FAO Penman-Monteith Model Research Articles

Generalized reference evapotranspiration models with limited climatic data based on random forest and gene expression programming in Guangxi, China

Accurate estimation of reference evapotranspiration (ET0) is very important in hydrological cycle research, and is essential in agricultural water management and allocation. The application of the standard model (FAO-56 Penman-Monteith) to estimate ET0 is restricted due to the absence of required meteorological data. Although many machine learning algorithms have been applied in modeling ET0 with fewer meteorological variables, most of the models are trained and tested using data from the same station, their performances outside the training station are not evaluated. This study aims to investigate generalization ability of the random forest (RF) algorithm in modeling ET0 with different input combinations (refer to different circumstances in missing data), and compares this algorithm with the gene-expression programming (GEP) method using the data from 24 weather stations in a karst region of southwest China. The ET0 estimated by the FAO-56 Penman-Monteith model was used as a reference to evaluate the derived RF-based and GEP-based models, and the coefficient of determination (R2), Nash-Sutcliffe coefficiency of efficiency (NSCE), root of mean squared error (RMSE), and percent bias (PBIAS) were used as evaluation criteria. The results revealed that the derived RF-based generalization ET0 models are successfully applied in modeling ET0 with complete and incomplete meteorological variables (R2, NSCE, RMSE and PBIAS ranged from 0.637 to 0.987, 0.626 to 0.986, 0.107 to 0.563 mm day−1, and −2.916% to 1.571%, respectively), and seven RF-based models corresponding to different incomplete data circumstances are proposed. The GEP-based generalization ET0 models are also proposed, and they produced promising results (R2, NSCE, RMSE and PBIAS ranged from 0.639 to 0.944, 0.636 to 0.942, 0.222 to 0.555 mm day−1, and −1.98% to 0.248%, respectively). Although the RF-based ET0 models performed slightly better than the GEP-based models, the GEP approach has the ability to give explicit expressions between the dependent and independent variables, which is more convenient for irrigators with minimal computer skills. Therefore, we recommend applying the RF-based models in water balance research, and the GEP-based models in agricultural irrigation practice. Moreover, the models performance decreased with periods due to climate change impact on ET0. At last, both of the two methods have the ability to assess the importance of predictors, the order of the importance of meteorological variables on ET0 in Guangxi is: sunshine duration, air temperature, relative humidity, and wind speed.

PERFORMANCE OF VAPOUR PRESSURE MODELS IN THE COMPUTATION OF VAPOUR PRESSURE AND EVAPOTRANSPIRATION IN ABHA, ASIR REGION, SAUDI ARABIA

The FAO-56 Penman-Monteith model is recognized as the standard method for estimating reference evapotranspiration (ETo) which requires daily meteorological data as inputs. Among all input data, vapour pressure deficit (VPD) is one of the critical parameter that drives evapotranspiration (ETo), and is of fundamental importance in crop models. In this study effort has been made to compare six vapour pressure models during four seasons. Three vapour pressure models (Models 1–3) selected as mentioned in Irrigation and Drainage Paper-56 of the Food and Agriculture Organization (FAO-56) and Models 4-6 has been selected from literature survey. Model 1, which uses daily maximum and minimum temperature, relative humidity (RH), is the preferred method to estimate actual air pressure (AE) hence it is used as standard for comparing other models. The effectiveness of vapour pressure models were measured by statistical tools and ranked according to Global Performance Indicator (GPI) where higher value of GPI represent best model. The ranking order using GPI shows that Model 5 resulted in best estimation capability with a GPI of 2.77. Moreover, the effect of variation in wind speed on the performance of the vapour pressure models in ETo estimation is also assessed.

