ETo Estimates Research Articles

Determination of Crop Coefficients for Flood-Irrigated Winter Wheat in Southern New Mexico Using Three ETo Estimation Methods

Determination of Crop Coefficients for Flood-Irrigated Winter Wheat in Southern New Mexico Using Three ETo Estimation Methods

Rain and evapotranspiration using the Penman-Monteih model for the periods 1963-1982. 1983-2001 and 2002-2019 for the amparo de São Francisco – Sergipe, Brazil

Evaluate the performance of the empirical method of estimating evapotranspiration, with the standard Penman-Monteih method, suggested by FAO-56, for Amparo de São Francisco – Sergipe in the periods 1963-1982; 1983-2001 and 2002-2019 generating their respective graphs and information for government decision makers. The Penman-Monteih method makes it possible to estimate (ETo(PM)) in mm/month and, after computing it, it is multiplied by the total number of days in each month of the year, thus obtaining the Penman-Monteith model estimated in mm/month. The standard Penman-Monteih method can help with irrigation planning and management, especially for small irrigators who do not have access to meteorological data. A better adaptation of the Penman-Monteith and Thornthwaite model was observed in the estimation of ETo, where its results showed adaptation for the location studied. It is advisable to evaluate other models so that they can provide more appropriate results. It is stated that the Penman-Monteith and Thornthwaite models are the best alternatives for the use of evapotranspiration in Amparo de São Francisco - Sergipe.

Improving prediction accuracy of CSM-CERES-Wheat model for water and nitrogen response using a modified Penman-Monteith equation in a semi-arid region

Context or problemThe implementation of crop models for water and nitrogen management are important in preserving water resources and reducing groundwater pollution. The Decision Support System for Agrotechnology Transfer (DSSAT) is a collection of field-scale process-based crop models that simulate crop growth and yield in response to water and nitrogen management as well as many other factors. Objective or research questionThe objective of this study was to improve the simulation of irrigation and nitrogen fertilizer effects on growth and yield of winter wheat using locally modified Penman-Monteith (PM) equation. Specifically, we focused on improving the estimation of ETo using a locally modified Penman-Monteith (PM) equation in the CSM-CERES-Wheat model. MethodsField measured data from a two-year experiment (2009–2010 and 2010–2011) in a semi-arid region were used to calibrate and evaluate the CSM-CERES-Wheat model in a region with strong advective condition. In this experiment, the irrigation treatments were 1.2, 1.0, 0.8, 0.5 times by full irrigation requirements and rain-fed, and nitrogen treatments were 0, 46, 92, and 136 kg N ha−1. ResultsUsing the CSM-CERES-Wheat model with the unmodified PM equation resulted in some growth variables such as: aboveground dry matter, grain yield, and grain nitrogen uptake with high normalized root mean square error (NRMSE) of 0.51, 0.35, and 0.32, respectively. However, using the modified PM equation for ETo module under semi-arid condition improved the soil water content estimation and the model outputs, such as the above ground dry matter, grain yield and grain nitrogen uptake with NRMSE of 0.2, 0.15 and 0.16, respectively, that are accurate. This modification provided more accurate estimations, particularly in our experimental site in semi-aid region with strong advective conditions. ConclusionsThe findings of this study indicated that the locally modified PM equation in the CSM-CERES-Wheat model enhanced the accuracy of estimating irrigation and nitrogen fertilizer on the growth and yield of winter wheat. By improving the estimation of ETo value, the model's performance in simulating crop responses to water and nitrogen management was significantly enhanced. Implications or significanceThe utilization of the accurately estimated ETo value of the modified PM equation has significant importance in the practical application of the CSM-CERES-Wheat model. Furthermore, this modification greatly enhances the accuracy of model outputs, particularly at our experimental site located in a semi-arid region with robust advective conditions.

