Terrestrial Evapotranspiration Research Articles

Evapotranspiration over a rainfed maize field in northeast China: How are relationships between the environment and terrestrial evapotranspiration mediated by leaf area?

As a central process in the hydrological system and the climate system, terrestrial evapotranspiration is a key factor furthering our understanding of the climate change processes. Knowledge of factors controlling the variability in evapotranspiration is crucial for the prediction of the fate of terrestrial ecosystems under environmental changes. Based on long-term (2005–2014) eddy covariance flux data observed at a rainfed maize site in northeast China, the purpose of this study was to clarify the environmental regulation of actual evapotranspiration (ET) and the extent to which the regulatory effects on ET are directly or indirectly mediated by changes in biotic factors, using the structural equation modeling (SEM) method. The results showed that annual total ET was 397 ± 35 mm for the rainfed maize site in comparison with 575 ± 169 mm of precipitation (Prec), with an ET/Prec ratio ranging from 0.43 (2012) to 1.14 (2014). It was revealed that net radiation (Rn) was the primary controlling factor of the maize ET, followed by leaf area index (LAI), vapor pressure deficit (VPD), air temperature (Ta), and soil water content (SWC). The adjusted SEM models explained 71%, 67%, and 67% of the variation in daily ET of the maize growing season (ETgs) for dry, normal, and moist years, respectively. Rn and VPD dominated ETgs in an increasing order of dry, normal, and moist years. Conversely, the effects of LAI and Ta on ETgs followed the opposite trend. This indicated that drought may increase the sensitivity of maize ET to temperature changes, and decrease the sensitivity of maize ET to radiation changes. In SEM analysis, LAI played an important mediating role in the relationship among climate, soil variables, and ETgs. Rn, VPD, Ta, and SWC all had significant indirect effects on ETgs mediated through LAI. At the annual scale, it was identified that most active days could be a robust predictor of annual ET.

Evapotranspiration and its dominant controls along an elevation gradient in the Qinghai Lake watershed, northeast Qinghai-Tibet Plateau

Evapotranspiration (ET) and its dominant controls show obvious elevational pattern on the Qinghai-Tibet Plateau, due to heterogeneous environmental conditions regulated by altitude. To understand better how and why ET varies at different altitudes in the Qinghai Lake watershed, this study measured and retrieved soil moisture, solar radiation, and ET data between 3300 m and 4700 m, and further investigated the influence of water and energy conditions on ET. Results showed that, the mean annual terrestrial ET was 343 and 360 mm in this watershed in 2014 and 2015, respectively. The higher ET mainly appeared in the midstream of Shaliu River and on the southern region of Qinghai Lake, while the sand land on the east of Qinghai Lake and the bare rock in the northwest of the watershed had the lowest values. The ET increased firstly and then decreased with the increase of altitude, and its peak value appeared at 3600–3700 m. The dominant controls for ET switched from water conditions to energy conditions with the increase of elevation. The maximum limited fraction [(predicted value – actual value)/predicted value × 100] of ET by water condition (soil moisture content) achieved 11.2% and 10.1% at 3300–3350 m in 2014 and 2015, and the corresponding mean area-weighted values were 7.3% and 5.4% at 3300–3650 m, respectively. The maximum limited fraction of ET by energy condition (shortwave radiation and air temperature) achieved 24.4% and 29.8% at 4650–4700 m in 2014 and 2015, and the corresponding mean area-weighted values were 10.8% and 11.9% at 3650–4700 m, respectively. Overall, the energy conditions were more influential factors limiting the ET in the entire watershed, and this conclusion is critical for the management of regional terrestrial ecosystem with future climate change.

