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Methods used to quantify evapotranspiration (ET) from Sphagnum‐dominated peatlands often assume that soil moisture is not a limiting factor; actual ET (AET) equals potential ET (PET). However, soil moisture can become limiting as peatlands dry, lowering AET below PET and necessitating the use of a surface resistance term in AET estimations. Quantifying and calculating surface resistance is a challenge for the non‐vascular plant surfaces such as those dominated by Sphagnum moss. This paper explores and quantifies the ecohydrological processes that drive Sphagnum resistance to ET. It is hypothesized that a relationship exists between the Sphagnum moss resistance and the ratio of unsaturated to saturated hydraulic conductivity (K‐ratio) for boreal peatlands, where the K‐ratio is a proxy for the hydrophysical properties of the porous medium. An empirical relationship between Sphagnum moss resistance and the K‐ratio was developed from data collected from a boreal peatland and implemented in the cold regions hydrological model. Empirically modelled resistance values (0–800 s m−1) did not match well with estimates from inverting observations and the Penman–Monteith (PM) algorithm (0–5000 s m−1). Difficulties in validating resistance values were possibly due to lack of moisture limiting conditions although this is seemingly contradicted by the alpha value being less than 1. Priestley–Taylor (PT) and PM algorithms in CRHM were used to estimate AET and compared with each other and with observations from an onsite eddy covariance (EC) system. The PT algorithm, using a site‐specific alpha value (0.75) performed the best with a mean difference of 9.4% (±12.0%) when compared to EC measurements of AET. The PM algorithm consistently overestimated EC measurements with a mean difference of 68.4% (±50.0%), even with a moss resistance incorporated into its use. The performance of PM algorithm is impeded by the uncertainty in quantifying Sphagnum resistance. Reducing this uncertainty should be a focus of future studies, as it does not require the use of a site‐specific alpha value. [ABSTRACT FROM AUTHOR]

The estimation of reference evapotranspiration (ET0) has been widely used in irrigation engineering to calculate crop water requirements. The correct estimation of ET0 represents a key step in planning and managing water resources. Experts recommend the FAO56 Penman-Monteith method as a standard method for estimating ET0, with the disadvantage that it requires a lot of data on meteorological variables for its execution. This study aimed to estimate the daily reference evapotranspiration by the Hargreaves-Samani and Priestley-Taylor methods during the 2001-2006 period for five automatic weather stations in the state of Guanajuato; the results were compared with those of the FAO56 Penman-Monteith (FAO56 P-M) method to select the most accurate alternative method and determine the distance from any station at which the ET0 data estimated with each of the methods were considered valid. The root means square error (RMSE) and the coefficient of determination (R2) were used to evaluate the performance of the methods compared to the FAO56 P-M. As a result, it was found that Hargreaves-Samani is the best alternative method to estimate ET0 in the five stations in the state of Guanajuato. The distances determined from a station where the data of a method are valid are 93.02, 124.65, and 36.44 km for Hargreaves-Samani, PriestleyTaylor, and FAO56 Penman-Monteith, respectively [ABSTRACT FROM AUTHOR]

Copyright of Tecnología y Ciencias del Agua is the property of Instituto Mexicano de Tecnologia del Agua (IMTA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman–Monteith, Priestley–Taylor, and Shuttleworth–Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016–2017 and 2019–2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse. [ABSTRACT FROM AUTHOR]

The present study was taken up to demonstrate an overall methodology for local calibration of simpler reference crop evapotranspiration (ET0) estimation equations relative to the physically-based, albeit more data-intensive Penman-Monteith (PM) method. Climate records for the historical period 2006-2016 of 67 stations located across 10 agro-climatic zones of Karnataka State, India, were used for this purpose. The numerical coefficients in the original forms of the simpler equations namely, Blaney-Criddle (BC), Priestley-Taylor (PT), Radiation (RAD), and Turc (TC) were treated as unknown parameters and optimized for each station using PM ET0 estimates as reference. Results of local calibration indicated significant improvement in prediction accuracies and bias reduction for all the equations with the calibrated PT equation exhibiting the best performance. Spatial maps depicting the variations in the optimal values of parameters were developed to aid the accurate estimation of monthly ET0 values in the study area using only minimal climate inputs. [ABSTRACT FROM AUTHOR]

This study aimed to determine cucumber crop coefficients under different greenhouse microclimatic conditions, parameterizing the Priestley-Taylor reference evapotranspiration model. Crop evapotranspiration was directly measured with the use of lysimeters, and crop coefficients were computed following the two-step climate FAO 56 methodology. Greenhouse compartments (i.e., cooled or uncooled) showed reference evapotranspiration differences of up to 12% in an autumn-winter crop. The results presented cucumber crop coefficient values from the initial to the late-season growth stages from 0.45 to 0.94 depending on the greenhouse climate. Based on the greenhouse hourly microclimatic variation of KC, it is recommended not to apply a KC as a constant for transpiration estimation even at greenhouses located within the same region Regression analysis relating crop coefficients with leaf area revealed very high correlation coefficients for the equations tested. The results indicated that evapotranspiration can be modeled satisfactory based on a significant relationship between crop coefficient and simple measurements of the leaf area index (i.e., KC = 0.447 × LAI). [ABSTRACT FROM AUTHOR]

Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman–Monteith, Priestley–Taylor, and Shuttleworth–Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016–2017 and 2019–2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse.

Los flujos verticales, dentro del ciclo hidrológico, son una de las variables de mayor relevancia en zona de llanura, dado que las pendientes varían entre 0 y 5%, y los flujos horizontales no son significativos. En este sentido, la evapotranspiración juega un rol fundamental en el manejo hídrico, ya que alrededor del 85% del agua que sale del sistema lo hace mediante este proceso, requiriendo una cuantificación precisa. El objetivo principal de este trabajo es calcular la evapotranspiración potencial y real (ETp y ETr) con datos de satélite y reanálisis mediante el uso de la plataforma Google Earth Engine. Para su cálculo se tomó la ecuación de Priestley-Taylor (PT) combinado con información de humedad de suelo, con una resolución espacio-temporal de 250 x 250 m cada ocho días, en la región pampeana argentina (RPA). El producto se valoró en siete estaciones de la RPA, cuyos resultados mostraron, para la ETp, un R-RMSE (error cuadrático medio robusto) de 0.5 mm d-1; un error sistemático (mediana) de 0.3 mm d-1, y el error aleatorio (RSD- desviación estándar robusta) de 0.5 mm d-1; mientras que para la ETr, estos valores son de 0.6, -0.2 y 0.5 mm d-1, respectivamente. Los resultados globales muestran que el método utilizado es una herramienta válida para caracterizar la ET en la RPA y que se puede usar para analizar su variabilidad espacio-temporal en diferentes condiciones extremas y realizar estudios ambientales aplicados.