Selection of best wavelet functions and decomposition levels for coupling with soft computing methods in estimating ETo in coastal and island regions

ABSTRACT Mass transfer-based models are among the extensively applied reference evapotranspiration (ET o ) estimation approaches that have been proven to provide reliable estimates under certain climatic and geographical conditions. A major issue with such approaches is the high variations in wind speed time series, which is a governing meteorological parameter in mass transfer-based models. few studies have focused on applying wavelet transform as a robust pre-processing technique for ETo estimation. A major question with coupling wavelet transforms with soft computing methods would be the proper choice of the wavelet function, vanishing moments and the decomposition levels. The present study aims at assessing different wavelet functions coupled with boosted regression tree (BT) models, i.e. wavelet-BT (WBT), in estimating ET o values (through mass transfer parameters) in both coastal and island regions, where it is supposed that wind speed variations are affected by sea–inland interactions and so has the sharp variations (unlike ET o ). The obtained results showed that the coupled WBT model could improve the single BT model results to a great extent, and meanwhile, the Daubechies wavelet function with six vanishing moments provided the most accurate results in all the locations. Further, the best simulation outcomes with each wavelet function were obtained when the maximum possible decomposition level was used with each function.

Performance of the Copernicus European Regional Reanalysis (CERRA) dataset as proxy of ground-based agrometeorological data

The continuous advances in numerical modeling of the atmosphere, computing power and data assimilation techniques entail frequent updates of numerical weather prediction (NWP) models that show improved forecast skill. This circumstance leads to the recurrent delivery of revised reanalysis databases that provide weather estimates for several decades back in time by combining the latest NWP models with observations. Since climate studies and agriculture water management applications require the availability of accurate and reliable weather data, assessing the performance of reanalysis products contributes to informed choices of potential weather proxy of ground-based agrometeorological data. CERRA (Copernicus European Regional ReAnalysis) dataset is the latest regional reanalysis product released by the European Centre for Medium-Range Weather Forecasts (ECMWF), in August 2022. CERRA is forced by the global ERA5 reanalysis, and it provides weather data with resolution of 5.5 km for the pan-European territory from 1984. For the first time in literature, this study explores the performance of CERRA data at 38 ground-based weather stations located in Sicily, an Italian region with Mediterranean climate, during the irrigation seasons 2003–2022. The objective of the study lies in evaluating CERRA performance with respect to air temperature, actual vapor pressure, wind speed and solar radiation that are input variables for assessing reference evapotranspiration, ETO, which is a key variable for quantifying irrigation volumes needed for water resources studies. The accuracy of ETO estimates depends on those input variables through the equation provided by the Food and Agriculture Organization of the United Nations (FAO), i.e., the FAO Penman-Monteith equation. Here, it is also evaluated the performance of ETO estimates by using CERRA weather inputs in the FAO Penman-Monteith equation. The results show that the performances of CERRA weather data are excellent, especially for air temperature, and this determines that CERRA ETO estimates present high accuracy and reliability with a mean PBIAS and NRMSE equal to 5.6% and 13%, respectively, over the region. Those outcomes lead to the conclusion that CERRA dataset represents a valid alternative to ground-based agrometeorological measurements and their spatial interpolation for water resource regional studies.

Solar Fertigation: A Sustainable and Smart IoT-Based Irrigation and Fertilization System for Efficient Water and Nutrient Management

The agricultural sector is one of the major users of water resources. Water is an important asset that needs to be preserved using the latest available technologies. Modern technologies and digital tools can transform the agricultural domain from being manual and static to intelligent and dynamic leading to higher production with lesser human supervision. This study describe the agronomic models that should be integrated with the intelligent system which schedule the irrigation and fertilization according to the plant needs, and monitors and maintains the desired soil moisture content via automatic watering. Solar fertigation is a fertigation support system based on photovoltaic solar power energy and an IoT system for precision irrigation purposes. The system monitors the temperature, radiation, humidity, soil moisture, and other physical parameters. An agronomic DSS platform based on the integration of soil, weather, and plant data and sensors was described. Furthermore, a three-year study on seven ETo models, such as three temperature-, three radiation-, and a combination-based models were tested to evaluate the sustainable ETo estimation and irrigation scheduling in a Mediterranean environment. Results showed that solar fertigation and Hargreaves–Samani (H-S) equation represented a nearby correlation to the standard FAO P–M and does offer a small increase in accuracy of ETo estimates. Furthermore, the hybrid agronomic DSS is suitable for smart fertigation scheduling.

Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products

This study assesses the accuracy of estimating daily grass reference evapotranspiration (PM-ETo) using daily shortwave radiation (Rs) and reference evapotranspiration (ETREF) products provided by the Meteosat Second Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (Rs ERA5) provided by the European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed using observed weather variables at 37 weather stations distributed across continental Portugal, where climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized by humid, windy and often cloudy conditions. This study's use of data from a variety of climate conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for ETo estimation. The first assessment focused on comparing LSA-SAF estimates of Rs (Rs LSA-SAF) against ground stations (Rs ground). The results showed a good matching between the two Rs data sets for continental Portugal but a tendency for Rs LSA-SAF to under-estimate Rs ground in the cloudy islands of Azores. ETo values computed using Rs LSA-SAF data and observed temperature, humidity and wind speed (ETo LSA-SAF) were then compared with PM-ETo estimates with ground-based data, which were used as benchmark; input data of temperature and humidity needed for PM-ETo were quality checked for surface aridity effects. It was observed that ETo LSA-SAF is strongly correlated with PM-ETo (R2 > 0.97) for most locations in continental Portugal, with regression coefficient of a linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE) of 0.13 mm d−1, and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations, ETo LSA-SAF over-estimated PM-ETo. This is likely a consequence of the high spatio-temporal heterogeneity of weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ETREF product (ETREF LSA-SAF) was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values, for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach was shown to improve both ETo derived from the LSA-SAF products, namely for Azores stations, which seem to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed using the Rs LSA-SAF and Rs ERA5 data, which showed a superiority of the LSA-SAF product for ETo estimations (ETo PMT LSA-SAF). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE when adopting ETo PMT and ETREF LSA-SAF. Differently, results showed that using the Rs LSA-SAF in the PMT approach (ETo PMT LSA-SAF) produces significantly better RMSE results than ETo PMT and ETREF LSA-SAF. Overall, the performed assessment allows concluding that the use of Rs LSA-SAF, and to a lesser extent the use of the Rs ERA5, highly improves the accuracy of computation of ETo when Rs observations are not available, including when only temperature data are accessible. The use of the ETREF LSA-SAF product is a good alternative when observed weather data are not available.

Reference evapotranspiration estimation using equations with limited data in arid zones

Reference evapotranspiration (ETo), is the most important parameter to estimate water consumption. Nowadays the FAO-56 Penman-Monteith method is the most used in the world to estimate Eto, and recommended as the standard method. The main limitation to use this method is the availability of the requiere weather data. There are step by step calculations to estimate ETo when there is a lack of climate data; with the purpose to estimate the crop water consumption in arid regions, it was evaluated the presicion and aplicability of three equations to estimate this parameter when there is limited climate data. Estimates of Eto were performed for five sites, New Mexico State University main campus and its research centers Leyendecker, Artesia and Fabian Garcia, in new Mexico, USA; as well as the Agriculture and Range Science School of the Juarez University of Durango State in Mexico. The estimates of ETo were done with all required wheater data and with lack of solar radiation and relative humidity data. The presicion of the equations was evaluated by using the relative error and the index of agreement, consiedring as reference the FAO-56 with full weather data.

Performance of solar radiation models for obtaining reference evapotranspiration to Santa Maria-RS, Brazil

In the absence of observed data from Solar radiation (Sr), it is possible to estimate it using mathematical models. In general, the models vary in degree of complexity and the adjustment coefficients, and these must be calibrated to the place of interest to obtain the best performance. In this regard, the present work aims to evaluate the performance of simplified models of solar radiation in obtaining reference evapotranspiration. The data were obtained from the automatic meteorological station of the National Meteorological Institute (Inmet), located in Santa Maria – RS, Brazil. In the estimates of global solar radiation and its influence on reference evapotranspiration, ten models were evaluated, five models with the coefficients calibrated and five models, with the coefficients determined by the authors. It was observed that all the models studied presented performance index above 0.82, indicating “optimal” performance. Thus, both calibration and non-calibration models to obtain Sr do not interfere with ETo estimation. Therefore, given the impossibility of obtaining Sr data in meteorological stations, it is possible to use any of the models analyzed.

