جستجوی مقالات مرتبط با کلیدواژه « پنمن مانتیث فائو » در نشریات گروه « آب و خاک »

Class A pan evaporation method as one of the most common methods for reference evapotranspiration (ET0) estimation has been widely used in the world due to its simplicity, relatively low cost, and ability to estimate daily ET. In this study, the performance of 8 empirical methods consisting of Allen and Pruitt (1991), Cuenca (1989), Snyder (1992), modified Snyder, Pereira, et al. (1995), Orang (1998), Raghuwanshi and Wallender (1998), and FAO/56 were analyzed to estimate class A pan coefficient and ET0 at Fasa synoptic station located in Fars province. The calculated pan evaporation coefficients from the above equations were compared with measured pan evaporation coefficients which were obtained from the ratio of evapotranspiration calculated by the FAO-Penman-Monteith method to the rate of evaporation from the pan. The results showed that all empirical methods did not predict pan coefficient values well (R2 < 0.3 and NRMSE > 0.25). The comparison results between ET0 from empirical methods and ET0 obtained from FAO-Penman–Monteith indicated that the FAO/56 method had the best performance (R2 = 0.72 and NRMSE = 0.3). To increase the accuracy of empirical pan coefficient equations, these equations were modified with eight years (2007-2015) of meteorological data from the Fasa synoptic station and validated using two years of independent data (2015-2017). The results showed that the accuracy of all empirical models was improved and the Cuenca equation with NRMSE = 0.16 and R2= 0.63 was selected as the best equation for pan coefficient estimation and ET0 (R2 =0.85; NRMSE =0.18) in Fasa region. The sensitivity analysis revealed that the estimated pan coefficient is more sensitive to wind speed, followed by relative humidity, fetch distance, the slope of the saturation vapor pressure curve, sunshine hours, and air pressure. According to statistical results and sensitivity analysis, an equation was expanded for the Fasa region and other areas with the same climate.

An experiment was conducted in a commercial greenhouse to determine cucumber (Negin cultivar) evapotranspiration and crop coefficient in two seasons of winter and spring cultivation in Hamedan province. Irrigation was done to meet 100% of the water requirement based on reaching the suction tensiometer to the field capacity (40 to 50 cm). The soil water balance was used to estimate plant evapotranspiration in the greenhouse. Stanghellini and FAO Penman-Monteith evapotranspiration methods were 214.2 and 181.5 mm in winter and 222.3 and 227.6 mm in spring, respectively. The evapotranspiration ratio by the FAO Penman-Monteith method inside and outside the greenhouse in winter and spring cultivation was 0.8 and 0.81, respectively. The actual evapotranspiration from soil water balance in winter and spring cultivation were 148.2 and 210.4 mm, respectively. The results showed that the average crop coefficient in the initial, middle, and final stages of the growing season in winter planting was 0.69, 1.43, and 1.05, and in spring planting were 0.63, 1.15, and 0.9, respectively. The results of this study showed the necessary scientific basis for optimizing irrigation and saving water consumption, creating appropriate irrigation planning, and improving the crop water use efficiency in the greenhouse. Also, by reducing excessive water consumption, it can reduce energy consumption and provide a maximum increase in product production efficiency and economic efficiency. The investigation of evapotranspiration, crop canopy growth, and humidity changes during the growing season also showed that it is necessary to prevent the development of plant diseases, to use a higher ventilation level or forced ventilation in greenhouses.

In this study, the seasonal applied water and physical and economic water productivity of soybean were evaluated through monitoring 37 farmers’ fields (with furrow/border irrigation systems) in Moghan Plain, Ardabil Province, Iran, during the 2020-21 growing season. The net soybean water requirement during that growing season and its 10-year mean value ranged from 431-691 mm and 442-671 mm with a mean of 542 and 543 mm, respectively. The mean seasonal total applied water (irrigation + effective precipitation) and the grain yield were 6554 m3 ha-1 and 2.90 ton ha-1, ranging from 5005-10009 m3 ha-1 and 2.05-4.12 ton ha-1, respectively. The mean seasonal total applied water for spring soybean (7906 m3 ha-1) was significantly (P < 0.01) higher than its corresponding value for summer soybean (6390 m3 ha-1). Total water productivity (WPI+Pe) and economic water productivity (WP$) ranged from 0.18 to 0.30 kg m-3 and 15.21 ´ 103 to 62.40 ´ 103 Rials m-3 with a mean of 0.24 kg m-3 and 33.19 ´ 103 Rials m-3, respectively. In most of the studied farms (70% of total cases), the grain yield was higher than the minimum expected threshold for irrigated soybean (2.5 ton ha-1). The results indicated that reasonable levels of grain yield and water productivity indices can be achieved by applying five and three irrigations for spring and summer soybean, respectively. The mean water application efficiency over soybean growth stages in the studied fields ranged between 50-82%.