The Priestley‐Taylor (PT) method is widely used in hydrologic and crop models to calculate the atmospheric demand for water or reference evapotranspiration (ETo). However, the default value of the PT coefficient PTa=1.26 $\left({\mathrm{P}\mathrm{T}}_{a}=1.26\right)$ cannot assure reliability under different climatic regions due to the inadequate consideration of the aerodynamic components. In addition, the spatial and temporal evolution of PTa at global scales and how meteorological parameters affect its change have not been elucidated to date. Here, we derived an analytical expression of PTa following the Penman‐Monteith method, i.e., PTa=1SA1+SU2 ${\mathrm{P}\mathrm{T}}_{a}=\frac{1}{{S}_{A}}\,\left(1+{S}_{{U}_{2}}\right)$, where SA and SU2 ${S}_{{U}_{2}}$ represent the available energy and wind speed impacts on ETo, respectively. The daily Princeton Global Forcing data set (0.25° × 0.25°, 1948–2016) was used to validate PTa. The calibration‐free PTa improved the simulation of aerodynamic components and, consequently, the accuracy of ETo estimation. The gridded global monthly PTa data set is fully open‐source and can be incorporated into hydrologic and crop models. We also demonstrated that PTa under equilibrium or quasi‐equilibrium evaporation conditions (1.26 ± 0.04) was very close to the default value. The simplified PTa, with relative humidity as the only input, still performed better than the original method. Results indicated that the radiative component was the driving factor of the global ETo changes from 1948 to 2016. The impacts of available energy and wind speed on global ETo variations tend to intensify in a warming climate. Our findings have important implications for understanding the roles of radiative and aerodynamic components in the global ETo changes. Key Points: An analytical expression for the Priestley‐Taylor (PT) coefficient following the Penman‐Monteith method is derivedThe derived PT coefficient well captures the temporal and spatial distribution of global ETo, as well as its long‐term trendThe simplified PT coefficients with relative humidity as the only input still perform better than the original PT method [ABSTRACT FROM AUTHOR]

Copyright of Irrigation & Drainage is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Indonesia is a maritime country with a vast ocean area. Indonesia has high potential to produce salt because it has a lot of saltwater resources. When sea salt is harvested, seawater evaporates from a concentration of 3.5°Be to 29°Be. Evaporation can be affected by several factors, such as air temperature, wind speed, water vapor pressure, humidity, radiation, geographical location, time interval, and season. Many modifications have been made to increase the evaporation rate in salt production. One of them is the WAIV (Wind-Aided Intensified eVaporation) method. WAIV evaporation systems utilize sunlight and wind to accelerate the evaporation rate. The modeling in this study was adjusted to the environmental conditions in the case study for which it was necessary to determine new parameter values for the existing models. The Penman, Priestley-Taylor, and Harbeck models were used. The Harbeck model has been studied in previous studies, which were used as a reference in the present study. This study first determined and then validated the parameter values obtained. A simulation of the evaporation rate was conducted in a different place, namely Kupang, East Nusa Tenggara, Indonesia using Meteorology, Climatology, and Geophysical Agency (Indonesian: Badan Meteorologi, Klimatologi, dan Geofisika / BMKG) data. [ABSTRACT FROM AUTHOR]

Accurate evapotranspiration (ET) estimation plays a central role in better understanding the allocation of water resources in a time of increasing scarcity; however, ET estimation remains many challenges. To enhance the accuracy of ET prediction, this study proposes an enhanced gross primary productivity (GPP)‐based Priestley–Taylor algorithm (GPP‐PT) that uses GPP to compute fractional vegetation cover (fV). In terms of soil moisture fraction (fSM), it is described by using either diurnal temperature (DT) or soil moisture index (SWI), conducting two variations of the proposed model (i.e., hereafter called GPP‐DT and GPP‐SWI, respectively). These two improved algorithms were compared with their previous models, the GPP‐DT with a modified satellite‐based Priestley–Taylor model (MS‐PT), and the GPP‐SWI with a soil water index (SWI)‐based Priestley–Taylor model (SWI‐PT). Datasets from 42 flux towers covering different land cover types were used to investigate the performance of these algorithms. The GPP‐DT algorithm was found to be superior to the MS‐PT model, with 12.60% and 10.42% reductions in the root mean square error (RMSE) and mean absolute error (MAE), respectively, and with 9.05% and 2.19% increases in the determination coefficient (R2) and index of agreement (IOA), respectively. Similarly, the GPP‐SWI model yielded RMSE and MAE reductions of 10.95% and 10.67%, respectively, and R2 and IOA increases of 8.88% and 3.72%, respectively, compared to the SWI‐PT model. In the direct comparison between the two newly proposed models, the GPP‐DT model performed better in shrubland and forest, whereas the GPP‐SWI model performed more efficiently in grassland. Sensitivity analysis found that soil moisture was more sensitive to both evaporation and transpiration than DT in most land cover types, and the GPP had a stable relationship with transpiration in different biomes. The newly improved GPP‐PT models were robust and effective for estimating ET and might thus be used as a reliable input for hydrological models. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is needed to optimize irrigation in semi-arid environments. The present work aims to estimate evapotranspiration using empirical formulas and remote sensing in a commercial olive orchard near Menzel Mhiri in east central Tunisia. This study compares evapotranspiration with the Mapping Evapotranspiration at high Resolution with Internal Calibration (METRIC) model with estimates from five empirical equations (Penman–Monteith; Blaney-Criddle; Hargreaves temperature; Hargreaves radiation; and Priestley-Taylor). Reference evapotranspiration estimated using these five empirical equations was based on meteorological station measurements in olives at the pilot study site. Three years of ET estimates based on Landsat-8 satellite images and the METRIC method covering 2017, 2018, and 2019 were downloaded using Google EEFlux. The results obtained by remote sensing showed good ability to characterize seasonal variation in reference (ET0) and actual crop (ETc) evapotranspiration. Reference evapotranspiration values for olive trees estimated by the METRIC model during the three experimental years accurately represent those estimated with the Penman–Monteith formula. Also, there was very good agreement between results obtained with METRIC and those calculated using the Blaney-Criddle method. The monthly average of ET0 and ETc values determined during the three experimental years (2017, 2018, and 2019) showed that the METRIC model underestimates irrigation needs by about 15% compared to the Penman–Monteith (PM) approach. [ABSTRACT FROM AUTHOR]