Complementary‐Relationship‐Based Modeling of Terrestrial Evapotranspiration Across China During 1982–2012: Validations and Spatiotemporal Analyses

AbstractHaving recognized the limitations in spatial representativeness and/or temporal coverage of (i) current ground ETa observations and (ii) land surface model‐ and remote sensing‐based ETa estimates due to uncertainties in soil and vegetation parameters, a calibration‐free nonlinear complementary relationship (CR) model is employed with inputs of air and dew‐point temperature, wind speed, and net radiation to estimate 0.1°, monthly ETa over China during 1982–2012. The modeled ETa rates were first validated against 13 eddy‐covariance measurements, producing Nash‐Sutcliffe efficiency values in the range of 0.72–0.94. On the basin scale, the modeled ETa values yielded a relative bias of 6%, and a Nash‐Sutcliffe efficiency value of 0.80 in comparison with water‐balance‐derived evapotranspiration rates across 10 major river basins in China, indicating the CR‐simulated ETa rates reliable over China. Further evaluations suggest that the CR‐based ETa product is more accurate than seven other mainstream ETa products. The 31‐year mean annual ETa value decreases from the southeast to the northwest in China, resulting in a country average of 406 ± 15 mm/year. The country‐representative annual ETa rates slightly decreased with a rate of −0.5 mm/year (p = 0.86) during 1982–2012. Annual ETa increased significantly over most parts of western and northeastern China but decreased significantly in many regions of the North China Plain as well as in the eastern and southern coastal regions. The present CR‐based method, with its calibration‐free nature and minimal data requirement, could help future calibrations/verifications of the more complex and more data‐intensive land surface model‐ and remote sensing‐based models.

Attribution analysis of actual and potential evapotranspiration changes based on the complementary relationship theory in the Huai River basin of eastern China

Accurate terrestrial evapotranspiration (ET) estimation and understanding the causes of ET variation are essential for water resource management and irrigation planning. In this research, the complementary relationship (CR) between actual evapotranspiration (ETa) and potential evapotranspiration (ETp) was evaluated. An Advection–Aridity (AA) model was calibrated and validated using eddy covariance measurements. The spatiotemporal variations of ETa, ETp and associated meteorological variables were examined through Mann–Kendall (MK) testing and Theil–Sen's estimator, using daily weather data from 137 meteorological stations in Huai River basin (HRB) during 1961–2014. Moreover, the influences of meteorological factors on ETa and ETp were quantified by the differential equation method. The results indicate that CR theory is applicable in the HRB and the calibrated AA model can simulate the ETa well. ETa exhibited a significant increasing trend before 1990 and then decreased significantly. However, ETp decreased significantly before 1990 and then declined slightly. During 1961–1990, except for significant increasing relative humidity (RH), other meteorological variables exhibited decreasing trends. The aerodynamic component dominated ETa and ETp trends in general. The wind speed at 2‐m height (u2) dominated ETa trends except for summer and growing season and ETp trends except for summer, when the dominant factor is net radiation (R n). During 1991–2014, mean temperature (T a) and RH showed distinct increasing and decreasing trends, respectively, whereas significant decline in u2 palpably slowed. The absolute value of the radiative component was larger than that of the aerodynamic one. The dominant factor of ETa trends shifted from u2 to RH in spring and to R n in autumn, winter and annual timescales. Moreover, the dominant factor of ETp trends changed from u2 to RH in spring, winter and annual timescales and to R n in growing season and autumn. R n always played a pivotal role in both ETa and ETp trends in summer.

Simulation of evapotranspiration for the mobile and semi-mobile dunes in the Horqin Sandy Land using the Shuttleworth-Wallace model.

Terrestrial evapotranspiration (ET) plays a crucial role in climate regulation and the maintenance of regional water balance. Quantitative estimation of ET and its partitioning are important for revealing the eco-hydrological processes in arid and semi-arid areas. Using the in situ data sampled by the meteorological monitoring system, the Shuttleworth-Wallace (S-W) model was applied to simulate and partition ET in the mobile and semi-mobile dunes of the Horqin sandy land during the growing season in 2017. The eddy covariance system was used to verify the simulated ET. The results were as follows: the simulated ET (308 mm) was very close to the eddy covariance observed ET (296 mm) during the whole growing season, indicating the applicability of the S-W model for ET estimation in this area. The ET rate at the vigorous growth stage (192 mm) was larger than those at the late and early growth stages (71 and 45 mm, respectively) which accounted for 62.3%, 23.1%, and 14.6% of the total, respectively. The simulated ET was close to the eddy covariance observed ET at the daily time-scale. The simulation performance of the S-W model for clear days was better than for cloudy or rainy days. The simulated ET rate was always smaller than the eddy covariance observed ET in the cloudy or rainy days. According to the model, the evaporation (E) from soil was 176 mm and the transpiration (T) from plants was 132 mm, accounting for 57.1% and 42.9% of the ET, respectively, suggesting that water use efficiency of the sand dune was low. The characteristics of ET varied substantially under the sustained drought and precipitation events. Compared to T from plants, E from soil was more sensitive to precipitation.