Comparison of reference evapotranspiration models for the agro-ecological zones of Nigeria

Irrigation practices are best done by estimating the crop water requirement in order to avoid over or under irrigation which may negatively affect crop yields. In this study, weather data (2004-2015) were collected and analyzed. The weather data include; minimum and maximum temperature (°C), relative humidity (%), wind speed (km/day), sunshine (hr/day) and radiation (MJ/m2/day). FAO Penman-Monteith model is a universal standard model used with other five evapotranspiration models such as; Priestley-Taylor model, Thornth-Waite model, Hargreaves model, ASCE-Penman Monteith model and Blaney-Criddle model to compute the mean monthly reference evapotranspiration (ET°) for the six agro-ecological zones of Nigeria. Statistic regressions were performed to examine the relationship of the reference ET° estimates from the five models with the estimates by FAO Penman-Monteith model. The results of the analyses show that the mean monthly average ETo estimates by the FAO Penman-Monteith model, Priestley-Taylor model, Thornth-Waite model, Hargreaves model, ASCE-Penman Monteith model and Blaney-Criddle model across the six weather stations are; 6.48, 7.66, 14.14, 11.16, 5.57, and 3.70 mm/day, respectively. The best predictor is the ASCE-Penman Monteith model which correlated well with the FAO Penman-Monteith model while, the Priestley-Taylor model is the second-best model. Thornth-Waite model and Hargreaves model produced underestimated ET values while, Blaney-Criddle model greatly over-estimated the FAO Penman-Monteith model. Therefore, this study is useful to the precise agricultural water management and regional water resources planning.

Evaluation of the Penman–Monteith reference evapotranspiration under limited data and its sensitivity to key climatic variables under humid and semiarid conditions

The objectives of this study were to assess the accuracy of FAO Penman Monteith equation (FAO PM) under limited data conditions and to perform sensitivity analysis to determine approximately the change in reference evapotranspiration (ETref) expected for a known change in one of the independent variables and derive the sensitivity coefficient. Meteorological data were collected from 8 weather stations under humid and semiarid condition in Cote d’Ivoire. The results showed good performance of FAO PM equation under missing solar radiation (Rs) in semiarid condition and under missing wind speed data (U2) and relative humidity (RH) in all locations with coefficient of determination (R2) ranging from 0.70 to 0.99 and regression slope from 0.99 to 1.05. Under missing Rs, RMSE varied from 0.45 to 0.48 mm/day and AME from 0.30 to 0.35 mm/day. The RMSE and AME vary respectively from 0.12 to 0.51 mm/day and from 0.09 to 0.30 mm/day under missing RH data, and respectively from 0.11 to 0.60 mm/day and 0.04 to 0.34 mm/day under missing wind speed data. The poor performance of FAO PM method to estimate ETo was observed when three climatic variables were missing with regression slope from 0.93 to 1.06 and R2 from − 0.06 to 0.26. The response of ETo to changes in all climate variables was linear, with high R2 values (≥ 0.99) in most cases. Any error in Rs, maximum temperature (Tmax) data would have contributed to significant change in ETo estimate. The effect of Rs on change in ETo estimates had the greatest slope (≥ 2.80) in Bouake, Daloa, Korhogo, Man, Seguela whereas it had the lowest slope in Ferkessedougou (slope = 2.74), Odienne (slope = 2.73), Yamoussoukro (slope = 2.77). The effect of Tmax in change in ETo was also important in all location except Daloa and Man with low regression slope values of 1.63, 1.74, respectively. All sensitivity coefficients showed a large degree of daily and seasonal fluctuations and revealed significant differences in northern and central study locations. The sensitivity coefficients of U2 and Tmax were greatest under semiarid condition while the one of Rs were very high in humid condition. Accurate measuring of U2, Tmax and Rs in estimating reference evapotranspiration using Penman–Monteith equation is required.

