the precipitation data of the Baghan Meteorological Station and the discharge of Baghan Hydrometric Station from 1981 to 2010. The Salas model is derived from a number of simple sub models that characterize different flow processes in the basin such as surface runoff, infiltration, evapotranspiration, deep infiltration and base flow. Error squares were used to calibrate the function model. The results of this study showed that the highest amount of rainfall in the basin was evacuated from the basin by evapotranspiration. The results showed Relative root mean square error before and after optimization of the coefficients of the four-variable Salas model decreased from 2.18% to 1.5% and the mean absolute error from 10.13 to 0.73. and mean error of the Salas four-variable model showed that in the years when the discharge value is almost average, the simulation value is very close to the observed value, and when the discharge value is much higher than the normal years, the simulation value is the less than its observed value.

The study of drought as a natural phenomenon that affects the lives of most people is very important. According to researchers in the field of drought, rainfall, temperature, evaporation, wind and relative humidity have been shown to play an important role in drought. The low variety of data required and the simplicity of calculating the SPI index led to its widespread use. The effect of increasing temperature in drought intensification is far more than the decrease in rainfall, which can confirm the effective role of temperature in strengthening or weakening of drought. Based on this, the SPEI index can be used as the appropriate index for determining the drought. In our hydrological studies, we try to fit the empirically measured data into a proper fitting function. And the best function that matches the data is chosen as the probability distribution function to derive the value of the variable for each probability. This research seeks to find the best distribution function for the SPEI index at the stations studied in Tehran province and also compares the SPI and SPEI indices at different time intervals. In this research, monthly precipitation and temperature data were used for Shemiran, Abali, Mehrabad and Tehran stations in Tehran province in 2017-1987. After qualitative control and correction and completion of statistics, statistical analysis of precipitation, based on the standardized precipitation index (SPI) and statistical analysis and dispersion analysis, are based on the standardized precipitation evapotranspiration index (SPEI). The values of the SPEI index are calculated using four Fatigue life, Weibull (three parameters), Loglogestic and kumaraswamy functions. Relationships (1) and (2) and (3) and (4) are used to calculate various cumulative distribution functions in the SPEI of the index. Fatigue life Weibull Log logistic kumaraswamy In order to investigate the most suitable distribution function compatible with Di, P-value comparison was performed based on Kolmogorov –Smirnov test ،Also to check the compatibility of the two indexes, graphs were plotted 24,12,6,3,1 and 48 months. To find out the degree of compatibility, we used the absolute value graphs of Difference of Two Indices. The results of computing and comparing the SPI and SPEI index indicate that in general, all stations in a drought condition are largely consistent and only in short periods of this adaptation are confused. Also, in comparison to the severity of drought between the two indices, the SPI index shows a lower intensity of drought and it can generally be concluded that the SPEI index shows the dry weather in terms of severity. Also, this index shows the beginning of drought in shorter time intervals, which can be attributed to the sensitivity of the SPEI index to rainfall variations and to include the temperature parameter in this index. In the short intervals, two indicators have a better match, and in the long term (24-48 months), the two indicators do not fit well. Abali station displays the best fit with the least error in all time intervals. The reason for the suitability of the Abali standardized evapotranspiration index station to show the overlap between the two SPI and SPEI indicators is the maximum rainfall and the minimum temperature and minimum evapotranspiration between stations however, it can be concluded that the drought index is well-matched in wet weather conditions with low temperatures. The difference between the two indicators in the hardest case in 1997 was 0.63, which means that each year, when the standardized rainfall index is reduced, the Standardized Precipitation Evapotranspiration Index is also declining. It can be concluded that these two indicators are in good agreement at this time interval and one can estimate one with a mean error of ± 0.209on the other consequently, reducing or increasing rainfall can directly affect the reduction and increase of evapotranspiration and temperature. In this research, it is assumed that, in addition to the spatial variation that causes changes in the statistical distribution, the annual variations of Di also confirm this hypothesis So, in calculating droughts or other climate studies, this should be considered, since rainfall, evapotranspiration, and temperature vary in different seasons, and therefore, in terms of statistical distribution, they act differently, for example The stations under study in Tehran province in the middle of June till the end of summer are followed by logistical distribution and in the middle of the warm year to late spring, more diverse statistical distributions are followed. The results showed that the behavior of both SPI and SPEI indicators in the monthly time intervals, especially in wet areas (Abali station), and in the 12-month period are very similar. It was also found that the two indicators did not match the annual time interval and that the same behavior of the two indicators could not be expected in the study of drought with annual data. The severity of all drought events, especially the most severe droughts, has been higher by the SPEI index for all periods of time. This is due to the sensitivity of this index to precipitation variations. Although rain has a special role in the diversity of drought time, the effect of temperature is significant and increases the phenomenon of drought. Based on the results, standardized evapotranspiration index has high accuracy in addition to having the main advantages of the SIP index, such as multi-variability and the use of minimum parameters of meteorology.

Evapotranspiration is a major component of the hydrological cycle which shows the amount of water loss. Since the amount of evapotranspiration is directly associated with climate variables and is related with the amount of changes in climate parameters, particularly temperature plays a key role in this regard. Therefore, in this study, possible impacts of climate change on evapotranspiration rate are estimated in the Lake Urmia Basin as a wet basin in the country. The basin nowadays is faced with drought and reduction of water level. Predictions of the changes in the lake, were examined Under scenarios A1B, A2, B1 and B2 using LARS-WG and SDSM Statistical Downscaling models and HadCM3 general circulation model output in the next three periods (2030-2011, 2065-2046 and 2099-2080) . Using the predicted climate parameters changes, Evapotranspiration rates in the basin in monthly and seasonal periods, was calculated using Hargreaves Samani and Priestley Taylor. The results showed an increase in long-term average minimum temperature in the basin between 0.2 to 3.4 degrees and a maximum temperature increase of between 0.9 to 2.9 degrees in future periods compared to the base period (1990-1961). The estimate of evaporation rate shows an increase in monthly and seasonal time series in future affected by the temperature. The increase would be between 2.4 to 15 percent on long-term average in the basin. The results can be used in the management of groundwater and surface water resources, irrigation and drainage projects, estimating crop water requirements, irrigation scheduling and environmental studies and watershed plans.

Evapotranspiration process is a key element in hydrological simulation of water supply, rainfall-runoff models, infiltration calculations and drought prediction models. Recently, several equations were used for estimating annual, monthly and daily evapotranspiration in the world. In this study, the potential evapotranspiration of Taleghan watershed was estimated by three methods in the SWAT model including Priestley Taylor, Penman-Montieth and Hargreaves methods. The influence of applying these methods were evaluated on simulated streamflow of the Taleghan watershed in the calibration (1998 - 2003) and validation (2003 - 2005) periods, using determination coefficient (R2), root mean square error (RMSE), Nash–Sutcliffe performance coefficient (NS) and skew index (PBIAS). Results revealed that the maximum and minimum values of simulated evapotranspiration and consequently, simulated runoff were related to the Hargreaves and Priestley Taylor methods, respectively. Moreover, investigation of statistic coefficients showed that there is no much difference among the three methods. Results of ANOVA also confirmed that there was no statistically significant difference at the 99% level among the simulated mean monthly flow using the three methods. In conclusion, the Hargreaves method provided better results than the two other methods during calibration and validation periods.