ESTIMATING THE POTENTIAL EVAPOTRANSPIRATION (PET) USING SATELLITE IMAGERY IN ARID LANDS

Evapotranspiration is one of the main sources of water loss in arid regions. Although FAO Penman-Monteith (FAO-PM) method is one of the accurate method to estimate potential evapotranspiration (PET). Nevertheless, it is a point-based method and requires several weather data such as radiation, wind speed, air humidity and temperature, which is not available in all regions. Therefore, this study is aimed to estimate PET equivalent to FAO-PM model using satellite data and Priestly-Taylor (PT) model in Yazd province, located in Central Iran. Daily net radiation and soil heat flux, which are used in PT method, were calculated using Landsat 5 data. Then, the net radiation data were integrated with ground data to estimate PET through PT equation. Although similarity between ground-based Priestly-Taylor (PT land) and satellite-based Priestly-Taylor (PT image) was observed, FAO-PM had higher PET values (RMSE=4.74 mmd-1) compared to other methods in all climatic zones of the study area. Therefore, results of PT image method can be replaced with PT land results to estimate potential evapotranspiration, in regions with limitation or lack of weather data. Finally, linear regression model were used for presenting relationship between ground-based FAO-PM and PT land. For this purpose, 70% and 30% of ground data were used for modeling and testing, respectively at different Selianinov climatic zones of the study area. Maximu RMSE for modeled and test data were 4.6 and 2.93, respectively. The model output was applied on PT image to get the FAO-PM image with maximum RMSE of 3.67. It can be concluded that the defined regression equations for each climate zones in this study, can be used to convert values of satellite- based Priestly Taylor method (PT image) as independent variable (X) to equivalent of FAO-PM PET.

Does climate adaptation of vulnerable households to extreme events benefit livestock production?

Extreme climate events have become more frequent and severe as a result of climate change. In semi-arid pastoral regions, extreme drought is harmful to livestock production and to vulnerable human communities and livelihoods. In this study, we considered extreme drought in semi-arid regions and investigated climate adaptations taken by the local vulnerable households and their effects on livestock production. We first analyzed the characteristics of spatio-temporal variation of extreme drought in Hulun Buir, Inner Mongolia, China, during 1980–2015 by using the FAO Penman–Monteith model and then applied stochastic frontier analysis to evaluate the technical efficiency of livestock production of 126 pasturing households. We further explored the effects of climate adaptations to extreme drought on the technical efficiency of livestock production. The results showed that the average frequency of extreme drought in Hulun Buir was 4.6 month/year and displayed a decreasing trend varying from southwest to northeast during 1980–2015. Based on the survey data, the average technical efficiency of livestock production of the local households was 0.530 in 2015, which could be greatly improved. The adaptations of the households significantly positively increased the technical efficiency of livestock production. Purchasing more forage and selling more livestock were the two most frequently adopted and effective adaptive measures for the response of vulnerable households in Hulun Buir to extreme drought risks. Further policy options were provided to improve livestock production as well as rangeland protection and restoration for coping with extreme drought in the context of climate change in semi-arid pastoral regions.

Comparative Study of Evapotranspiration Variation and its Relationship with other Climatic Parameters in Asaba and Uyo

This study was carried out to assess the variations of Reference Evapotranspiration (ETO also denoted with RET) calculated using FAO-56 Penman Monteith model of two locations Asaba and Uyo and evaluate its relationships with the variations of other climatic parameters. Meteorological data of forty one years (1975-2015) and thirty five years (1981-2015) period for Asaba and Uyo, respectively gotten from Nigeria Meteorological Agency, Abuja were used. It was observed that the variations of Evapotranspiration (ET) in both locations were in line with two seasons (rainy and dry) normally experienced in Nigeria having its highest value in March (4.8 mm/day) for Asaba and for Uyo in February (4.5 mm/day); and its lowest value in August (3.1 mm/day) for Asaba and in July (2.9 mm/day) for Uyo. ET variation when compared with other climatic variables in both locations was observed to have the same trend with maximum temperature, solar radiation and sunshine hours. It also has the same variation with minimum temperature though with slight deviation. It was observed that ET variation is inversely proportional to the variation relative humidity. Wind speed displayed relatively small variation in its trend over the study period and is not in line with the variations of ET.Keywords— Evapotranspiration, Climatic Variables, FAO Penman-Monteith Model, Variations

Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China

Accurate estimation of reference evapotranspiration (ET0) is of great importance for the regional water resources planning and irrigation scheduling design. The FAO-56 Penman-Monteith model is recommended as the reference model to predict ET0, but its application is commonly restricted by lack of complete meteorological data at many worldwide locations. This study evaluated the potential of machine learning models, particularly four relatively simple tree-based assemble algorithms (i.e. random forest (RF), M5 model tree (M5Tree), gradient boosting decision tree (GBDT) and extreme gradient boosting (XGBoost)), for estimating daily ET0 with limited meteorological data using a K-fold cross-validation method. For assessment of the tree-based models in terms of prediction accuracy, stability and computational costs, these models were further compared with their corresponding support vector machine (SVM) and extreme learning machine (ELM) models. Four input combinations of daily maximum and maximum temperature (Tmax and Tmin), relative humidity (Hr), wind speed (U2), global and extra-terrestrial solar radiation (Rs and Ra) with Tmax, Tmin and Ra as the base dataset were considered using meteorological data during 1961–2010 from eight representative weather stations in different climates of China. The results showed that, when lack of complete meteorological data, the machine learning models using Tmax, Tmin, Hr, U2 and Ra obtained satisfactory ET0 estimates in the temperate continental, mountain plateau and temperate monsoon zones of China (RMSE < 0.5 mm d−1). However, models with three input parameters of Tmax, Tmin and Rs were superior for daily ET0 prediction in the tropical and subtropical zones. The ELM and SVM models offered the best combination of prediction accuracy and stability. The simple tree-based XGBoost and GBDT models showed comparable accuracy and stability to the SVM and ELM models, but exhibited much less computational costs. Considering the complexity level, prediction accuracy, stability and computational costs of the studied models, the XGBoost and GBDT models have been recommended for daily ET0 estimation in different climatic zones of China and maybe elsewhere with similar climates around the world.

Reference Evapotranspiration Variation Analysis and Its Approaches Evaluation of 13 Empirical Models in Sub-Humid and Humid Regions: A Case Study of the Huai River Basin, Eastern China

Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman–Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash–Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961–2000 and 2001–2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April–October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.

Quantifying Climatic Impact on Reference Evapotranspiration Trends in the Huai River Basin of Eastern China

Reference evapotranspiration (ETref) is an important study object for hydrological cycle processes in the context of drought-flood risks of the Huai River Basin (HRB). In this study, the FAO-56 Penman–Monteith (PM) model was employed to calculate seasonal and annual ETref based on 137 meteorological station data points in HRB from 1961 to 2014. The Mann–Kendall (MK) trend analysis was adopted together with Theil–Sen’s estimator to detect tendencies of ETref and climate factors. Furthermore, a developed differential equation method based on the FAO-56 PM model was applied to quantify the sensitivities of ETref to meteorological factors and their contributions to ETref trends. The results showed that the ETref demonstrated a strong spatially heterogeneity in the whole HRB at each time scale. ETref showed a significant decreasing trend in the upper-middle HRB and Yi-Shu-Si River Basin, especially at the annual time scale, in growing season and summer, while a generally increasing trend in ETref was detected in the lower HRB, and the significance only showed in spring. These phenomena could be reasonably explained by a significantly increasing mean temperature (TA), a significantly decreasing wind speed (WS), solar radiation (SR), and a slightly decreasing relative humidity (RH). The most sensitive factor to ETref was RH in most sub-regions and most time scales, except in the growing season and summer. Based on the developed differential equation method, the dominant factor of the decreasing ETref was WS in the annual time scale, spring, autumn, and winter in most sub-regions, except the lower HRB, which then shifted to SR in the growing season and summer. However, in the lower HRB, the significantly decreasing RH was the most dominant factor, especially in the annual time scale, growing season, and spring, which might be responsible for the slightly increasing ETref there.

Crop-coefficients of tomato as derived using monolithic weighing type lysimeter in mid hill region of Meghalaya

Crop coefficients (kc) was determined for tomato (Lycopersicon esculentum Mill.) with the help of UMS-GmBH cylindrical field lysimeter of 30 cm diameter and 120 cm deep and Penman-Monteith FAO-56 model. Eight other models viz. Modified Penman Method, Hargreaves equation, Samani-Hargreaves equation, Thornthwaite equation, Solar Radiation Method, Net Radiation Method, Blaney-Criddle Method and Radiation Method were also used for estimation of ET0­ and compared with Penman-Monteith model to find out the accuracy of prediction with limited weather parameters. Scatter plot and paired t-test were used for comparison. Out of all these models, Blaney-Criddle method, Solar and Net Radiation method were found to yield similar results as given by Penman-Monteith model. The values of crop evapo-transpiration (ETc) were varying from 2.54 mm d-1 to 6.70 mm d-1. The crop-coefficients (kc) for three growth stages of tomato viz., initial, mid and maturity were found to be 0.55, 1.07 and 0.78, respectively.