Calibration and evaluation of the FAO56-Penman-Monteith, FAO24-radiation, and Priestly-Taylor reference evapotranspiration models using the spatially measured solar radiation across a large arid and semi-arid area in southern Iran

Crop evapotranspiration (ET) is one of the main components in calculating the water balance in agricultural, hydrological, environmental, and climatological studies. Solar radiation (Rs) supplies the available energy for ET, and therefore, precise measurement of Rs is required for accurate ET estimation. However, measured Rs and ET and are not available in many areas and they should be estimated indirectly by the empirical methods. The Angstrom-Prescott (AP) is the most popular method for estimating Rs in areas where there are no measured data. In addition, the locally calibrated coefficients of AP are not yet available in many locations, and instead, the default coefficients are used. In this study, we investigated different approaches for Rs and ET calculations. The daily measured Rs values in 14 stations across arid and semi-arid areas of Fars province in south of Iran were used for calibrating the coefficients of the AP model. Results revealed that the calibrated AP coefficients were very different and higher than the default values. In addition, the reference ET (ETo) was estimated by the FAO56 Penman–Monteith (FAO56 PM) and FAO24-radiation methods by using the measured Rs and were then compared with the measured pan evaporation as an indication of the potential atmospheric demand. Interestingly and unlike many previous studies, which have suggested the FAO56 PM as the standard method in calculation of ETo, the FAO24-radiation with the measured Rs showed better agreement with the mean pan evaporation. Therefore, the FAO24-radiation with the measured Rs was used as the reference method for the study area, which was also confirmed by the previous studies based on the lysimeter data. Moreover, the accuracy of calibrated Rs in the estimation of ETo by the FAO56 PM and FAO24-radiation was investigated. Results showed that the calibrated Rs improved the accuracy of the estimated ETo by the FAO24-radiation compared with the FAO24-radiation using the measured Rs as the reference method, whereas there was no improvement in the estimation of ETo by the FAO56 PM method compared with the FAO24-radiation using the measured Rs. Moreover, the empirical coefficient (α) of the Priestley and Taylor (PT) ETo estimation method was calibrated against the reference method and results indicated ca. 2 or higher α values than the recommended α = 1.26 in all stations. An empirical equation was suggested based on yearly mean relative humidity for estimation of α in the study area. Overall, this study showed that (1) the FAO24-radiation method with the either measured or calibrated Rs is more accurate than the FAO56 PM, (2) the spatially calibrated AP coefficients are very different from each other over an arid and semi-arid area and are higher than those proposed by the FAO56, (3) the original PT model is not applicable in arid and semi-arid area and substantially underestimates the ETo, and (4) the coefficient of the PT should be locally calibrated for each station over an arid and semi-arid area.

Spatial Interpolation of Reference Evapotranspiration in India: Comparison of IDW and Kriging Methods

In the present study, to understand the spatial distribution characteristics of the ETo over India, spatial interpolation was performed on the means of 32 years (1971–2002) monthly data of 131 India Meteorological Department stations uniformly distributed over the country by two methods, namely, inverse distance weighted (IDW) interpolation and kriging. Kriging was found to be better while developing the monthly surfaces during cross-validation. However, in station-wise validation, IDW performed better than kriging in almost all the cases, hence is recommended for spatial interpolation of ETo and its governing meteorological parameters. This study also checked if direct kriging of FAO-56 Penman–Monteith (PM) (Allen et al. in Crop evapotranspiration—guidelines for computing crop water requirements, Irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations (FAO), Rome, 1998) point ETo produced comparable results against ETo estimated with individually kriged weather parameters (indirect kriging). Indirect kriging performed marginally well compared to direct kriging. Point ETo values were extended to areal ETo values by IDW and FAO-56 PM mean ETo maps for India were developed to obtain sufficiently accurate ETo estimates at unknown locations.

A Committee Machine with Intelligent Systems for Estimating Monthly Mean Reference Evapotranspiration in an Arid Region

The aim of this research is to estimate the reference evapotranspiration ETo as given by FAO-56 PM equation in Basrah city, southern Iraq by using several climatic inputs data including maximum monthly mean air temperature, minimum monthly mean air temperature, monthly mean relative humidity and monthly mean wind speed. Three artificial intelligent systems (generalized regression neural network GRNN, multi-layer perceptron MLP and adaptive neuro-fuzzy inference systems ANFIS) were used for predicting reference evapotranspiration. Root mean squared error and coefficient of determination were used as comparison criteria for evaluation of performance of all the developed models. The results shown that the models performances of multi-layer perceptron models are better than adaptive neuro-fuzzy inference systems models and slightly better than generalized regression neural network models with different inputs combination. A Committee Machine with Intelligent Systems (CMIS) was constructed for estimation of ETo by integrating the results of predicting ETo from GRNN, MLP and ANFIS, each of them has a weight factor representing its contribution in overall estimation. The results illustrated that the performance of committee machine with intelligent systems is better than any one of the individual artificial intelligent systems for predicting ETo.