The FAO Penman-Monteith (FAO-56 PM) model is proposed as a standard model to estimate reference evapotranspiration (ETO) in various climates. Different models are used to estimate the total solar radiation (Rs) as one of the essential inputs of this model. This study aimed to calibrate and validate four Rs estimation models (Ångström-Prescott, Hargreaves-Samani, Mubiru et al., and Chen and Li) in Ahvaz (with arid climate) and Hamedan (with semi-arid climate) stations during the 1992-2020 climate period and the effect of these models on the ETO estimation. The coefficients of these models were calibrated by the intelligent shuffled frog leaping algorithm (SFLA). To evaluate the efficiency of these models, the estimated Rs values were compared with measured values. Based on the root mean square error (RMSE), the coefficient of determination (R2) statistics and Nash-Sutcliffe, the A-P model with RMSE=1.929, R2=0.918, NS=0.896 and Mobiro et al. model with RMSE=2.925, R2=0.875, NS=0.860 showed better performance than the other models in Ahvaz and Hamedan stations, respectively. A decrease of about 20% was observed in the percentage of ETO difference between, the calculated and the estimated Rs compared to the measured Rs in 2 stations at all of the models.

The main purpose of this study was to calculate the net irrigation requirement of agricultural products in the Qaleh Chay catchment in the current climatic conditions and evaluate it with the data of the National Water Document (NETWAT). For this purpose, the reference evapotranspiration was calculated by the Penman-Monteith-FAO method for the years 2013 to 2019. Subsequently, the plant coefficients were modified according to the guidelines of FAO 56. Then the effective rainfall and net irrigation requirement were calculated. Finally, the net irrigation requirements of the region were compared with the data of the National Water Document. The results showed that the values obtained in this research were in all cases higher than the values mentioned in the National Water Document. This difference was due to the fact that the information used for the calculations in this study was from the year of establishment of the meteorological station of the catchment (2012), while the calculations in the national water document were related to meteorological stations in neighboring cities and years before 1378. Also, increasing temperature and decreasing rainfall in recent years have increased the irrigation requirement compared to previous years. Finally, it is suggested that the estimation of irrigation requirements be done according to meteorological data of recent years to be closer to reality.

Greenhouse gas emissions cause warming and impacting climate components and consequently affecting water demand in agricultural sector. This study aimed to identify the impact of climate change on reference evapotranspiration in Mazandaran province. For this purpose, climatic data of Gharakheil, Babolsar, Noshahr, and Ramsar weather stations were used during 1985-2005. Meteorological data for a future period (2006-2081) were estimated using the CanEMS2 model under RCP2.6, RCP4.5, and RCP8.5 scenarios and the reference evapotranspiration was calculated using climatic data for future periods. The SVM model was used for downscaling the climatic parameters. The results showed that the maximum and minimum temperatures would increase over the coming period and the annual maximum temperatures in the selected meteorological stations under RCP2.6, RCP4.5, and RCP8.5 scenarios will be increased by 1.5, 2, and 3° C, respectively. Minimum temperatures in the selected stations under RCP2.6, RCP4.5, and RCP8.5 scenarios will be increased by 3.8, 5.7, and 5.7° C, respectively. Precipitation will also be reduced between 8 to 29 percent over the selected weather stations. The results show that the reference evapotranspiration will be increased or decrease in some months in all meteorological stations compared with the base period. The highest increase in maximum temperature under different climatic scenarios will be occured in March between 1.4 to 6.4° C at Babolsar Meteorological Station, and the highest increase in minimum temperature under different climatic scenarios will be occured between 3.8 to 5.7° C in February at the Gharakheil Meteorological Station. The results showed that the highest and lowest percentages of reference evapotranspiration changes would occur in October and March, respectively. Evaluation of the reference evapotranspiration at the selected stations shows that the percentage of evapotranspiration variations in different months varies between -16.1 to 25.7% and the highest increase and decrease in reference evapotranspiration will occur in Ramsar and Gharakheil stations, respectively.