Spatio-temporal variation of the wet-dry conditions from 1961 to 2015 in China

As an important part of the regional environment, the wet-dry climate condition is determined by precipitation and potential evapotranspiration (expressed as ET o). Based on weather station data, this study first calculated ET o by using the FAO56 Penman-Monteith model. Then, the dryness index K (ratio of ET o to precipitation) was used to study the spatio-temporal variation of the wet-dry condition in China from 1961 to 2015; moreover, dominant climatic factors of the wet-dry condition change were discussed. The annual precipitation and ET o of the Qinling-Huaihe line were close to a balance ( K ≈1.0). The annual precipitation in most areas exceeded the ET o in the south of this line and the east of Hengduan Mountains ( K ET o ( K ≥4.0). The overall annual K of China fluctuated around the 55-year mean and its linear trend was not significant. However, a relatively wet period of about 10 yr (1987–1996) was recorded. The overall annual K of China showed strong cyclicality on the time scale of 3, 7–8, 11 and 26–28 yr , and regional differences of the annual K trends and cyclicality were large. The degrees of wetness in the Northwest China and western Qinghai-Tibet Plateau were substantially increased, whereas the degrees of dryness in the Yunnan-Guizhou Plateau, Sichuan Basin, and Loess Plateau were markedly increased. The linear trend of the annual K in most regions of China was not significant, and the annual K of most areas in China showed strong cyclicality on the 8–14 yr time scale. Precipitation was the dominant factor of wet-dry condition change in most areas, especially in North China, where the annual K change was highly correlated with precipitation.

Comparison of different reference evapotranspiration (ET0) models and determination of crop-coefficients of french bean (Phesiolus vulgaris.) in mid hill region of Meghalaya

The water requirement and crop evapotranspiration (ETc)is determined using reference evapotranspiration (ET0) and crop-coefficient (kc). Numerous models are available for estimation of ET0,among which Penman-Monteith (FAO-56) model is considered to be the most accurate and universally acceptable. In present study eight models for estimation of ET0viz. Modified Penman method, Hargreaves equation, Samani-Hargreaves equation, Thornthwaite equation, Solar radiation method, Net radiation method, Blaney-Criddle method and Radiation method were compared with Penman-Monteith model to find out the accuracy of prediction with limited weather parameters. Among these, Net radiation and Solar radiation models were found to yield relatively closer values. A field experiment was also conducted withfrench bean (Phesiolus vulgaris.) crop in UMS-GmbH cylindrical field lysimeter of 30 cm diameter and 120 cm deep for determination of crop coefficient taking Penman-Monteith FAO-56 model as the base model for ET0 estimation. The values of ETc as determined in field lysimeter varied from 3.80 mm-d-1 to 5.89 mm-d-1. The kc for initial, mid and maturity were found to be 0.45, 1.01 and 0.39, respectively.

Spatiotemporal variation of reference evapotranspiration during 1954–2013 in Southwest China

Analysis of temporal trend and spatial variation of reference evapotranspiration (ET0) is important in Southwest China, where water resources are vulnerable under the impacts of climate changes and human activities. The main objective of this study was to analyze temporal and spatial variation of ET0 computed by FAO-56 Penman-Monteith model for 119 stations in Southwest China during the period of 1954–2013. Mann-Kendall test, linear trend, Morlet wavelet analysis and inverse distance weighting interpolation methods were applied for the analysis. The results showed that during the past 60 years, annual sunshine hours, relative humidity, wind speed and precipitation decreased while temperature increased. ET0 decreased at a rate of −1.5 mm per decade, or −0.4, −0.7, −0.3, and −0.1 mm per decade in spring, summer, autumn, and winter, respectively. There existed significant periods of 26, 12 and 5a in annual ET0 series based on the Morlet wavelet analysis. Lower and higher ET0 values were found in the northeast and southwest regions both for annual and spring series. These findings will be useful for sustainable planning of water resources under the impacts of climate changes and human activities.