Parameter Analysis and Estimates for the MODIS Evapotranspiration Algorithm and Multiscale Verification

AbstractAccurate estimation of terrestrial evapotranspiration (E) is critical to understand the world's energy and water cycles. MOD16 is the core algorithm of the widely used global E data set (the Moderate Resolution Imaging Spectroradiometer [MODIS] E product). However, it exhibits considerable uncertainties in some regions. Based on the data from 175 flux towers, we identified the key parameters of the MOD16 algorithm using the Sobol’ sensitivity analysis method across biomes. The output of the MOD16 algorithm was sensitive to eight parameters. Among them, β, which is treated as a constant (0.2 kPa) across biomes in the original MOD16 algorithm, was identified as the parameter to which the algorithm was most sensitive. We used the differential‐evolution Markov chain method to obtain the proper posterior distributions for each key parameter across a range of biomes. The values of the key parameters for the different biomes were accurately estimated by differential‐evolution Markov chain in comparison with data from the flux towers. We then evaluated the performances of the original MOD16 and the optimized MOD16 and compared them at multiple spatial scales (i.e., site, catchment, and global). We obtained relatively consistent and more reliable E simulations using the optimized MOD16 at all three scales. In the future, more attention should be paid to uncertainties in the algorithm's structure and its parameterizations of soil moisture constraint, canopy resistance, and energy partitioning.

A Global Assessment of Terrestrial Evapotranspiration Increase Due to Surface Water Area Change.

Surface water, which is changing constantly, is a crucial component in the global water cycle, as it greatly affects the water flux between the land and the atmosphere through evaporation. However, the influences of changing surface water area on the global water budget have largely been neglected. Here we estimate an extra water flux of 30.38 ± 15.51 km3/year omitted in global evaporation calculation caused by a net increase of global surface water area between periods 1984–1999 and 2000–2015. Our estimate is at a similar magnitude to the recent average annual change in global evapotranspiration assuming a stationary surface water area. It is also comparable to the estimated trends in various components of the hydrological cycle such as precipitation, discharge, groundwater depletion, and glacier melting. Our findings suggest that the omission of surface water area changes may cause considerable biases in global evaporation estimation, so an improved understanding of water area dynamics and its atmospheric coupling is crucial to reduce the uncertainty in the estimation of future global water budgets.

Hysteresis in sap flow and its controlling mechanisms for a deciduous broad-leaved tree species in a humid karst region