Many remote sensing‐based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley–Taylor Jet Propulsion Laboratory (PT‐JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman–Monteith Mu model (PM‐MOD), and Penman–Monteith Nagler model (PM‐VI). ET was predicted satisfactorily by all four models, with correlations consistently higher (R2>0.6) for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (−10

Background: In explaining and predicting spatial vegetation patterns, ecologists have increasingly favoured the use of climatic water balance variables, including actual evapotranspiration (AET) and climatic water deficit (CWD), for representing the hydrologic and energetic environment experienced by plants. Much of the interest in these variables lies in their hypothesized potential to characterize biologically relevant environmental variation more directly than simple climate variables, such as precipitation and temperature. Practically, obtaining AET and CWD values across space requires hydrologic process models that involve assumptions, including assumptions about vegetation transpiration rates. However, transpiration parameter values are rarely known with precision and can vary several‐fold within and among vegetation types. Approach: We evaluate the extent to which assumptions about vegetation physiology in water balance models affect (a) relative spatial variation in modelled water balance values and (b) ecological inferences that are derived from analyses using water balance variables. We demonstrate an approach for identifying inferences that are robust to these assumptions. Results: Assumptions about vegetation physiology can substantially affect relative spatial variation in modelled water balance values. More importantly, such assumptions can also substantially affect the inferences (e.g., expected vegetation distributions) drawn from ecological analyses that use water balance variables as predictors. Water balance variables are less sensitive to assumptions in environmental settings with abundant water supply, where AET variation is driven primarily by available energy (e.g., temperature and insolation), but they can be highly sensitive to assumptions in drier environments. Conclusion: Because of their sensitivity to assumptions, water balance variables are not unambiguously superior to simpler climatic and topographic variables, such as precipitation and temperature. However, they retain some advantages, primarily related to their mechanistic incorporation of interactions between water and energy, which may support their use in applications where sensitivity to hydrologic modelling assumptions is low or of minor concern. [ABSTRACT FROM AUTHOR]

Evapotrantaspiration is a crucial part of the hydrological cycle but few ground observatories for the Tibetan Plateau exist. In this study, we present lysimeter measurements from the growing season during seven years at a remote field location on the Tibetan Plateau. The measurements show rates between 2.5 and 3 mm·d−1 during the warmer months from June to August, dropping to 2 to 2.5 mm·d−1 in September. This results in a total volume of evapotranspiration of approximately 300 mm·yr−1 for the months from June to September. The inter-daily variability is however large, and comparison to meteorological variables suggest that this is largely driven by radiation and humidity. Data for a single season from a nearby flux tower allows us to compare the two common measurement methods for evapotranspiration in the field, showing an overall good agreement between the approaches. We also tested commonly applied models used to estimate evapotranspiration rates, namely the FAO-Penman-Monteith (PM) and the Priestly-Taylor (PT) model, which both make use of radiation data as well as the simpler Hargreaves-Samani (HS) and Rohwer (R) models which only need air temperature and wind speed as input. The most data intensive model (PM) has the lowest root mean square error (RMSE) (1.36 mm·d−1) and the mean bias error (MBE) (−0.05 mm·d−1) and reproduces the daily variability generally well. The much simpler HS model performs slightly worse (1.38 and 0.35 mm-d−1), but fails to reproduce the variability, due to its lack of information of local radiation and humidity data. Our results are in line with large scale estimates of evapotranspiration for the cold and arid region, provide a first long time series of in-situ measurements from a high elevation site and suggest that both the PM and HS models are appropriate when no direct measurements are available. [ABSTRACT FROM AUTHOR]

Remote sensing models that measure evapotranspiration directly from the Penman‐Monteith or Priestley‐Taylor equations typically estimate the soil evaporation component over large areas using coarse spatial resolution relative humidity (RH) from geospatial climate datasets. As a result, the models tend to underperform in dry areas at local scales where moisture status is not well represented by surrounding areas. Earth observation sensors that monitor large‐scale global dynamics (e.g., MODIS) afford comparable spatial coverage and temporal frequency, but at a higher spatial resolution than geospatial climate datasets. In this study, we compared soil evaporation parameterized with optical and thermal indices derived from MODIS to RH‐based soil evaporation as implemented in the Priestley Taylor‐Jet Propulsion Laboratory (PT‐JPL) model. We evaluated the parameterizations by subtracting PT‐JPL transpiration from observation‐based flux tower evapotranspiration in agricultural fields across the contiguous United States. We compared the apparent thermal inertia (ATI) index, land surface water index (LSWI), normalized difference water index (NDWI), and a new index derived from red and shortwave infrared bands (soil moisture divergence index [SMDI]). Relationships were significant at the 95% confidence band. LSWI and SMDI explained 18–33% of variance in 8‐day soil evaporation. This led to a 3–11% increase in explained ET variance. LSWI and SMDI tended to perform better at the irrigated sites than RH. LSWI and SMDI led to markedly better performance over other indices at a seasonal time step. L‐band microwave backscatter can penetrate clouds and can distinguish soil from canopy moisture content. We are presently fusing red‐SWIR‐RADAR to improve soil evaporation estimation. Key Points: Shortwave infrared in combination with red or near‐infrared MODIS bands capture short‐term and seasonal variation in soil evaporationThese band combinations are particularly strong performers at perennially flooded sitesThermal‐based indices are susceptible to changing meteorological conditions and should not be used for soil evaporation estimation [ABSTRACT FROM AUTHOR]

Evapotranspiration, a major component in terrestrial water balance and net primary productivity models, is difficult to measure and predict. This study compared five models of potential evapotranspiration (PET) applied to a ponderosa pine forest ecosystem at. an AmeriFlux site in Northern California. The AmeriFlux sites are research forests across the United States, Canada, Brazil, and Costa Rica with instruments on towers that measure carbon, water, and energy fluxes into and out of the ecosystems. The evapotranspiration models ranged from simple temperature and solar radiation-driven equations to physically-based combination approaches and included reference surface and surface cover-dependent algorithms. For each evapotranspiration model, results were compared against mean daily latent heat from half-hourly measurements recorded on a tower above the forest canopy. All models calculate potential evapotranspiration (assuming well-watered soils at field capacity), rather than actual evapotranspiration (based on soil moisture limitations), and thus overpredicted values from the dry summer seasons of 1997 and 1998. A soil moisture function was integrated to estimate actual evapotranspiration, resulting in improved accuracy in model simulations. A modified Priestley-Taylor model performed well given its relative simplicity. (c) 2004 Elsevier Ltd. All rights reserved.

