Priestley-Taylor Jet Propulsion Laboratory Research Articles

Improved 30‐m Evapotranspiration Estimates Over 145 Eddy Covariance Sites in the Contiguous United States: The Role of ECOSTRESS, Harmonized Landsat Sentinel‐2 Imagery, Climate Reanalysis, and Deep Neural Network Postprocessing

AbstractThis study developed and evaluated 30‐m daily evapotranspiration (ET) estimates using the Priestley‐Taylor Jet Propulsion Laboratory (PT‐JPL) model with ECOSTRESS, Moderate MODIS, harmonized Landsat Sentinel‐2 (HLS) imagery, ERA5‐Land reanalysis, and eddy covariance measurements. The new daily 30‐m ET showed significantly improved performance (overall, r = 0.8, RMSE = 1.736, KGE = 0.466) at 145 EC sites over contiguous United States compared to the current 70‐m ECOSTRESS ET (overall, r = 0.485, RMSE = 4.696, KGE = −0.841). A deep neural network postprocessing model trained with ET measurements from EC sites further improved the performance on test sites that were not used for model training (overall, r = 0.842, RMSE = 0.88, KGE = 0.792). The 30‐m ET estimation biases were significantly related to the biases in the upwelling longwave (RUL) and downwelling shortwave radiation (RDS) inputs, with ET estimates driven by MODIS radiation showing higher biases compared to those driven by ERA5‐Land radiation. The error diagnosis using random forest indicates that ET biases tend to be larger under higher ET estimates, and RUL and RDS were the primary contributors to the high bias at the higher ET ranges, with partial dependence plots revealing that the estimation biases tend to be higher under more humid environment, denser vegetation covers, and high net radiation conditions. In conclusion, higher spatial resolution satellite imagery of vegetation characteristics and higher temporal resolution radiation data, combined with continent‐wide EC measurements and deep learning, provided substantial added value for improving ET estimations at the field scale (30‐m).

Response of blue-green water to climate and vegetation changes in the water source region of China's South-North water Diversion Project

The characteristics of water fluctuations within the basin have remained ambiguous in recent years due to climate and vegetation changes, posing a challenge to the planning and utilization of regional water resources. This study coupled the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, which can consider vegetation dynamics information and evapotranspiration physical mechanisms, into the Distributed Time Variant Gain Model (DTVGM) to improve the hydrological simulation accuracy under changing environments. Based on different simulation scenarios of the coupled model, the effects of climate and vegetation changes on hydrological processes were fully investigated using blue and green water (BW and GW) as assessment metrics. The upper Han River Basin (UHRB), as water source for the Central Line Project of China’s South-North Water Diversion (CSNWD), was selected as a typical basin for the study, results indicated that: (1) The DTVGM coupled with PT-JPL could better reflect the spatiotemporal patterns of major hydrological processes (runoff, evapotranspiration, and soil moisture) in UHRB from 2001 to 2019; (2) The BW in UHRB exhibited decreasing trend from 2001 to 2019, while the GW on the contrary. Surface runoff (Rs), vegetation transpiration (Et), and soil moisture (W) contributed most in the components of BW and GW; (3) Vegetation change dominated by greening in UHRB, which facilitated the transformation of BW to GW in the basin, and it increased the proportion of GW mainly by promoting Et. BW was mainly influenced by precipitation, but vegetation change altered the original correlation between climatic factors and hydrological processes. This study can support the management of water resources in the basin under changing environments.

Discriminating the impacts of vegetation greening and climate change on the changes in evapotranspiration and transpiration fraction over the Yellow River Basin

Evapotranspiration (ET) is a vital parameter in terrestrial water-energy cycles. The transpiration fraction (TF) is defined as the ratio of transpiration (T) to evapotranspiration (ET), representing the contribution rate of vegetation transpiration to ecosystem ET. Quantifying the relative contributions of vegetation and climate change on the ET and TF dynamic is of great significance to better understand the water budget between the land and atmosphere. Here, we chose Yellow River Basin (YRB) as the study area and analyzed the spatiotemporal changes of ET, T, and TF from 1982 to 2015 using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model. Meanwhile, the relative contributions of vegetation and climate change to ET, T and TF change were quantified. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During 1982–2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a over the YRB during 1982–2015, respectively. The regions with significant increases in ET, T and TF almost covered the whole study area except for the upper reaches of the YRB. Vegetation greening was the main factor for the increase of ET and TF in the YRB and enhanced ET and TF at a rate of 0.72 mm/a and 0.57/a, respectively, which mainly observed in the entire Loess Plateau region (over 50 % of the study area). Precipitation (PRE) was also the dominated factor contributing to the increase in ET and TF, and temperature (TEM) showed a positive correlation with the changes in ET and TF in the most areas of YRB, which jointly dominated ET changes in the upper reaches of the YRB and TF changes in the southern part of the basin. Except for the total effects, leaf area index (LAI) also indirectly promoted ET changes by affecting PRE, TEM and relative humidity (RH). While wind speed (WS) and radiation (RAD) had a relatively weak regulatory effect on the changes in ET and TF. These findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies for local government.