Estimating Daily Reference Evapotranspiration in a Semi-Arid Region Using Remote Sensing Data

Estimating daily evapotranspiration is challenging when ground observation data are not available or scarce. Remote sensing can be used to estimate the meteorological data necessary for calculating reference evapotranspiration ETₒ. Here, we assessed the accuracy of daily ETₒ estimates derived from remote sensing (ETₒ-RS) compared with those derived from four ground-based stations (ETₒ-G) in Kurdistan (Iraq) over the period 2010–2014. Near surface air temperature, relative humidity and cloud cover fraction were derived from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU), and wind speed at 10 m height from MERRA (Modern-Era Retrospective Analysis for Research and Application). Four methods were used to estimate ETₒ: Hargreaves–Samani (HS), Jensen–Haise (JH), McGuinness–Bordne (MB) and the FAO Penman Monteith equation (PM). ETₒ-G (PM) was adopted as the main benchmark. HS underestimated ETₒ by 2%–3% (R2 = 0.86 to 0.90; RMSE = 0.95 to 1.2 mm day−1 at different stations). JH and MB overestimated ETₒ by 8% to 40% (R2= 0.85 to 0.92; RMSE from 1.18 to 2.18 mm day−1). The annual average values of ETₒ estimated using RS data and ground-based data were similar to one another reflecting low bias in daily estimates. They ranged between 1153 and 1893 mm year−1 for ETₒ-G and between 1176 and 1859 mm year−1 for ETₒ-RS for the different stations. Our results suggest that ETₒ-RS (HS) can yield accurate and unbiased ETₒ estimates for semi-arid regions which can be usefully employed in water resources management.

Estimation of grass reference evaporation and sensible heat flux using surface renewal and Monin-Obukhov similarity theory: A simple implementation of an iterative method

An iterative method was applied to daily crop reference evaporation ETo. The method correctly evaluated the slope of the saturation water vapour pressure vs temperature relationship between surface temperature and air temperature. Using daily meterological data spanning several decades from four selected locations in Australia, South Africa and USA, differences in ETo estimates were noted with and without the iteration method applied. The largest difference, which occurred under high water vapour pressure deficit conditions, ranged from 1.65mm/day for Griffith, Australia to 0.51mm/day for Pretoria, South Africa. The aerodynamic component of the ETo equation was more affected by not applying the spreadsheet iterative procedure compared to the radiative component. Other spreadsheet examples of the iterative method employed included obtaining the roots of a depressed cubic polynomial in the air temperature surface renewal (SR) ramp. This value was used for the measurement of sensible heat flux using surface renewal. An iterative method, together with Monin-Obukhov similarity theory (MOST) and surface-layer scintillometer (SLS) measurements in a mesic grassland, was also used to calculate the sensible heat flux. The simple iterative method is quick, accurate and convenient, easy to repeat following changes to equations or data, allows easy manipulation and allows convenient visual inspection of data and graphics. Sub-hourly measurements of sensible heat flux for the mesic grassland using SR and SLS MOST iterative methods compared favourably with Bowen ratio and eddy covariance measurements.