In order to calculate water deficit of agricultural crops, it is necessary to have an insight into the evapotranspiration process. As for evaluation of reference evapotranspiration, the Penman-Monteith (FAO56-PM) method, suggested by The International Commission on Irrigation and Drainage (ICID) and Food and Agriculture Organization of the United Nations (FAO), requires several climate parameters, which are often unavailable. Thus, in this paper, the methods for computing ETo, which use limited weather data, were tested and then compared to FAO56-PM. The selected methods were those most often used as the replacement for FAO56-PM: Hargreaves, adjusted Hargreaves, Copais, Turc, Priestley-Taylor, Makkink and Hamon. ETo was calculated at the daily and average monthly levels, for the 2010 2013 period, using data from the following meteorological stations: Niš, Belgrade, Novi Sad, Loznica, Valjevo, Zlatibor, Ćuprija and Kikinda. Special importance was given to the vegetation period during the dry season due to the application of irrigation. The comparison of methods was based on statistical analysis, using parameters: MXE, MAE, RMSD, ARMSD, WRMSD, b and R2. The highest rate of matching FAO-PM at the average monthly level, as well as during the 2012 growing season, was shown by Copais, Turc and Priestley-Taylor methods, thus these methods may be recommended as the replacement for FAO-PM under climate conditions of Serbia. In case only temperature data are available, the results of this research justify the use of the adjusted Hargreaves equation to calculate ETo for the vegetation period.

The radiation-based Priestley–Taylor (PT) model is a common way of modeling evapotranspiration (ET0) when only air temperature and solar radiation records are obtainable. However, this method presents the crucial drawback of requiring an initial local calibration. Most of the existing calibration procedures usually utilize similar patterns (data) for calibrating and testing the ET0 models. In the current research, the PT model and its calibrated versions were evaluated by utilizing meteorological data from 29 weather stations in Iran. Thoroughgoing local and external data scrutinizing procedures (using k-fold validation) were adopted to evaluate the models. Additionally, the externally calibrated models were reevaluated considering vapor pressure deficit (VPD) and net radiation (Rn) records. A similar plan was replicated for assessing the performance of gene expression programming (GEP)–based equations fed with the air temperature and solar radiation data. Both local and external calibrations of the PT model generally improved the accuracy of original PT for estimating ET0, especially in humid and arid stations. External calibration using VPD and Rn data was found to be comparable to locally calibrated and non-calibrated PT models. Local GEP models generally performed more accurately than locally calibrated and non-calibrated PT models. Higher accuracy was also obtained using external GEP models in comparison with non-calibrated PT models. [ABSTRACT FROM AUTHOR]

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Abstract: Evapotranspiration (ET) is one of the major uncertain components of the energy and water cycle and was derived for the Nagqu River Basin based on remote sensing data and atmospheric surface layer observations under cloudless conditions. Two process‐based models were used to determine the ET: a Priestley‐Taylor (PT)‐based model and a topographical enhanced surface energy balance system (TESEBS) model. Improved broadband albedo, downward shortwave radiation flux, and reconstructed normalized difference vegetation index (NDVI) were coupled into the TESEBS model and PT‐based model to estimate the actual ET. The atmospheric surface layer meteorological data, SPOT Vegetation (VGT) data, and Moderate Resolution Imaging Spectroradiometer data were used as inputs for 10‐day ET calculations. The model‐estimated results were compared with ground truths calculated via the combinatory method. The results indicated that the ET determined by both models well fit the actual ET, with correlation coefficients (R) of 0.88 and 0.82, respectively. However, the TESEBS model showed a better performance than the PT model, with a lower mean bias error (−0.02 mm/hr) and lower root–mean‐square error (0.08 mm/hr). Although the PT model is computationally simple and requires few parameters, the strong weighting of the NDVI may lead to some overestimations, especially during the growing season. [ABSTRACT FROM AUTHOR]

Although interannual streamflow variability is primarily a result of precipitation variability, temperature also plays a role. The relative weakness of the temperature effect at the annual time scale hinders understanding, but may belie substantial importance on climatic time scales. Here we develop and evaluate a simple theory relating variations of streamflow and evapotranspiration (E) to those of precipitation (P) and temperature. The theory is based on extensions of the Budyko water-balance hypothesis, the Priestley-Taylor theory for potential evapotranspiration (Ep), and a linear model of interannual basin storage. The theory implies that the temperature affects streamflow by modifying evapotranspiration through a Clausius-Clapeyron-like relation and through the sensitivity of net radiation to temperature. We apply and test (1) a previously introduced "strong" extension of the Budyko hypothesis, which requires that the function linking temporal variations of the evapotranspiration ratio (E/P) and the index of dryness (Ep/P) at an annual time scale is identical to that linking interbasin variations of the corresponding long-term means, and (2) a "weak" extension, which requires only that the annual evapotranspiration ratio depends uniquely on the annual index of dryness, and that the form of that dependence need not be known a priori nor be identical across basins. In application of the weak extension, the readily observed sensitivity of streamflow to precipitation contains crucial information about the sensitivity to potential evapotranspiration and, thence, to temperature. Implementation of the strong extension is problematic, whereas the weak extension appears to capture essential controls of the temperature effect efficiently. [ABSTRACT FROM AUTHOR]