Date palm is an important horticultural crop in Iran. In this research, after measuring the amount of plant evapotranspiration during first to third years by lysimeter, equal 274.3, 402.7 and 597.2 mm, respectively, plant evapotranspiration was estimated by five methods of FAO Penman-Monteith, FAO Blaney-Criddle, FAO pan evaporation, corrected Jensen-Heise and Hargreaves-Samani. Statistical analysis of linear regression of evapotranspiration equations compared to lysimeter showed that all equations were significant at 1% level of probability. The adjusted coefficient of determination (R2adj) was between 0.94 (FAO pan evaporation) and 0.97 (FAO Blaney-Criddle), while modeling efficiency (EF) varied from 0.93 (FAO Penman-Monteith) to 0.95 (FAO Blaney-Criddle). Minimum and maximum of maximum error (ME) were related to Hargreaves-Samani and FAO pan evaporation equations, respectively. Minimum and maximum of normalized root mean square error (nRMSE) were in FAO Blaney-Criddle and FAO Penman-Monteith equations, respectively. Also maximum and minimum of coefficient of residual mass (CRM) were in FAO Blaney-Criddle and corrected Jensen-Heise equations, respectively. The FAO Blaney-Criddle equation had the most fitting accuracy in Ahvaz region. However, the methods of FAO Penman-Monteith and FAO evaporation pan had also well accurate.

Estimation of evapotranspiration is,one of the main components of the hydrological cycle, and is essential for irrigation scheduling, water balance, irrigation system design and management and crop yields simulation. Unlike conventional methods remote sensing estimates evapotranspiration in different spatial scales. Therefore, the aim of this study is to estimate evapotranspiration using OLI sensor images and SEBAL algorithm in the Dasht-e-Naz area, Sari, Iran. To evaluate the results, evapotranspiration estimated by the reference method, Penman-Monteith-FAO, was compared with SEBAL algorithm. Strong and significant correlation was obtained between these two methods (R2=0.93), Low error of estimation by SEBAL compared with reference method (RMSE=1.14) and low absolute difference between the SEBAL and Penman-Monteith-FAO (MAE=0.96) indicates that there is a good match between estimated values by SEBAL algorithm and Penman-Monteith-FAO standard method. This study showed that OLI sensor images and SEBAL algorithm could satisfactorily estimate actual evapotranspiration in the Dasht-e-Naz area, Sari.

Accurate estimation of reference crop evapotranspiration (ETo) plays an important role in water resources management and planning in dry regions. In this study, accuracy and ability of Adaptive Neuro- Fuzzy Inference System (ANFIS) in estimating ETo was evaluated. Daily meteorological data, including air temperature, relative humidity, sunshine hours, vapor pressure deficit, wind speed and solar radiation ofMinab synoptic station, Hormozgan province, during 2006 to 2011 were used for modeling. The evapotranspiration values estimated by the FAO-56 Penman-Monteith equation (PM) were considered as the reference values for calibrating ANFIS model. The performance of the developed model with different input combinations was also compared with the empirical models, namely, Hargreaves-Samani (HS) and Blaney- Criddle (BC). The root mean square error (RMSE), mean absolute error (MAE) and the coefficient of determination (R2) were used for comparing the results of ANFIS, HS and BC methods with reference method (FAO-56 Penman- Monteith equation). The results showed that the ANFIS was a more appropriate method for estimating the ETo inMinab and this model with 6 inputs (with 3 membership functions and Gaussian mixture model) had a better performance than the other considered methods with the R2, MAE and RMSE values of 0.99, 0.03 (mm day-1) and 0.04 (mm day-1), respectively. Also, the ANFIS model with 2 inputs (with 3 membership functions and Gaussian mixture model) was the best model for the stations which had only the measured temperature data.

Reference evapotranspiration is an important parameter in irrigation system's design that is evaluated through either direct (Lysimeter) or calculated method (Empirical equations). When there is a lack of lysimeter's data, Penman Monteith FAO method could be employed as a standard method for evaluating the other empirical method's results. In this research, 13 year evaporation pan data of Amol Station are multiplied by the calculated pan coefficient from such different equations as Cuenca, Allen Pruitt, Snyder, modified Snyder, Orang and FAO and then the results compared with Penman Monteith FAO Method's results. The sensitivity of models with variations of ±10, ±20, and ±30 percent in such input parameters as wind velocity and relative humidity is then analyzed. Regression and statistical analysis showed Cuenca, Snyder, Allen Pruitt, Orang methods as recommended for estimation of daily ET0 from pan evaporation data. Cuenca, Snyder, Allen Pruitt methods are suitable for 10 day duration period ET0, while Snyder, Cuenca, Allen Pruitt for monthly ET0. The results of sensitivity analysis show that the sensitivity of the methods Orang, Allen Pruitt and modified Snyder in relation with input parameters is less than that of other methods. Statistical and sensitivity analyses show that Allen Pruitt and modified Snyder methods are the suitable ones for an estimation of pan coefficient in Amol and in areas that are of similar climatic condition.