Comparison of remote sensing evapotranspiration models: Consistency, merits, and pitfalls

Various models are available for large-scale evapotranspiration (ET) estimation. The performance of these models generally differs due to their differences in forcing data, model structure (mathematical representations of the ET process), and parameter estimation. Model comparison is the most straightforward way to identify the strengths, weaknesses, and uncertainty sources of a model. In this study, three widely used remote sensing ET models were considered: the air-relative-humidity-based two-source (ARTS) model, Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model, and Penman-Monteith-Leuning (PML) model. The three models were evaluated based on measurements from 12 eddy-covariance (EC) towers and water-balance-based ET estimates from 286 basins. The evaluation results indicate that the PML model performs the best on both the site and basin scales. The advantage of the PML model may be due to (i) the land-cover-based parameter configuration and (ii) the consideration of differences in the responses of soil evaporation and transpiration to soil water deficit. We also investigated the consistencies and differences between the models in simulating the spatiotemporal variation and component partitioning of ET, that is, interception loss (Ei), soil evaporation (Es), and transpiration (Et). The three models show high consistency in estimating nationwide multi-year average ET (416.3–438.2 mm/yr) and its spatial pattern but large discrepancies in ET trends (0.10–0.98 mm/yr2) and component partitioning. The PT-JPL model considerably overestimates the ratio of Ei/ET, thereby underestimating the ratio of Es/ET because of the negative correlation between Ei and Es. The ARTS model presents better applicability in grasslands than in croplands or forestlands. This may be because its parameter value (constant for all biomes) and the water constraint scheme are more suitable for grasslands. Finally, we proposed specific modifications to address the potential issues of each model.

Assessing the synergistic modulation of evapotranspiration by global impervious surface and vegetation changes

The different characteristics of impervious urban surfaces and natural underlying surfaces affect water and heat balances, with consequent impacts on evapotranspiration (ET). The global impervious surface area in 1982 was only 34% of that in 2015, motivating an assessment of the net effect of impervious surface changes on ET under rapid impervious surface expansion. In this study, we incorporated the van Dijk model's interception evaporation (Ei) algorithm into the PT-JPL (Priestley-Taylor Jet Propulsion Laboratory) model, and added an impervious surface evaporation (Eu) module, to enable urban ecosystem simulations. This improved model (named the PT-JPLim model) was validated against annual mean ET calculated by P-Q in 8,205 catchments, and against ET measured at 203 flux towers in natural ecosystems and 11 flux towers in urban ecosystems. Calibration showed that the PT-JPLim model performed well (catchments: R = 0.36; natural ecosystems: R = 0.78, RMSE = 13.17 mm; urban ecosystems: R = 0.79, RMSE = 11.74 mm). Additionally, we examined the reliability of modelled ET and its partitioning, by comparison with observed soil evaporation (Eb), Ei, and satellite-based products. By controlling for the impervious surface fraction in the model, it was concluded that the net increase in Eu due to increased impervious surface changes was 0.23 mm/yr, with larger increases in eastern China, India, Europe and southeastern North America than in other regions. The effects of impervious surface and vegetation changes on ET were then analyzed for global impervious surface, with a ratio of 1/4.1 for the effects of impervious surfaces to vegetated surfaces on ET. The contributions of transpiration (Et), Eu, and Eb changes to ET changes on impervious surfaces were 65%, 27% and 8% respectively. These results indicate that synergistic modulation of ET by impervious surface changes and vegetation changes should not be ignored when studying urban eco-hydrological processes.