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Accurate estimation of reference evapotranspiration (ETo) is essential for water resources management and irrigation systems scheduling, especially in arid and semiarid regions such as Iran. In the present research, constant coefficients of Hargreaves–Samani (CH–S) and Priestley–Taylor (CP–T) equations were locally calibrated to estimate the ETobased on the FAO–Penmen–Monteith (PM) method as standard method. For this purpose, meteorological data of eight synoptic stations located in the northwest of Iran were used during the period of 1997–2008. The outcomes showed that the values ofCH–SandCP–Twere 0.0026 (instead of 0.0023) and 1.68 (instead of 1.26), respectively. Also, at stations with high wind speed, the values of calibrated coefficients ofCH–SandCP–Twere maximum. Then, the estimated ETovalues using adjustedCH–SandCP–Tcoefficients were compared to the obtained actual ETovalues by PM method using root mean square error and mean bias error indices. The results indicated that the new calibrated H–S and P–T equations have good agreement with the PM method for estimation of the ETo. Moreover, the equation of Ravazzani et al. was calibrated in the studied region. It was concluded that in general, the mentioned equation was shown better performance than original H–S equation. [ABSTRACT FROM PUBLISHER]

Accurate estimation of reference crop evapotranspiration (ET 0 ) is important due to its crucial role in determining crop water requirement in irrigated agriculture. Though a great number of models have been developed, their rigorous evaluation with measurements is still lacking, leading to confusion and arbitrariness in model selection. In this paper daily estimates of 16 ET 0 models, including five combination-, six radiation and five temperature-based ones, were compared with weighing lysimeter measurements during crop growing season (April through October) in 2012 at a semiarid site in China. Daily ET 0 was measured by two weighing lysimeters (area 1.3 m × 1.3 m, depth 2.3 m) located in a fescue grass ( Festuca arundinacea Schreb) plot (100 m × 100 m) surrounded by a 167 ha crop, winter wheat rotated with summer maize. We found the models were ranked decreasingly as: FAO-ppp-17 Penman > 1963 Penman > FAO-24 Blaney-Criddle (BC) > 1996 Kimberly Penman > FAO-24 radiation > FAO-56 Penman-Monteith (PM) > FAO-24 Penman > Turc > DeBruin-Keijman > Jensen-Haise > Priestley-Taylor > Hargreaves > Makkink > Hamon > Blaney- Criddle > Mcloud on basis of RMSE (root mean square error). Overall, the combination models performed best with RMSE ranging from 0.93 to 1.32 mm d −1 , followed by the radiation models with RMSE from 1.28 to 1.79 mm d −1 , and the temperature models with RMSE from 1.09 to 2.48 mm d −1 . The best combination model (FAO-ppp-17 Penman) was respectively 29% and 17% more accurate than the best radiation (FAO-24 radiation) and temperature (FAO-24 BC) models. Better performance of the combination and radiation models resulted because they explicitly contain the dominant factors influencing ET 0 . All models tended to overestimate under low evaporative demand while underestimating the measured values under high demand, but on average the combination and radiation methods underestimated by 0.46 mm d −1 and 0.60 mm d −1 , respectively, whereas the temperature method overestimated by 0.21 mm d −1 . All combination and radiation models, and the Hargreaves and FAO-24 BC in temperature method showed robust structure. To improve them future efforts should be on local calibration, but for temperature models showing structure failure focus should be on its optimization. The coefficients of commonly used models were calibrated and related to meteorological variables. Particularly, those of the Priestley-Taylor, Makkink, Turc and the Hamon were enhanced, while those of the Hargreaves and BC were decreased. In climate similar to the current site in China we suggest continued use of the older Penman equations for combination method and the FAO-24 radiation or Turc for radiation method. Meanwhile, two questions need to be addressed in future studies: i) adoption of the FAO-56 PM equation as the sole standard for computing ET 0 and the proper value for surface resistance; and ii) the effectiveness of the later modifications to the original wind function in the Penman equation. [ABSTRACT FROM AUTHOR]

Actual vapor pressure (VP) is an important parameter that is used in many evapotranspiration equations. However, vapor pressure is difficult to measure accurately. In the humid climate, the actual vapor pressure can be derived from minimum air temperature. The objectives of this study were: first, to estimate errors that can arise if VP data are not available and have to be estimated; second, to compare the Priestley-Taylor ET0 values computed under various levels of VP data availability; and third, to evaluate the reliability of Priestley-Taylor equation as compared to the FAO-56 Penman-Monteith method. The following main conclusions can be drawn: Estimated VP values generally were in closest agreement with measured VP values. The measurements of air humidity at humid locations are not indispensable for estimating reference evapotranspiration. The Priestley-Taylor method (with measured or estimated VP) provides the very good agreement with the evapotranspiration obtained by the FAO-56 Penman-Monteith method except windless locations.

Three methods including the Penman-Monteith (PM), Priestley-Taylor (PT), and 1963 Penman equation (PE) for calculating daily reference evapotranspiration (ETo) were evaluated in the Maritime region of Canada with the data collected from 2004 to 2007. An automatically operated meteorological station located on the Potato Research Centre, Agriculture and Agri-Food Canada, Fredericton, New Brunswick, Canada, was used to collect required meteorological data for evapotranspiration modeling. A Bowen Ratio system (BR) was setup near the Environment Canada grade one weather station to provide evapotranspiration observations for the validation research of reference evapotranspiration models. The results showed that the prediction from each of the tested models had a certain degree of offset in comparison with the observations obtained by the BR method. All of the tested models slightly overestimated evapotranspiration compared to the BR system by 5-14%, depending on the method. However, the PM generated a better fit to the pooled dataset while the PT produced the best prediction for the 2007 validation dataset. The PM generated the best estimation of evapotranspiration for year 2004 during a inter-annual comparison. The BR revealed that the average daytime ET for the site was around 2.5 mm day-1(±0.1) averaged for Julian day 157-276 in 2004 to 2006 and possible condensation was 0.16 mm day-1 for the same period. Crop coefficient (Kc) varied with different models, for example, 0.42 for the PM, 0.44 for the PT, and 0.67 for the PE with a slight yearly variation. With this set of Kc values, a validation with additional dataset collected in 2007 indicated that all three equations achieved a good fit with observations using the above Kc values. The PT performed slightly better than the other two models. A single factor analysis did not show any statistically significant difference between predicted and measured ET. With a consideration of simplicity and application for scaling up to landscape, this research suggested that the PT is the preferable method for estimating ET values in this region.