The critical zone (CZ) represents the intersection of the biosphere with the atmosphere, hydrosphere and lithosphere. Understanding the hydrological processes and human impact factors on the CZ is fundamental to sustainable water resources management for agroforestry. Transpiration ( T ) is an important component of terrestrial evapotranspiration (ET), and understanding the time lag (TL) between vegetation transpiration and meteorological factors can improve our knowledge of the mechanisms of vegetation adaptability to a changing environment. However, the controlling factors on the TL remain poorly understood. Therefore, the objective of this study is identifying the temporal dynamics of key controlling factors on the TL, using a typical deciduous broad-leaved tree species ( Zenia insigins Chun) of CZ in subtropical humid karst regions. This species is used as an example to explore the characteristics of the TL between SF (sap flow) and hydro-meteorological forcing. Sap flow in these 6 trees was monitored using the thermal dissipation probes (TDP). Results showed that: (1) the peak of diurnal sap flow generally lagged behind PAR but preceded Ta (air temperature), RH (relative humidity) and VPD (vapor pressure deficit), with the mean TL of −67.4 min (PAR), 90.5 min ( Ta ), 91.6 min (RH) and 92.9 min (VPD), respectively; (2) TL had no significant relationships with the daily mean meteorological factors and soil moisture, but was highly ( R 2>0.66) correlated to CRs (changing rates of meteorological factors) in the morning; (3) At seasonal scale, the sap flow rate and TL both were controlled by the seasonality of precipitation and temperature. Overall, the seasonality of the TL was caused by plants’ high water loss and strongly active physiological response in hot seasons, leading to close stomata earlier than in cold seasons; (4) The reason why CRs proposed can explain the TL better than mean values of metrological factors is that the CRs considered the distribution and change processes of metrological factors in the daytime. This study may be helpful for understanding the physiological response of vegetation to climatic change, and may be useful for constructing models to simulate transpiration processes more accurately during a day.

Evaluation of ten machine learning methods for estimating terrestrial evapotranspiration from remote sensing

Remote sensing retrieval of evapotranspiration (ET), or surface latent heat exchange (LE), is of great utility for many applications. Machine learning (ML) methods have been extensively used in many disciplines, but so far little work has been performed systematically comparing ML methods for ET retrieval. This paper provides an evaluation of ten ML methods for estimating daily ET based on daily Global LAnd Surface Satellite (GLASS) radiation data and high-level Moderate-Resolution Imaging Spectroradiometer (MODIS) data products and ground measured ET data from 184 flux tower sites. Measurements of accuracy (RMSE, R2, and bias) and run time were made for each of ten ML methods with a smaller training data set (n = 7910 data points) and a larger training data set (n= 69,752 data points). Inclusion of more input variables improved algorithm performance but had little effect on run time. The best results were obtained with the larger training data set using the bootstrap aggregation (bagging) regression tree (validation RMSE = 19.91 W/m2) and three hidden layer neural network (validation RMSE = 20.94 W/m2), although the less computationally demanding random kernel (RKS) algorithm also produced good results (validation RMSE = 22.22 W/m2). Comparison of results from sites with different ecosystem types showed the best results for evergreen, shrub, and grassland sites, and the weakest results for wetland sites. Generally, performance was not improved by training with data from only the same ecosystem type.

Seasonality of the Transpiration Fraction and Its Controls Across Typical Ecosystems Within the Heihe River Basin

AbstractUnderstanding the seasonality of the transpiration fraction (T/ET) of total terrestrial evapotranspiration (ET) is vital for coupling ecological and hydrological systems and quantifying the heterogeneity among various ecosystems. In this study, a two‐source model was used to estimate T/ET in five ecosystems over the Heihe River Basin. In situ measurements of daily energy flux, sap flow, and surface soil temperature were compared with model outputs for 2014 and 2015. Agreement between model predictions and observations demonstrates good performance in capturing the ecosystem seasonality of T/ET. In addition, sensitivity analysis indicated that the model is insensitive to errors in measured input variables and parameters. T/ET among the five sites showed only slight interannual fluctuations while exhibited significant seasonality. All the ecosystems presented a single‐peak trend, reaching the maximum value in July and fluctuating day to day. During the growing season, average T/ET was the highest for the cropland ecosystem (0.80 ± 0.13), followed by the alpine meadow ecosystem (0.79 ± 0.12), the desert riparian forest Populus euphratica (0.67 ± 0.07), the Tamarix ramosissima Ledeb desert riparian shrub ecosystem (0.67 ± 0.06), and the alpine swamp meadow (0.55 ± 0.23). Leaf area index exerted a first‐order control on T/ET and showed divergence among the five ecosystems because of different vegetation dynamics and environmental conditions (e.g., water availability or vapor pressure deficits). This study quantified transpiration fraction across diverse ecosystems within the same water basin and emphasized the biotic controls on the seasonality of the transpiration fraction.