Evapotranspiration and crop coefficients of corn in monoculture and intercropped with jack bean

ABSTRACT This study was carried out to determine the evapotranspiration (ETc) and crop coefficients (Kc) for four stages of “Caatingueiro” corn under the climate condition of Seropédica, RJ, Brazil, using weighing lysimeters. The field trial occurred in 2015, from March 18 to June 25, in two areas cultivated with “Caatingueiro’ corn intercropped with jack bean and in monoculture. The reference evapotranspiration (ETo) was estimated by the FAO-56 Penman-Monteith model and the Kc values were determined by the ratio between ETc and ETo. The Kc values obtained for the intercropping and monoculture systems, were respectively: 0.78 (I); 1.01 (II); 1.10 (III) and 1.01 (IV), and 0.62 (I); 0.92 (II); 1.27 (III) and 0.81 (IV), and they were different from the values presented by FAO.

Predicting the reference evapotranspiration based on tensor decomposition

Most of the available models for reference evapotranspiration (ET0) estimation are based upon only an empirical equation for ET0. Thus, one of the main issues in ET0 estimation is the appropriate integration of time information and different empirical ET0 equations to determine ET0 and boost the precision. The FAO-56 Penman–Monteith, adjusted Hargreaves, Blaney–Criddle, Priestley–Taylor, and Jensen–Haise equations were utilized in this study for estimating ET0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Three-order tensor is used to capture three-way correlations among months, years, and ET0 information. Afterward, the latent correlations among ET0 parameters were found by the multiway analysis to enhance the quality of the prediction. The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Models are compared with respect to coefficient of determination (R 2), mean absolute error (MAE), and root-mean-square error (RMSE). The proposed tensor approach has a R 2 value of greater than 0.9 for all selected ET0 methods at both selected stations, which is acceptable for the ET0 prediction. RMSE is ranged between 0.247 and 0.485 mm day−1 at Nis station and between 0.277 and 0.451 mm day−1 at Belgrade station, while MAE is between 0.140 and 0.337 mm day−1 at Nis and between 0.208 and 0.360 mm day−1 at Belgrade station. The best performances are achieved by Priestley–Taylor model at Nis station (R 2 = 0.985, MAE = 0.140 mm day−1, RMSE = 0.247 mm day−1) and FAO-56 Penman–Monteith model at Belgrade station (MAE = 0.208 mm day−1, RMSE = 0.277 mm day−1, R 2 = 0.975).

Evaluating and Calibrating Reference Evapotranspiration Models Using Water Balance under Hyper-Arid Environment

This research investigates five reference evapotranspiration models (one combined model, one temperature-based model, and three radiation-based models) under hyper-arid environmental conditions at the operational field level. These models were evaluated and calibrated using the weekly water balance of alfalfa by EnviroSCAN to calculate crop evapotranspiration (ETc). Calibration models were evaluated and validated using wheat and potatoes, respectively, on the basis of weekly water balance. Based on the results and discussion, the FAO-56 Penman-Monteith model proved to be superior in estimating ETc with a slight underestimation of 2 %. Meanwhile, the Hargreaves-Samani (HS) model (temperature-based) underestimated ETc by 20 % and the Priestley-Taylor (PT) and Makkink (MK) models (radiation-based) had similar performances underestimating by up to 35 % of the measured ETc. The Turc (TR) model had the lowest performance compared with other models, demonstrating values underestimated by up to 60 % of the measured ETc. Local calibration based on alfalfa evapotranspiration measurements was used to rectify these underestimations. The surprisingly good performance of the calibrated simple HS model, with a new coefficient 0.0029, demonstrated its favorable potential to improve irrigation scheduling. The MK and PT models were in third and fourth rank, respectively, reflecting minor differences between one another. The new coefficients obtained for the MK and PT models were 1.99 and 0.963, respectively. One important observation was that the calibrated TR model performed poorly, with an increase in its coefficient from 0.013 to 0.034 to account for hyper-arid environmental conditions; moreover, it required additional seasonal calibration to adequately improve its performance.