Satellite remote sensing technology provides a promising means for near real-time monitoring of crop water status and requirements in agricultural and hydrological applications. Estimation of actual evapotranspiration (ET a) often requires thermal information; however, not every satellite is equipped with a thermal sensor, which limits the estimation of ET a. To address this limitation, here we propose a satellite-based ET a estimation model, OPTRAM-ET, based on the optical trapezoid model (OPTRAM) estimates of soil moisture and a vegetation index (VI). We applied the OPTRAM-ET model to Sentinel-2 and Landsat-8 satellite data and evaluated the model for ET a estimates using 16 eddy covariance flux towers in the United States and Germany with different landcover types, including agriculture, orchard, permanent wetland, and foothill forests. Next, OPTRAM-ET was compared with the conventional land surface temperature (LST)-VI model. The proposed OPTRAM-ET model showed promising performance over all the studied landcover types. In addition, OPTRAM-ET showed comparable performance to the conventional LST-VI model. However, since the OPTRAM-ET model does not need thermal data, it benefits from higher spatial and temporal resolution data provided by ever-increasing drone- and satellite-based optical sensors to predict crop water status and demand. Unlike the LST-VI model, which needs to be calibrated for each satellite image, a temporally-invariant region-specific calibration is possible in the OPTRAM-ET model. Therefore, OPTRAM-ET is substantially less computationally demanding than the LST-VI model. • OPTRAM-ET is a novel method for remote sensing of ET a. • OPTRAM-ET relies on optical reflectance data and does not require thermal data. • Its estimates agree well with eddy covariance data of ET a. • Only a one-time calibration of OPTRAM-ET is required for each region. • A new linkage between ET a and SWIR-derived soil moisture was established. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a critical component in the hydrological cycle. However, its actual values appear to be difficult to obtain, especially in areas in which precipitation has high inter-annual variability. Here, we evaluated eight commonly used ET models in semi-arid and semi-humid areas of China. The order of overall performance from best to worst is as follows: the revised Priestley-Taylor model (PT-JPL, 0.71, 1.65 [18.37%], 4.72 [49.19%]), the modified PT-JPL model (M1-PT-JPL, 0.67, −0.68 [7.56%], 3.87 [40.31%]), the Community Land Model (CLM, 0.68, −2.52 [28.01%], 5.10 [53.17%]), the modified PT-JPL model (M2-PT-JPL, 0.63, 0.57 [6.27%], 5.04 [52.52%]), the revised Penman-Monteith model (RS-PM, 0.62, 3.56 [37.40%], 6.11 [63.68%]), an empirical model (Wang, 0.59, −1.04 [11.57%], 5.61 [58.43%]), the advection-aridity model (AA, 0.55, 5.56 [61.78%], 7.45 [77.60%]), and the energy balance model (SEBS, 0.35, 5.11 [56.72%], 9.43 [98.18%]). The performance of all of the models is comparably poor in winter and summer, except for the PT-JPL model, and relatively good in spring and autumn. Because of the vegetation control on ET, the Wang, RS-PM, PT-JPL, M1-PT-JPL, and M2-PT-JPL models perform better for cropland, whereas the AA model, SEBS model and CLM perform better for grassland. The CLM, PT-JPL, and Wang models perform better in semi-arid region than in semi-humid region, whereas the opposite is true for SEBS and RS-PM. The AA, M1-PT-JPL, and M2-PT-JPL models perform similarly in semi-arid and semi-humid regions. When considering the inter-annual variability in precipitation, the Wang model has relatively good performance under only some annual precipitation conditions; the performance of the PT-JPL and AA models is reduced under conditions of high precipitation; the two modified PT-JPL models inherited the steady performance of the PT-JPL model and improved the performance under conditions of high annual precipitation by the modification of the soil moisture constraint. RS-PM is more appropriate for humid conditions. CLM and PT-JPL models could be effectively applied to all precipitation conditions because of their good performance across a wide annual precipitation range. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Using high-quality dataset from 12 flux towers in north China, the performance of four evapotranspiration (ET) models and the multi-model ensemble approaches including the simple averaging (SA) and Bayesian model average (BMA) were systematically evaluated in this study. The four models were the single-layer Penman-Monteith (P-M) model, the two-layer Shuttleworthe-Wallace (S-W) model, the advection-aridity (A-A) model, and a modified Priestley-Taylor (PT-JPL). Based on the mean value of Taylor skill ( S) and the regression slope between measured and simulated ET values across all sites, the order of overall performance of the individual models from the best to the worst were: S-W (0.88, 0.87), PT-JPL (0.80, 1.17), P-M (0.63, 1.73) and A-A (0.60, 1.68) [statistics stated as (Taylor skill, regression slope)]. Here, all models used the same values of parameters, LAI and fractional vegetation cover as well as the forcing meteorological data. Thus, the differences in model performance were mainly attributed to errors in model structure. To the ensemble approach, the BMA method has the advantage of generating more skillful and reliable predictions than the SA scheme. However, successful implementation of BMA requires accurate estimates of its parameters, and some degradation in performance were observed when the BMA parameters generated from the training period were used for the validation period. Thus, it is necessary to explore the seasonal variations of the BMA parameters according the different growth stages. Finally, the optimal conditional density function of half-hourly ET approximated well by the double-exponential distribution. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Studies examining potential evapotranspiration (PET) for a mature forest reference compared with standard grass are limited in the current literature. Data from three long-term weather stations located within 10 km of each other in the USDA Forest Service Santee Experimental Forest (SEF) in coastal South Carolina were used to (1) evaluate monthly and annual PET estimates from five different methods with varying complexities [Penman-Monteith (P-M), Turc, Thornthwaite (Thorn), Priestley-Taylor (P-T), and Hargreaves-Samani (H-S)] at two grass reference sites; and (2) compare results for the grass sites with PET estimated using the P-M method for a forest reference site using measured daily climatic data for the 2011-2014 period. The grass reference sites are located at the SEF headquarters (SHQ) and in the Turkey Creek watershed (TC). The forest reference station is on a 27-m-tall tower above the canopy of a pine/mixed hardwood forest in watershed WS80 in the SEF. At the WS80 forest site, the highest annual PET (1,351 mm) was observed in 2011 with the lowest rainfall (934 mm), and the lowest PET (1,017 mm) was observed in 2013 with the highest rainfall (1,433 mm), which is consistent with the two grass sites. The temperature-based H-S method yielded estimated monthly and annual PETs that were in better agreement than those of another temperature-based Thorn method at both grass sites when compared against the P-M PET for the forest site. The P-M-based PET values estimated for the SHQ grass site were significantly lower (α = 0.05) than those obtained at the TC grass site and the P-M PET values for the WS80 forest site. The solar radiation-based Turc and temperature-based Thorn PET estimates at both grass sites were significantly different (α = 0.05) from the P-M PET estimates for the forest. These results for the grass sites demonstrate that PET estimates are sensitive to the method used, resulting in significantly different estimates using a single method even for nearby sites because of differences in the complexity of describing the PET process, climatic factors, and interaction with site vegetation types. When compared with the P-MPET for the forest site, the P-T method was in the closest agreement, with the highest R² of 0.96 and the least bias of 9.7% in mean monthly estimates, followed by the temperature-based H-S with an R² of 0.95 and a bias of 12.6% at the SHQ grass site. It is concluded that the simpler P-T and H-S methods appear to be adequate to estimate forest P-M PET and that their estimates are within the error bounds of the data-intensive P-M PET method for coastal forests. [ABSTRACT FROM AUTHOR]