Performance of Twelve Mass Transfer Based Reference Evapotranspiration Models under Humid Climate

Reference evapotranspiration is very important parameter in the hydrological, agricultural and environmental studies and is accurately estimated by the FAO Penman-Monteith equation (FAO-PM) under different climatic conditions. However, due to data requirement of the FAO-PM equation, there is a need to investigate the applicability of alternative ETo equations under limited data. The objectives of this study were to evaluate twelve mass transfer based reference evapotranspiration equations and determine the impact of ETo equation on long term water management sustainability in Tanzania and Kenya. The results showed that the Albrecht, Brockamp-Wenner, Dalto, Meyer, Rohwer and Oudin ETo equations systematically overestimated the daily ETo at all weather stations with relative errors that varied from 34% to 94% relative to the FAO-PM ETo estimates. The Penman, Mahringer, Trabert, and the Romanenko equations performed best across Tanzania and the South Western Kenya with root mean squared errors ranging from 0.98 to 1.48 mm/day, which are relatively high and mean bias error (MBE) varying from -0.33 to 0.02 mm/day and the absolute mean error (AME) from 0.79 to 1.16 mm/day. For sustainable water management, the Trabert equation could be adopted at Songea, the Mahringer equation at Tabora, the Dalton and/or the Rohwer equations at Eldoret, the Romanenko equation at Dodoma, Songea and Eldoret. However, regional calibration of the most performing equation could improve water management at regional level.

Analyses, calibration and validation of evapotranspiration models to predict grass-reference evapotranspiration in the Senegal river delta

Abstract Study region: Grass-reference evapotranspiration estimation by the Penman-Monteith method (PM-ETo) requires a number of climate variables which are not always available at all weather stations. Different alternative ETo equations have been developed and their utilization for various local climate conditions requires analyses of their accuracy as compared to the standardized Penman-Monteith method. There is a significant lack of data and information on this topic in the Senegal River Delta (SRD). Study focus: The objective of this study was to evaluate, calibrate and validate six ETo equations ((Trabert, Mahringer, Penman1948, Albrecht, Valiantzas1 and Valiantzas2) for the SRD. Although all six equations showed good agreement with the PM-ETo (R2 > 0.60) for daily ETo estimates, the Valiantzas2 equation was the best model for the Senegal River Delta and had the lowest root mean squared difference (RMSE) of 0.45 mm/day and the lowest percent error of estimate (PE) about 7.1%. New hydrological insights for the region: In the case of data limitations, the equations calibrated in this study are recommended for ETo estimation in the Senegal River Delta. The results of this study could be used by agricultural producers, crop consultants, university researchers, policy makers for the agricultural, hydrological, and environmental studies as well as proper allocation and use and forecasting in the SRD where lowland irrigated rice is predominant.

EVAPOTRANSPIRAÇÃO DE REFERÊNCIA POR PENMAN-MONTEITH FAO 56 COM AUSÊNCIA DE DADOS DE RADIAÇÃO GLOBAL

The aim of this study was to evaluate the errors generated on the reference evapotranspiration (ET0) estimation by Penman-Monteith FAO 56 (PMF 56) when employed simplified models to estimate the global radiation (HG) are based on the air temperature. We evaluated 28 automatic weather stations (EMA's) belonging to the National Institute of Meteorology (INMET) network, in different biomes of Mato Grosso state. Was evaluated fifteen simplified models of HG estimate calibrated regionally and five models without calibration. It was used as a reference ETo obtained by PMF 56, with HG measure. The statistical performance were employed mean bias error (MBE), root mean square error (RMSE), adjustmentindex (d) and the cumulative numerical order of the different models in each index. The regional calibration models HG estimation models improve the estimates of ETo. Can be used Bristow and Campbell (1984) and Goodin et al. (1999), De Jong and Stewart (1993) models to HGestimates and then ET0 to Amazon, Cerrado and Pantanal, respectively.

Comparison of methods for estimating reference evapotranspiration (ETo) for Rahuri region

Penman Monteith (FAO56-PMM), Modified Penman FAO-24 (MPM), Hargreaves-Samani (HSM), FAO-24 Pan Evaporation (FPEM), Blaney-Criddle (BCM) and FAO Radiation (FRM) methods were used for estimation of ETo for Rahuri region. The Penman Monteith method was considered as the standard of comparison for evaluating the other five methods. The ETo values estimated by PMM were correlated with ETo values estimated by other five methods. The good correlation was found between the ET o values estimated by MPM, HSM and FRM. The coefficient of determination was high for MPM (R 2=0.99), HSM (R2=0.97) and FRM (R2=0.93) and therefore found to be more suitable in the absence of adequate climate data for the use of PMM for this climatic region.