Evaluation of FAO-56 Penman-Monteith Model with Limited Data and the Valiantzas Models for Estimating Grass-Reference Evapotranspiration in Sahelian Conditions

Accurate determination of grass-reference evapotranspiration (ETo) is very important for agricultural, hydrological, and environmental studies, especially under increasing water scarcity and climate mitigation conditions. The FAO-56 Penman-Monteith (FAO-PM) model is renowned for being the most accurate model; however, it requires a full climate data set that is not always available at all weather stations, especially in most of the developing countries. Thus, using ETo models that require a reduced set of climate data continues to be an important alternative in such cases. The objectives of this study were to (1) evaluate the FAO-56 Penman-Monteith equation to estimate ETo with limited climate data, and (2) evaluate two of the latest ETo equations developed by Valiantzas. Climatic variables, including maximum and minimum air temperature, maximum and minimum relative humidity, solar radiation, and wind speed were collected from eight weather stations across Burkina Faso. The results showed that when solar radiation data were missing, solar radiation estimation from maximum and minimum daily air temperatures generated accurate estimates of ETo, with regression slope from 0.98 to 1.04, root mean squared error (RMSE) less than 0.60 mm/day, and low mean biased error (MBE) within the range of −0.18–0.02 mm/day. In the case of lacking relative humidity data, the RMSE and MBE varied from 0.07 to 0.47 mm/day and from −0.45 to 0.22 mm/day, respectively, and the regression slope varied from 0.90 to 1.14, and the coefficient of determination (R2) ranged from 0.77 to 0.92. In the case of missing wind speed, the method that used long-term average wind speed (ETo-um) resulted in the best estimates, especially for lower ETo rates (ETo<6 mm/day) as compared to the method (ETo-w2) that adopted the default wind speed of 2 m/s. Indeed the ETo-w2 method overestimated ETo from 4 to 35%. With the ETo-um method, RMSE varied from 0.43 to 0.57 mm/day and the MBE varied from −0.05 to 0.04 mm/day whereas the (ETo-w2) method had the RMSE ranging from 0.59 to 2.11 mm/day and the MBE ranging from 0.26 to 1.90 mm/day. The FAO-PM equation had the least accurate performance when only temperature data is available. The Valiantzas 1 equation that uses only air temperature and relative humidity data was not suitable and is not recommended for use in Burkina Faso climatic conditions. The Valiantzas 2 equation with full climatic data resulted in good ETo estimates relative to the FAO-PM ETo with full data under the Burkina Faso climate conditions; however, the FAO-PM equation is recommended because of limitations of the Valiantzas 2 equation under limited data conditions.

Comparison of M5 Model Tree and Artificial Neural Network’s Methodologies in Modelling Daily Reference Evapotranspiration from NOAA Satellite Images

The objective of this study was to compare feed-forward artificial neural network (ANN) and M5 model tree for estimating reference evapotranspiration (ET0) only on the basis of the remote sensing based surface temperature (Ts) data. The input variables for these models were the daytime surface temperature at the cold pixel obtained from the AVHRR/NOAA sensor and extraterrestrial radiation (Ra). The study has been carried out in five irrigated units that cultivate sugar cane, which located in the Khuzestan plain in the southwest of Iran. A total of 663 images of NOAA–AVHRR level 1b during the period 1999–2009, covering the area of this study were collected from the Satellite Active Archive of NOAA. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two above approaches. The study demonstrated that modelling of ET0 through the use of M5 model tree gave better estimates than the ANN technique. However, differences with the ANN model are small. Root mean square error and R2 for the comparison between reference and estimated ET0 for the tested data set using the proposed M5 model are 13.7 % and 0.96, respectively. For the ANN model these values are 14.3 % and 0.95, respectively.