• Accuracy of evaporation simulation methods was evaluated by flux observations. • The accuracy of each method varied significantly at different sites. • The combination of methods proposed in this study showed the best performance. • The calibrated method showed high stability in simulating daily evaporation. • Optimization of parameters may improve the accuracy of the Penman and PT equations. Evaporation from the surface of water is a vital component of the hydrological cycle. Accurately simulating evaporation is crucial for modeling hydrological processes, ensuring ecosystem water efficiency, and managing water resources. Previous methods for evaluating evaporation have generally been limited to a single site and on a regional scale. Based on eddy covariance measurements of 14 boreal flux sites, the accuracy of 26 methods for simulating daily water surface evaporation was comprehensively evaluated in this study. Most methods accurately simulated daily evaporation at most sites with a KGE >0.60. The combination methods with simultaneous calibration of the energy and aerodynamic terms and the double-parameter aerodynamic methods based on the linear and exponential functions showed the best performance, with the median KGE of the evaluated sites ranging from 0.72 to 0.76. The Bowen ratio energy balance (BREB) method embedded with Tw, Rs-based two-variable empirical methods, double-parameter aerodynamic methods, and the combination method of the energy term based on net radiation (Rn) and the aerodynamic term based on the exponential function method performed better than the other methods of the same type. The relative error (RE) simulated by most methods was generally within ± 30 %, with the median RE of all sites within ± 10 % for each method. The combination methods tended to overestimate the level of evaporation, whereas the BREB-type and aerodynamic methods tended to underestimate the extent of evaporation. The simulation accuracy of the daily evaporation showed significant variance among the sites. It showed the best model performance at two FLUXNET and two sites taken from the literature, in which 75 % of the methods were able to accurately simulate daily evaporation with a Kling–Gupta efficiency (KGE) >0.80. All methods performed poorly at the three sites from the literature and were mainly due to the lack of measured variables with a strong correlation with the latent heat flux (LE). The FLUXNET sites generally showed better performance. The observed LE of the sites with the best model performance generally showed a unimodal distribution throughout the year. The simulation accuracy of non-unimodal distribution sites mainly depended on the correlation between the LE and related variables. The combination of the energy term based on Rn and the aerodynamic term based on the power function method showed the best model stability. This finding indicated that the calibrated method was robust and showed high stability in simulating daily evaporation, and it was recommended for application in other sites or regions. The optimization of parameters calibrated in this study may improve the accuracy of simulating the daily evaporation for the application of the Penman and Priestley–Taylor equations when the water heat storage measurement is missing. [ABSTRACT FROM AUTHOR]

Effective water use in the irrigated agriculture requires an accurate estimation of evapotranspiration (ET) to understand the interaction between land surface and the atmosphere. The operationally available polar orbit satellite datasets with low temporal resolutions have long been utilized for the estimation of ET from field to regional scale. However, geostationary satellites, which are continuously measuring several factors related to land surface and the atmosphere over large regional scales, have high temporal resolution compared to polar orbit satellites. Thus, in this study, we present a framework for estimating potential ET at three different temporal scales (instantaneous, 3-h and daily) using the Priestley–Taylor (ET PT ) method with a new geostationary satellite, the Communication, Ocean, and Meteorological Satellite (COMS) dataset. The derived ET PT estimates were compared with ground based flux tower [Cheongmi (CFC) and Sulma (SMC)] measurements, with ET PT calculated from MODerate Resolution Imaging Spectroradiometer (MODIS) and with ET PT calculated from Global Land Data Assimilation System (GLDAS) datasets during the growing seasons of 2011. The GLDAS ET PT were significantly overestimated compared to the flux tower ET PT (bias of 147.92 and 169.69 W m −2 at 3-h time scale and bias of 2.64 and 3.37 mm day −1 at daily time scale for SMC and CFC, respectively), while the COMS and MODIS ET PT were slightly underestimated (bias ranged from −15.31 to −55.65 W m −2 at instantaneous time scale and bias ranged from −0.04 to −1.03 mm day −1 at daily time scale for SMC and CFC, respectively). Based on the results, the COMS estimated ET PT was slightly more accurate than MODIS ET PT in comparison with the flux tower ET PT , yielding the index of agreement (IOA) between ∼0.89 and 0.96 for all time scale. [ABSTRACT FROM AUTHOR]

• Bowen Ratio-Energy Balance data were used to evaluate the CSM-CROPGRO-Soybean. • CROPGRO-Soybean model was able to accurately simulate daily evapotranspiration. • FAO-56 (PM) with Ritchie Two-Stage methods provided the best fit for simulated ET. • The CROPGRO-Soybean can be a potential tool for predicting crop water productivity. Prediction of crop yield, evapotranspiration, and crop water productivity are essential aspects for water management and the sustainable intensification of agriculture. The goal of this study was to evaluate the Cropping System Model (CSM)-CROPGRO-Soybean model for simulating evapotranspiration and crop water productivity of soybean grown in a tropical environment. Energy balance evapotranspiration was measured daily using a Bowen Ratio Energy Balance (BREB) system for irrigated experiments that were conducted in Piracicaba, SP, Brazil, during the 2016-2017 and 2017-2018 growing seasons. Evapotranspiration was simulated with the CROPGRO-Soybean model using either the Priestley–Taylor or the FAO-56 Penman–Monteith method for potential ET combined with either the Ritchie-Two-Stage or the Suleiman–Ritchie soil water evaporation methods. The model provided good predictions of daily (D-statistic > 0.7) and cumulative evapotranspiration (RMSE ranged from 8 to 64 mm). FAO-56 Penman–Monteith with the Ritchie-Two-Stage method provided a better fit than the Priestley–Taylor with Suleiman–Ritchie when compared with measured data. Simulated crop water productivity agreed well with observed, but with a systematic underprediction (variation between simulated and measured ranged from -2.2 to -16.8 %). Simulation of long-term scenarios was conducted for different tropical environments, i.e., Piracicaba and Teresina, with soil tillage and water management practices. The results demonstrated that the implementation of no-tillage can increase 0.1 kg/m3 (11%) crop water productivity for grain. This study also showed that when irrigation was triggered at more than 60% of available soil water, irrigation did not result in an increase in yield despite an increase in water supply. [ABSTRACT FROM AUTHOR]