The Grain for Green Project intensifies evapotranspiration in the revegetation area of the Loess Plateau in China

The Grain for Green Project (GFGP) in Chinas Loess Plateau significantly influences regional vegetation growth and water cycles, especially the inter-annual variability of terrestrial evapotranspiration (ET). In this study, we analyzed the spatial-temporal variations of ET and its driving factors before the period of (1982−1997) and after implementing of the GFGP in the revegetation area of the Loess Plateau during 2001−2015. Firstly, three sets of ET products are collected herein, including global flux product evapotranspiration (FLUXNET ET, FET), model simulation WB-MTE-ET (WET) and GLEAM ET (GET). To evaluate the performance of the ET products in the Loess Plateau, we calculated the mean annual streamflow ( Q mod) based on the water balance equation with three sets of ET products against the observed mean annual streamflow ( Q obs) at seven catchments over the Loess Plateau. The results indicated that Q mod estimated from GET shows the best agreement with Q obs in terms of both spatial ( R 2=0.97, P 0.01) and temporal ( R 2=0.94, P 0.01) variations. Thus, we selected GLEAM ET (GET) products in the following analysis. Secondly, we analyzed the trend of annual NDVI and ET in the growing season before and after implementing of the GFGP in the revegetation area using the linear regression. Furthermore, we conducted the stepwise regression analysis to identify the controlling factors that affect the ET changes in the revegetation area during different period. The environmental factors included soil moisture, air temperature, precipitation and averaged Normalized Difference Vegetation Index (NDVI) during the growing season. The results showed that: (1) The inter-annual variability of ET in the revegetation area was significantly increased after implementing of the GFGP compared with that before the GFGP. The inter-annual ET variability also exhibited great spatial differences which showed the highest peak in the regions with annual precipitation ranging from 400 to 600 mm a-1. (2) Compared with the mean air temperature and total precipitation in growing-seasons, the variation of NDVI contributed the most to the changes in ET followed by the soil water content. (3) After implementing of the GFGP, the contribution of the soil water content to ET variation has generally declined, while the contribution of NDVI has increased. This study reveals the influence of the GFGP on the regional water cycle in terms of ET variation, which is of guiding importance to the ecological engineering construction, as well as the rational water resources allocation.

Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017

Accurate quantification of terrestrial evapotranspiration (ET) is essential to understand the Earth's energy and water budgets under climate change. However, despite water and carbon cycle coupling, there are few diagnostic global evapotranspiration models that have complete carbon constraint on water flux run at a high spatial resolution. Here we estimate 8-day global ET and gross primary production (GPP) at 500 m resolution from July 2002 to December 2017 using a coupled diagnostic biophysical model (called PML-V2) that, built using Google Earth Engine, takes MODIS data (leaf area index, albedo, and emissivity) together with GLDAS meteorological forcing data as model inputs. PML-V2 is well calibrated against 8-day measurements at 95 widely-distributed flux towers for 10 plant functional types, indicated by Root Mean Square Error (RMSE) and Bias being 0.69 mm d−1 and −1.8% for ET respectively, and being 1.99 g C m−2 d−1 and 4.2% for GPP. Compared to that performance, the cross-validation results are slightly degraded, with RMSE and Bias being 0.73 mm d−1 and −3% for ET, and 2.13 g C m−2 d−1 and 3.3% for GPP, which indicates robust model performance. The PML-V2 products are noticeably better than most GPP and ET products that have a similar spatial resolution, and suitable for assessing the influence of carbon-induced impacts on ET. Our estimates show that global ET and GPP both significantly (p < 0.05) increased over the past 15 years. Our results demonstrate it is very promising to use the coupled PML-V2 model to improve estimates of GPP, ET and water use efficiency, and its uncertainty can be further reduced by improving model inputs, model structure and parameterisation schemes.