Evaluation of reference evapotranspiration methods for the northeastern region of India

The study planed to identify a suitable alternative to the FAO-56 Penman-Monteith (FAO56PM) equation for calculating reference evapotranspiration (ET0) from chosen temperature and radiation based models utilizing monthly meteorological data from 30 destinations in diverse agro-ecological regions of the Northeast (NE) India i.e., Assam Bengal Plain (ABP), eastern Himalaya (EH), and the northeastern hilly (NEH) region. Radiation-based IRMAK3 most appropriate in the ABP (weighted root mean square deviation, WRMSD=0.17mmd−1, r2=0.98, for Nagrakata), and TURC model being in the first three rank of most of the sites, with the lowest error and highest correlation in NEH (WRMSD=0.10mmd−1, r2=0.92, for Shillong), and EH (WRMSD=0.23mmd−1, r2=0.95, for Gangtok). Findings reveal that IRMAK3 and TURC models performed equally well and were observed to be the best among selected models for the majority of stations followed by FAO24 Blaney-Criddle (FAO24BC), and 1957MAKK. Pair-wise regression equations were developed for preferred FAO56PM ET0 estimates to ET0 estimates by alternative methods. Cross-correlation of eighteen chose methods demonstrated that the five equations (i.e. four radiation- and one temperature-based) performed exceptionally well when contrasted with the FAO56PM model, thus being advised for assessing ET0 under limiting data conditions as have yielded a better estimate of ET0 with a small error.

Evapotranspiration estimation of Platycladus orientalis in Northern China based on various models

Platycladus orientalis is one of the most popular afforestation species and greening species for water management in arid and semi-arid regions of northern China. We applied various models to estimate and validate artificial P. orientalis forest evapotranspiration features with the goal of accurately estimating the water use of a P. orientalis plantation. The American Society of Civil Engineers Evapotranspiration–Penman–Monteith model (APM) and FAO56–Penman–Monteith model (FPM) are extensively applied for vegetation evapotranspiration estimation because their reliability has been validated by many scholars. The Priestley–Taylor model (PT) and Hargreaves model (HS) require only the daily maximum temperature, daily minimum temperature and solar radiation to estimate evapotranspiration and are thus widely applied to grasslands but not to forests. We used the Energy Balance Bowen Ratio (EBBR) system to validate the accuracy of the four models. The results indicated that: (1) Compared to the EBBR measurement annual value, APM was the most accurate, followed by FPM, and PT; (2) During the year, the accuracies of the four models varied. APM and FPM underestimated evapotranspiration during June, July and August, whereas PT and HS overestimated evapotranspiration during this period. In the rest of the year, the estimation accuracies were reversed; (3) An analysis of the possible reasons indicated that wind speed, air temperature and precipitation were the most important contributors. High temperatures were measured in June, July and August, which led to an overestimation by PT and HS because these two models only calculated the temperature and radiation without vegetation information. Underestimation also occurred when a low temperature was recorded. Though APM and FPM addressed both meteorological and vegetation factors, slight deviations still existed; and (4) The two models were modified based on EBBR-measured data. Relative humidity was introduced into PT, and parameter “A” in the HS estimation model was amended to 1.41. The accuracy of the modified models significantly increased. The study highlighted the application, comparison and improvement of four models in estimating evapotranspiration and offers more approaches to assess forest hydrological functions.

English

Actual evapotranspiration and crop coefficient (Kc) of Amaranthus cruentus grown in weighing lysimeter was determined under a screen house. The weighing lysimeter was made of a cylindrical plastic of circular cross-sectional area of 0.076 m2 and diameter 0.3 m. Climatic variables such as solar radiation, relative humidity, air temperature and wind speed were collected for the estimation of reference evapotranspiration (ETr) using the FAO-Penman Monteith model. Actual crop evapotranspiration (ETc) was measured directly from the daily drop in the level of water in the burette that was connected to the lysimeter. Crop factor (Kc) was estimated from the ratio of ETc /ETo.&nbsp; The ETc of the crop rose gradually from the period of emergence (4.5 mm week-1) during the 1 week after planting (WAP) to a maximum value of 14.3 mm week-1 during the 7 WAP. Kc for the emergence and maturity stages of Amaranthus cruentus were 0.15 and 0.36, respectively. The highest leaf area index (LAI) and leaf coverage area were 11.39 and 0.866. The optimum soil moisture content for the highest Kc value (0.36) was 11.7%. The output of this research will be useful for farmers who are into vegetable production for enhanced productivity at farm levels. &nbsp; Key words: Lysimeter, Amaranthus cruentus, crop factor, soil water content, leave area index.