Highlights: [•] Model inter comparison between SEBS, Penman-Monteith, advection-aridity and modified Priestley–Taylor was undertaken. [•] High resolution data from 20 towers over five biomes for long periods of time were used. [•] Ensemble mean outperformed other models, followed by the Modified PT and SEBS. [•] Penman–Monteith and advection-aridity models showed reduced performance. [•] No single model was consistently best across all biomes. [Copyright &y& Elsevier]

Over the past decade, British Columbia (BC), has experienced the largest mountain pine beetle (MPB) outbreak on record. This study used the eddy-covariance (EC) technique to examine the impact of the MPB attack on evapotranspiration ( E) and associated canopy characteristics of two lodgepole pine stands with secondary structure (trees, saplings and seedlings surviving the attack) located in central BC. MPB-06, an 85-year-old almost pure stand of pine trees, was first attacked in 2006, and by 2010, ~80% of the trees had been killed. MPB-03, a 110-year-old stand with an overstory consisting of over 90% pine and a developed sub-canopy, was first attacked in 2003 and by 2007 had > 95% pine canopy mortality. EC measurements began in August 2006 at MPB-06 and in March 2007 at MPB-03, and continued for four years. Annual total E ranged from 226 mm to 237 mm at MPB-06, and from 280 to 297 mm at MPB-03, showing relatively little year-to-year change at both sites over the four years. Increased E from the accelerated growth of the surviving vegetation (secondary structure, shrubs and herbs) compensated for reduction in E due to the death of the overstory. Monthly average daytime canopy conductance, the Priestley-Taylor ( α), and the canopy-atmosphere decoupling coefficient (Ω) steadily increased during the growing season reaching approximate maximum values of 5 mm s−1, 0.75 and 0.12, respectively. Potential evapotranspiration was approximated using a vapour pressure deficit-dependent α obtained at high soil water content. Calculated water deficits indicated some water-supply limitation to the surviving trees and understory at both sites. Rates of root zone drainage during the growing season were low relative to precipitation. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: Evapotranspiration (ET) is a key component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. Several satellite-based ET models have been developed for extrapolating local observations to regional and global scales, but recent studies have shown large model uncertainties in ET simulations. In this study, we compared eight ET models, including five empirical and three process-based models, with the objective of providing a reference for choosing and improving methods. The results showed that the eight models explained between 61 and 80% of the variability in ET at 23 eddy covariance towers in China and adjacent regions. The mean annual ET for all of China varied from 535 to 852mmyr−1 among the models. The interannual variability of yearly ET varied significantly between models during 1982–2009 because of different model structures and the dominant environmental factors employed. Our evaluation results showed that the parameters of the empirical methods may have different combination because the environmental factors of ET are not independent. Although the three process-based models showed high model performance across the validation sites, there were substantial differences among them in the temporal and spatial patterns of ET, the dominant environment factors and the energy partitioning schemes. The disagreement among current ET models highlights the need for further improvements and validation, which can be achieved by investigating model structures and examining the ET component estimates and the critical model parameters. [Copyright &y& Elsevier]

Accurate land surface evapotranspiration (ET) estimations over a heterogeneous ecosystem are important to understand the interaction between the land surface and atmosphere including practical applications in integrated water resources management. Though numerous studies have been adopted and developed based on remote sensing technology to make a more accurate prediction of regional ET distribution, there has been still degree of uncertainty due to high spatio-temporal variability of the ecohydrologic parameter. This study suggested the revised remote sensing-based Penman–Monteith (Revised RS-PM) model and Trapezoid Interpolation Model (TIM) using only remotely sensed data as input data to assess applicability over complex topography in East Asia. Ground observations at the two flux sites having different land surface conditions were used to evaluate intra-annual seasonality in 2008. Both models represented temporal compatibility yielding biases of −74.25–38.79Wm−2 and Root Mean Square Error (RMSE) values of 68.96–90.90Wm−2 while the models consistently overestimated ET at the forests due to large amount of interception relatively restraining sufficient water supply to the plants. The revised RS-PM showed slight overestimation due to the overvalued Leaf Area Index (LAI) as an input parameter and classified parameterization in transpiration calculation. This algorithm was developed for global mapping of ET so that errors occurring from vegetation parameterization are inevitable. TIM reproduced higher ET than the measurements in a non-growing season since remotely sensed Normalized Difference Vegetation Index (NDVI) as an input parameter could be affected by cloud contamination. In contrast to the dormant season, the revised RS-PM estimated a larger amount of ET distribution than TIM in the growing season. A conservative estimation of TIM was mainly caused by the structural characteristics. Relationships between the land surface temperature and NDVI were contextually used to determine both maximum and minimum limits of the Priestley–Taylor parameters in the image data. Determination of the contextual relationship should be carefully conducted to achieve reliable estimations. Results of a sensitivity analysis shows that the net radiation (RN ) plays the most significant role in both models (±17–20% for ET by ±20% change of RN ). Variation of LAI impacted ET mostly in the revised RS-PM in a dormant season due to a logarithmic relationship between canopy conductance and LAI. TIM, on the other hand, was barely affected by LAI because of the simple structure of the algorithm including the Priestley–Taylor equation. The results suggest that the models can be applied to a regional scale with heterogeneous topography over long term periods if the input data handling is carefully conducted. In particular, the models can be usefully applied where ground ancillary data are not readily available. [ABSTRACT FROM AUTHOR]