Temporal and Spatial Variation Characteristics of Actual Evapotranspiration in the Yiluo River Basin Based on the Priestley–Taylor Jet Propulsion Laboratory Model

Evapotranspiration is an important part of the hydrological cycle, affecting the terrestrial hydrological process and the relationship between water resource transformation. Analyzing and mastering the temporal and spatial variations in evapotranspiration are of great significance for the rational development, utilization, and protection of water resources in the basin. Based on MODIS remote sensing data and combined with meteorological and hydrological data, the PT-JPL model was used to estimate the actual evapotranspiration of the Yiluo River Basin, and the applicability of the PT-JPL model for estimating actual evapotranspiration in the basin was analyzed. The spatial and temporal characteristics of actual evapotranspiration in the Yiluo River Basin were analyzed, and the correlation between actual evapotranspiration in the basin and influencing factors such as precipitation, temperature, and vegetation was explored. The main conclusions are as follows: the PT-JPL model has good applicability in the Yiluo River Basin; the total actual evapotranspiration in the basin showed a decreasing trend, which was consistent with the trend of precipitation, indicating that the actual evapotranspiration may be limited by water conditions in the study area. The evapotranspiration of the basin was higher in the upstream and lower in the downstream, which may be related to the better vegetation coverage in the upper basin than in the downstream. As an important indicator of vegetation change, NDVI showed a good correlation with evapotranspiration, which also verified this. In addition, the correlation between evapotranspiration and temperature was also good.

Untangling the effects of climate change and land use/cover change on spatiotemporal variation of evapotranspiration over China

• ET showed a slight upward trend over China from 2005 to 2020. • The separate effect of climate change on ET was much more significant than LUCC. • ET was sensitive to Ta, Rn, and WS in humid and high-altitude basins, while sensitive to RH and Pr in relatively dry basins. • Wetlands and forestlands corresponded to higher ET values among all land cover types. Evapotranspiration (ET) is sensitive to environmental factors. Accurate assessment of ET and its response to changing environments have important scientific and practical significance. In the context of global climate change, China has experienced tremendous land use/land cover change (LUCC) processes, leaving its ET dynamics and influencing factors still to be determined. Here, the interannual variation and spatial distribution characteristics of ET over China from 2005 to 2020 were analyzed based on the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model. Then the separate contributions of climate change and LUCC to ET variation were quantified by controlling the LUCC scenario of the PT-JPL model. Results indicated that the PT-JPL model could accurately capture the variation of ET. The average annual ET over China from 2005 to 2020 was 464.52 mm, displaying a slightly increasing trend (0.46 mm·yr −1 ). The regions of ET increase were mainly concentrated in southern, central, and northeastern China. Separating the contributions of climate change and LUCC to ET revealed that climate change has a more significant effect on ET than LUCC. Among the five climatic factors, the contributions of relative humidity and precipitation to ET variation in dry basins were greater than those in humid or high-altitude basins, while temperature, net radiation, and wind speed showed an opposite performance. Net radiation and temperature were identified as the most critical factors affecting ET on the national scale. According to China's LUCC data from 2005 to 2020, the area conversion between forestlands, grasslands, and croplands was more significant than that between other land cover types. Wetlands and forestlands corresponded to higher ET values among all land cover types, and conversion to other land cover types would cause a decrease in ET. This study can support policymaking to improve water use efficiency and optimize water resource management.

Resolve the Clear‐Sky Continuous Diurnal Cycle of High‐Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature

AbstractAlthough numerous evapotranspiration (ET) estimates have been developed from remote sensing measurements, a diurnally resolved product with high spatial resolution (<100 m) is still lacking, which is critically needed for agricultural and ecological monitoring. The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) provides, for the first time, ET at 70 m resolution with diurnal samplings, enabling a step toward filling this data gap. This study developed the first framework to resolve the full diurnal cycle of ET and Land Surface Temperature (LST) from sporadic ECOSTRESS measurements. We first constructed 70 m diurnal LST utilizing a diurnal temperature cycle (DTC) model that fused ECOSTRESS and Geostationary Operational Environmental Satellite (GOES) LST. Next, we derived 70 m diurnal ET from the diurnally resolved LST, along with ancillary meteorological and reflectance data sets, using the Priestley‐Taylor Jet Propulsion Laboratory (PT‐JPL) algorithm. This framework was tested in two regions: A relatively homogeneous semiarid grassland landscape (centered at the US‐Seg Ameriflux site) and a heterogeneous humid cropland landscape (centered at US‐ARM). Our diurnally resolved LST and ET successfully reproduced the spatial patterns in the native ECOSTRESS measurements during overpasses for both landscapes (LST: r > 0.97, RMSE ∼2°C; ET: r > 0.99, and RMSE = 1–7 W m−2). The constructed time series also well captured the temporal variability of the in situ measurements (especially under clear‐sky conditions) at both US‐Seg and US‐ARM, albeit performance varying with availability and quality of ECOSTRESS samples. This study sets the stage for testing and applying our framework to broader climates, biomes, and landscapes toward eventually generating diurnally resolved 70 m global operational LST/ET products to enhance ecological/agricultural applications.