Hydrologic Observation, Model, and Theory Congruence on Evapotranspiration Variance: Diagnosis of Multiple Observations and Land Surface Models

AbstractThis paper reconciles the state‐of‐the‐art observations and simulations of evapotranspiration (ET) temporal variability through a diagnostic framework composed of an observation‐model‐theory triplet. Specifically, a confirmed theoretical tool, Evapotranspiration Temporal VARiance Decomposition (EVARD), is used as a benchmark to estimate ET monthly variance ( ) across the contiguous United States (CONUS) with inputs including hydroclimatic observations, Gravity Recovery and Climate Experiment‐based terrestrial water storage, four observation‐based products (ETRSUW by the University of Washington, ETRSMOD16 from MOD16 Global Terrestrial ET Data Set, ETFLUXNET upscaled from of fluxtower observations, and ETGLEAM from Global Land Evaporation Amsterdam Model), and four operational land surface models (LSMs: MOSAIC, NOAH, NOAH‐MP, and VIC). Five experiments are systematically designed to evaluate and diagnose possible errors and uncertainties in ET temporal variance estimated by the four observation‐based ET products and the four LSM simulations. Based on the results of these experiments, the following diagnostic hypotheses regarding the uncertainty of the observation‐based ET products are illustrated: ETRSUW captures the high signals in the Midwest with negligible bias and moderate uncertainty over the contiguous United States; ETFLUXNET systematically underestimates over CONUS but with the lowest level of uncertainty; ETRSMOD16 has medium bias with the highest level of uncertainty, and the spatial distribution of high signal from ETRSMOD16 is different from other estimates; ETGLEAM has slight negative bias and medium uncertainty, and in the West Coast is smaller than that from ETVARD. Regarding the LSMs, it is found that any of the four LSMs can be the best depending on a certain set of reference observations. The study reveals that LSMs have shown a reasonably worthy, though not perfect, capability in estimating ET and its variability in regions/aquifers with limited human interference. However, RS‐based observations and theoretical estimates suggest that all the four LSMs examined in this study are not able to accurately predict the ET variability in regions/aquifers heavily influenced by human activities like Central Valley and High Plains aquifers; they all underestimate ET variability along the West Coast due to seasonal vegetation responses to Mediterranean climate and human water use. In addition, LSMs underestimate intraannual ET variance in California and the High Plains with underestimated terrestrial storage change components in ET variance, due to the inappropriate representation of groundwater pumping and its impact on ET and other hydrologic processes. This paper urges advancing hydrologic knowledge by finding congruence among models, data, and theories.

Evapotranspiration partitioning at the ecosystem scale using the stable isotope method—A review

Terrestrial evapotranspiration (ET) consists of evaporation (E) from canopy-intercepted water, evaporation from soil and open water, and transpiration (T) from plants. Determining the contribution of T to ET (hereafter T/ET) is challenging but necessary for improving water resource management and understanding the response of ecosystem water/energy budgets to climate change. Water stable isotopes provide unique information on ecosystem processes and can be used to partition evapotranspiration at the ecosystem scale. In this paper, the aim is to review the state of the science on the isotope method for ecosystem ET partitioning, with a focus on uncertainties related to estimating the three isotopic end members (isotopic compositions of ET, T and E). The published results show larger T/ET variations during the growing season in croplands due to water management and rapid leaf area index (LAI) changes compared to in other natural ecosystems. Another robust result is that on average, grasslands have lower T/ET than woodlands. The isotopic composition of ET is provided by measurements, while the isotopic compositions of T and E are generally obtained using the Craig-Gordon model with appropriate modifications. Significant advances have been made in the techniques for estimating the isotopic composition of ET, largely due to the availability of fast-responding instruments for in situ measurements of water vapor isotopic composition. The largest source of uncertainty in the T/ET estimation comes from uncertainties in the isotopic composition of ET. Based on published results of the uncertainties in the three end members, we estimate that a typical uncertainty range for T/ET is ±21% (one standard deviation). This review provides background information and theoretical references for studies on isotopic hydrology, ecosystem processes and climate change.