Vegetation restoration dominated the variation of water use efficiency in China

Implementation of numerous ecological restoration programs over the last two decades has significantly increased vegetation coverage in China. However, the response of the coupled carbon and water cycles to the large-scale vegetation restoration and the underlying mechanisms remain unclear. This study analyzed the spatiotemporal patterns of regional gross primary productivity (GPP), evapotranspiration (ET) and water use efficiency (WUE) in China using the two-leaf light use efficiency (TL-LUE) and the Priestley Taylor Jet Propulsion Laboratory (PT-JPL) models during the 2000–2017 period. The influencing mechanisms of anthropogenic re-vegetation and climatic factors on regional WUE were also analyzed. Results indicate that (1) both the GPP and WUE showed a significant increasing tendency with inter-annual change rates of 10.53 g C m−2 yr−1 and 0.01 g C kg−1 H2O yr−1, respectively; while the inter-annual change rate of annual ET was 1.43 kg H2O m−2 yr−1. (2) Spatially, the regional GPP dominated WUE variation of more than 79.51% of the total area. (3) Among the influencing factors, the greening of vegetation driven by human activities (LAIh) explained 35.27% of the WUE variation in China, much more than the climatic factors over during the study period. At the regional scale, human-driven vegetation greening also dominated the increasing WUE at regional scale. These findings provide important information to support large-scale ecological restoration policy/decision making to improve ecosystem services in China.

Improved global evapotranspiration estimates using proportionality hypothesis-based water balance constraints

Accurate estimation of global evapotranspiration (ET) is critical to understand the water and energy cycles in the Earth system. Satellite-driven ET algorithms serve as an effective way to estimate the global ET. However, many algorithms have been designed independently of water balance constraints, which potentially limit their ability to estimate ET in water-limited and high interception regions. As ET remains one of the most uncertain terms in the global water budgets, incorporating water balance constraints into algorithms should improve the performance of ET estimates. In this study, we developed a general solution (denoted PEW) based on the proportionality hypothesis to incorporate available water control into the widely used Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) ET algorithm. Simulated performances of the PEW model and PT-JPL algorithm were evaluated against 106 FLUXNET eddy covariance (EC) towers data at the site scale. Meanwhile, model results were compared at the global scale with the means of the widely used ET products. We found that the PEW model has smaller errors than the original PT-JPL algorithm, with the greatest improvements in water-limited regions and areas characterized by the high interception. Moreover, by incorporating the water balance constraints into the ET algorithm, the PEW model has the ability to distinguish variations in ET affected by El Nino-Southern Oscillation. In summary, our study offers a convincing evidence regarding the incorporation of water balance constraints into remote sensing algorithms for more accurately mapping global terrestrial ET with an enhanced understanding of ET variation under climate change. This model is the first of its kind among remote-sensing models to provide global land ET estimation with the proportionality hypothesis-based water balance constraints.

Different Vegetation Information Inputs Significantly Affect the Evapotranspiration Simulations of the PT-JPL Model

Evapotranspiration (ET) is an essential part of the global water cycle, and accurate quantification of ET is of great significance for hydrological research and practice. The Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model is a commonly used remotely sensed (RS) ET model. The original PT-JPL model includes multiple vegetation variables but only requires the Normalized Difference Vegetation Index (NDVI) as the vegetation input. Other vegetation inputs (e.g., Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR)) are estimated by the NDVI-based empirical methods. Here we investigate whether introducing more RS vegetation variables beyond NDVI can improve the PT-JPL model’s performance. We combine the vegetation variables derived from RS and empirical methods into four vegetation input schemes for the PT-JPL model. The model performance under four schemes is evaluated at the site scale with the eddy covariance (EC)-based ET measurements and at the basin scale with the water balance-based ET estimates. The results show that the vegetation variables derived by RS and empirical methods are quite different. The ecophysiological constraints of the PT-JPL model constructed by the former are more reasonable in spatial distribution than those constructed by the latter. However, as vegetation input of the PT-JPL model, the scheme derived from empirical methods performs best among the four schemes. In other words, introducing more remotely sensed vegetation variables beyond NDVI into the PT-JPL model degrades the model performance to varying degrees. One possible reason for this is the unrealistic ET partitioning. It is necessary to re-parameterize the biophysical constraints of the PT-JPL model to ensure that the model obtains reasonable internal process simulations, that is, “getting the right results for right reasons.”

Energy and evapotranspiration partitioning over a humid region orchard: Field measurements and partitioning model comparisons

Understanding energy and water flux cycling and quantifying their components are essential steps to elucidate the hydrological process and sustainable water resources management in agricultural ecosystems. The challenge of partitioning energy and evapotranspiration (ET) components (canopy transpiration Tc and surface evaporation Es) was addressed by the combination of eddy covariance (EC) technique, micro-lysimeters, and sap flow methods in a humid region kiwifruit orchard of Southwest China. The variations of energy and water flux and their controls were assessed, then the measured ET and its component were compared with the simulated values by Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), Shuttleworth-Wallace (S-W), and FAO-56 dual crop coefficient models (Dual-FAO). The results showed that latent heat flux (LE) dominated the consumption of net radiation energy (Rn), with the averaged ratio (EF = LE/Rn) above 0.70 during the growing seasons. More radiation energy is released in the form of LE with increased surface moisture and vegetation cover (total leaf area index, LAIt). Tc accounted for 41%–46% ET. The increase of canopy leaf area index (LAIc) strongly affected ET partitioning through the early growing seasons, while atmospheric evaporation demand dominated the Tc/ET and even caused the energy to be redistributed since high atmospheric evaporation demand caused a decrease of Tc while an increase of Es during the active growing seasons (LAIc > 2.5 m2 m−2). All the ET models performed well in estimating ET (R2 = 0.84–0.92) and its components (Tc, R2 = 0.70–0.74; Es, R2 = 0.63–0.69), allowing individual estimation of water interception by the canopy is one of the merits of the PT-JPL model for ET simulation in this humid site, with R2 of 0.92, RMSE of 0.55 mm d−1, while the S-W model performed slightly better in ET component simulations (Tc, R2 = 0.74, RMSE = 0.35 mm d−1; Es, R2 = 0.69, RMSE = 0.38 mm d−1). The results of our study may have much referential significance for eco-hydrological process analysis and water flux estimation in regions with similar environmental conditions.

Increased Interception Induced by Vegetation Restoration Counters Ecosystem Carbon and Water Exchange Efficiency in China

AbstractChanges in ecosystem water use efficiency (WUE) and evapotranspiration (ET) that are driven by vegetation change can be used as metrics to quantify ecosystem carbon and water exchange. The effect of vegetation on WUE has been explored in the past through consideration of total ET. However, interception (Ei) doesn't directly participate in ecosystem carbon and water exchange, and uncertainty of modeled Ei, resulting in great uncertainty of ET partitioning and ecosystem WUE. Here, we estimated Ei in China using Gerrits' model, replacing the algorithm for Ei in the Priestley‐Taylor Jet Propulsion Laboratory (PT‐JPL) model. The modified PT‐JPL model was then incorporated into the analytical WUE model to estimate WUE over China for 2003–2011, and the results were validated against literature data (WUELiterature). To evaluate the net effect of vegetation restoration on WUE, we simulated WUE in three ways: with vegetation change; without vegetation change; and with vegetation change, but without any Ei changes caused by vegetation changes. In the study presented here, we demonstrate the WUE simulated by the analytical WUE model is significantly correlated with the WUELiterature (R2 = 0.76, p‐value < 0.001), and leaf area index contributes the most to the spatial variability of Ei/ET, ranging from 10% to 55%. Increased Ei weakened the effect of vegetation change on WUE by ∼51.3% during vegetation restoration in China; a reduction that was particularly marked in southern China. These findings highlight the importance of considering Ei when assessing the effects of vegetation change on ecosystem carbon and water exchange, and provide insights that are important for the sustainable management of vegetation change in China.