Integration of two semi-physical models of terrestrial evapotranspiration using the China Meteorological Forcing Dataset

ABSTRACTCombining surface evaporation and plant transpiration, evapotranspiration (ET) is critical to surface water and heat balances as it links water, carbon cycles and energy exchanges. Many models have been developed and are presently used to estimate terrestrial ET. However, there are large model uncertainties among the different models, which present a problem. By combining meteorological reanalysis data from the China Meteorological Forcing Dataset (CMFD) with remote sensing data and observational data during 2002–2009, two semi-physical models, the modified satellite-based Priestley-Taylor (MS-PT) model and a semi-empirical Penman equation-based (SE-PM) model, are used to estimate ET and are validated using in situ measurements collected at 22 flux tower sites in China. Then support vector machine (SVM) method is used to integrate these two semi-physical models to improve the accuracy of ET estimates for eight different vegetation types separately, as well as all of these types together. The integrated model likely explains 56–94% of the land surface ET changes indicated by the observations collected at the flux tower sites. The ET predictions obtained by driving the models with the reanalysis data (for which the relative bias and the relative root mean square error (RMSE) for all types of the SVM were 6 and 51 W m–2, respectively, and the maximum decrease of the relative RMSE for different types is nearly 20 W m–2) are less accurate than those obtained by driving the models with the observational data (for which the relative bias and the relative RMSE for all types of the SVM are 4 and 43 W m–2, respectively). Compared to the individual semi-physical models, the results produced by the integrated model display significantly decreased bias (less than 5 W m–2 for all types) and RMSE (for which the maximum decrease is nearly 71 W m–2) in the validation.

Vegetation Water Use Based on a Thermal and Optical Remote Sensing Model in the Mediterranean Region of Doñana

Terrestrial evapotranspiration (ET) is a central process in the climate system, is a major component in the terrestrial water budget, and is responsible for the distribution of water and energy on land surfaces especially in arid and semiarid areas. In order to inform water management decisions especially in scarce water environments, it is important to assess ET vegetation use by differentiating irrigated socio-economic areas and natural ecosystems. The global remote sensing ET product MOD16 has proven to underestimate ET in semiarid regions where ET is very sensitive to soil moisture. The objective of this research was to test whether a modified version of the remote sensing ET model PT-JPL, proven to perform well in drylands at Eddy Covariance flux sites using the land surface temperature as a proxy to the surface moisture status (PT-JPL-thermal), could be up-scaled at regional levels introducing also a new formulation for net radiation from various MODIS products. We applied three methods to track the spatial and temporal characteristics of ET in the World Heritage UNESCO Doñana region: (i) a locally calibrated hydrological model (WATEN), (ii) the PT-JPL-thermal, and (iii) the global remote sensing ET product MOD16. The PT-JPL-thermal showed strong agreement with the WATEN ET in-situ calibrated estimates (ρ = 0.78, ρ1month-lag = 0.94) even though the MOD16 product did not (ρ = 0.48). The PT-JPL-thermal approach has proven to be a robust remote sensing model for detecting ET at a regional level in Mediterranean environments and it requires only air temperature and incoming solar radiation from climatic databases apart from freely available satellite products.

Partitioning global land evapotranspiration using CMIP5 models constrained by observations

The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface–atmosphere interactions. However, its magnitude remains highly uncertain at the global scale. Here we apply an emergent constraint approach that integrates CMIP5 Earth system models (ESMs) with 33 field T/ET measurements to re-estimate the global T/ET value. Our observational constraint strongly increases the original ESM estimates (0.41 ± 0.11) and greatly alleviates intermodel discrepancy, which leads to a new global T/ET estimate of 0.62 ± 0.06. For all the ESMs, the leaf area index is identified as the primary driver of spatial variations of T/ET, but to correct its bias generates a larger T/ET underestimation than the original ESM output. We present evidence that the ESM underestimation of T/ET is, instead, attributable to inaccurate representation of canopy light use, interception loss and root water uptake processes in the ESMs. These processes should be prioritized to reduce model uncertainties in the global hydrological cycle.

Attribution of Flux Partitioning Variations between Land Surface Models over the Continental U.S.