Effects of clouds and aerosols on ecosystem exchange, water and light use efficiency in a humid region orchard

Investigating the patterns of water and carbon dynamics in agro-ecosystems in response to clouds and aerosols can shed new insights in understanding the biophysical impacts of climate change on crop productivity and water consumption. In this study, the effects of clouds and aerosols as well as other environmental factors on ecosystem water and carbon fluxes were examined based on three-year eddy covariance measurements under different sky conditions (quantified as the clearness index, Kt, i.e., the ratio of global solar radiation to extraterrestrial solar radiation) in a kiwifruit plantation in the humid Sichuan Basin of China. Results showed that evapotranspiration (ET) and canopy transpiration (Tc, measured by sap flow sensors) increased, while ecosystem light use efficiency (eLUE) and ecosystem water use efficiency (eWUE) decreased with increasing Kt. GPP presented a parabolic relationship with increasing Kt. The path analysis revealed that surface conductance (Gs) and canopy conductance (Gc) were the most dominant variables directly regulated carbon (GPP) and water (ET and Tc) fluxes. The effect path of Kt on ET and Tc was converted from through diffuse photosynthetic active radiation (PARdif) to direct PAR (PARdir) when the sky became clearer. The effect path of Kt on GPP was primarily through PARdif under different sky conditions. The declined eWUE with increasing Kt was caused by the different responses of GPP and ET to PARdir under clear skies. The declined eLUE resulted from the sharp decrease in GPP/PARdir, which surpassed the slight increase of GPP/PARdif with increasing PAR. The Priestley-Taylor Jet Propulsion Laboratory ET model (PT-JPL) incorporating Kt with an exponential function produced more reliable Tc estimates but minor improvement in ET. Further, the LUE-GPP model incorporating Kt with a linear function obtained much better GPP estimates. Our study shed light on how sky conditions modulate water and carbon dynamics between the biosphere and atmosphere, highlighting the necessity of the inclusion of sky conditions for better modeling regional water and carbon budgets.

Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions?

AbstractMany 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). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT‐JPL, and PM‐MOD and PM‐VI presenting overall better responses in terms of percent bias (%). As for PM‐VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land‐use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.

Estimation of Evapotranspiration and Its Components across China Based on a Modified Priestley–Taylor Algorithm Using Monthly Multi-Layer Soil Moisture Data

Although soil moisture (SM) is an important constraint factor of evapotranspiration (ET), the majority of the satellite-driven ET models do not include SM observations, especially the SM at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer SM data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM ET) algorithm by incorporating SM control into soil evaporation (Es) and canopy transpiration (T). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM ET model shows increased R2, NSE and reduced RMSE, Bias, with more improvements occurring in water-limited regions. SM incorporation into T enhanced ET estimates by increasing R2 and NSE by 4% and 18%, respectively, and RMSE and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two ET algorithms to the whole of China and found larger increases in T and Es in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual ET increased from the northwest to the southeast. The SM constraint resulted in higher transpiration estimate and lower evaporation estimate. Es was greatest in the northwest arid region, interception was a large fraction in some rainforests, and T was dominant in most other regions. Further improvements in the estimation of ET components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum.

Trade-off between carbon sequestration and water loss for vegetation greening in China

Land use management of forests and croplands mainly drives the vegetation greening in China. Vegetation greening strongly modulates the trade-off between carbon sequestration via photosynthesis and water loss from evapotranspiration (ET) at the terrestrial ecosystem (representing by ecosystem water use efficiency, WUE). The function of vegetation greening in terrestrial carbon sequestration is well known, but the impacts of water loss from ET caused by vegetation greening on WUE are often neglected. Here, the GIS-based Priestley-Taylor Jet Propulsion Laboratory model was established to evaluate ET in China from 2001 to 2015, incorporating vegetation dynamics as a key component. To quantify the net effect of the ET caused by vegetation greening on WUE, we compared two different simulation scenarios: actual vegetation greening scenario and simulated without vegetation greening scenario. The results show that forests and croplands mainly contribute to the growth in GPP and NPP in China with annual rates of 2.53 gC·m−2 yr−2 and 1.59 gC·m−2 yr−2 from 2001 to 2015, respectively. With the increase of terrestrial carbon sequestration, the ET under actual vegetation greening scenario was generated 6.78 mm·yr−1 more than that under simulated without vegetation greening scenario. But as a result of the negative impacts of vegetation physiological effect (elevated CO2 concentration and the decreased VPD) on ET, values of ET under two different scenarios all exhibited a decline trend from 2001 to 2015 with rates of − 2.04% and − 3.63%, respectively. Consequently, although the WUE under two different scenarios exhibited increased trends (6.44%, actual vegetation dynamics scenario; 10.74%, simulated without vegetation greening scenario), the ET caused by vegetation greening led to an obvious divergence between the WUE under two different scenarios. For better understanding the impacts of human activities on carbon and water cycles at the terrestrial ecosystem, it is necessary to take the water loss from ET caused by vegetation greening into consideration, which is crucial for enhancing the sustainability of future vegetation-related projects.