Accurate quantification of the terrestrial evapotranspiration ( E T ) components of plant transpiration (T), soil evaporation (E) and evaporation of the intercepted water (I) is necessary for improving our understanding of the links between the carbon and water cycles. Recent studies have noted that, among the modeled estimates, large disagreements exist in the relative contributions of T, E and I to the total E T . As these models are often used in data assimilation environments for incorporating and extending E T relevant remote sensing measurements, understanding the sources of inter-model differences in E T components is also necessary for improving the utilization of such remote sensing measurements. This study quantifies the contributions of two key factors explaining inter-model disagreements to the uncertainty in total E T : (1) contribution of the local partitioning and (2) regional distribution of E T . The analysis is conducted by using outputs from a suite of land surface models in the North American Land Data Assimilation System (NLDAS) configuration. For most of these models, transpiration is the dominant component of the E T partition. The results indicate that the uncertainty in local partitioning dominates the inter-model spread in modeled soil evaporation E. The inter-model differences in T are dominated by the uncertainty in the distribution of E T over the Eastern U.S. and the local partitioning uncertainty in the Western U.S. The results also indicate that uncertainty in the T estimates is the primary driver of total E T errors. Over the majority of the U.S., the contribution of the two factors of uncertainty to the overall uncertainty is non-trivial.

Spatiotemporal pattern of terrestrial evapotranspiration in China during the past thirty years

Evapotranspiration (ET) is one of the most important fluxes in terrestrial ecosystems that regulate atmosphere–hydrosphere–biosphere interactions. Several studies have suggested that global ET has significantly increased in the past several decades, and that such increase has exhibited big spatial variability, but there are few detailed studies on the spatio-temporal change in ET over China. Here, we developed a high-resolution data-oriented monthly ET product in China between 1982 and 2015 by integrating remote-sensing and the eddy covariance technique observed ET data in a machine learning approach (model tree ensemble, MTE). We showed that the mean annual ET over China is 552 ± 14 mm yr−1, which is comparable to the estimate from a MTE-derived product based on water balance, but is larger than that from both previous MTE-derived global product and process-based land surface models. ET in China significantly increased with a rate of 10.7 mm yr−1 per decade over the past 30 years (p < 0.05). The largest increases in ET (>60 mm yr−1 per decade) occurred in the eastern periphery of Sichuan, southern Taiwan, and central China, which was attributed to the increases in temperature and solar radiation, as well as the enhanced vegetation productivity. About 22% of the area showed a decreasing trend in ET, mainly in parts of southeastern, southwestern, and northeastern China. The regional decrease in ET was likely due to decreasing precipitation and/or vegetation browning. Although our finding of the significant increase in China’s ET at the country scale is supported by five different ET products, there are still less agreement on the change in ET at the regional scale among different ET products.

A water balance based, spatiotemporal evaluation of terrestrial evapotranspiration products across the contiguous United States.

Accurate gridded estimates of evapotranspiration (ET) are essential to the analysis of terrestrial water budgets. In this study, ET estimates from three gridded energy-balance based products (ETEB) with independent model formations and data forcings are evaluated for their ability to capture long term climatology and inter-annual variability in ET derived from a terrestrial water budget (ETWB) for 671 gaged basins across the CONUS. All three ETEB products have low spatial bias and accurately capture inter-annual variability of ETWB in the central US, where ETEB and ancillary estimates of change in total surface water storage (ΔTWS) from the GRACE satellite project appear to close terrestrial water budgets. In humid regions, ETEB products exhibit higher long-term bias, and the covariability of ETEB and ETWB decreases significantly. Several factors related to either failure of ETWB, such as errors in ΔTWS and precipitation, or failure of ETEB, such as treatment of snowfall and horizontal heat advection, explain some of these discrepancies. These results mirror and build on conclusions from other studies: on inter-annual timescales, ΔTWS and error in precipitation estimates are non-negligible uncertainties in ET estimates based on a terrestrial water budget, and this confounds their comparison to energy balance ET models. However, there is also evidence that in at least some regions, climate and landscape features may also influence the accuracy and long-term bias of ET estimates from energy balance models, and these potential errors should be considered when using these gridded products in hydrologic applications.