A global assessment of PT-JPL soil evaporation in agroecosystems with optical, thermal, and microwave satellite data

Evapotranspiration (ET) accounts for water movements from land to air and plays a vital role in the terrestrial water, energy, and carbon cycles. Reliable estimates of ET for agricultural landscapes can facilitate water resources management and food security analysis. The widely used Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model has the most potential to operationally simulate ET over large areas, but its inability to fully track soil evaporation dynamics using atmospheric humidity limits its application in agroecosystems. In this study, we isolated the uncertainties resulting from soil evaporation and assessed three Earth observation-based alternatives - apparent thermal inertia (ATI), microwave soil moisture (SM), and optical spectral indices based on shortwave infrared (SWIR) to formulate soil evaporation. Our results illustrate that the incorporation of the SWIR-based soil moisture divergence index (SMDI) and microwave-based SM into monthly soil evaporation led to 6% and 5% increase in explained ET variances and reduced RMSE by 23.2% and 13.1% for cropland and grassland, respectively, as compared to PT-JPL using atmospheric reanalysis data only. Further analyses demonstrated that PT-SMDI explained more observed ET variances than PT-JPL using in-situ measurements of atmospheric humidity during the crop growing season, particularly for irrigated cropland (R2=0.65 for PT-SMDI; R2=0.62 for PT-JPL). On the other hand, the use of microwave SM outperformed other indices for ET assessment in grasslands but had lower performance in croplands. Our results suggest that a combination of optical SWIR and microwave SM has good potential to improve the PT-JPL model accuracy for agricultural landscapes.

Modelling water utilization patterns in apple orchards with varying canopy sizes and different growth stages in semi-arid environments

Accurate estimates of orchard evapotranspiration (ET) and its components are important for precise irrigation scheduling, irrigation system designs, and optimal on-farm water allocation particularly in water-limited environments. Direct measurements of ET remain costly, laborious and sometimes difficult to apply over heterogeneous surfaces such as crop fields. Therefore, accurate crop water-use models are required for on-farm precise water resources management. In this study, we adopted and improved the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model developed by Fisher et al 2008 to estimate crop water use across different apple plants. Specifically, the model was developed to quantify the partitioning of apple orchard water use into beneficial (tree transpiration) and non-beneficial water use (orchard floor evaporation) as influenced by tree canopy cover. Data were collected in twelve orchards spread across key apple producing regions in the Western Cape Province of South Africa over three growing seasons (2014/15, 2015/16, 2016/17). Model ET estimates were tested against ET data measured; using the eddy covariance method and transpiration measured based on sap flow monitoring techniques. The results showed that the original Fisher PT-JPL model performed poorly in ET estimation across all the orchards under study. The model yielded lower R2, ranging from 0.02 to 0.64 and Nash-Sutcliffe Efficiency (NSE) from -10.93 to 0.20. Thus, we subsequently improved the model by incorporating soil moisture and vapour pressure deficit stress factors and by introducing a variable Priestley and Taylor coefficient (α). The modified PT-JPL model demonstrated an improvement in ET estimates. The root mean square of error (RMSE) of the estimated daily ET varied from ±0.60 mm/d to ±1.99 mm/d whereas the mean absolute error (MAE) varied from ±0.49 mm/d to ±1.91 mm/d, while the R2 varied from 0.54 to 0.75 in orchards with varying canopy cover. The findings of this work underscore the utility of the modified PT-JPL model for estimating ET and its components in apple orchards from planting until the trees reach full-bearing age.

A spatial-temporal continuous dataset of the transpiration to evapotranspiration ratio in China from 1981\u20132015

The ratio of plant transpiration to total terrestrial evapotranspiration (T/ET) captures the role of vegetation in surface-atmosphere interactions. However, several studies have documented a large variability in T/ET. In this paper, we present a new T/ET dataset (also including transpiration, evapotranspiration data) for China from 1981 to 2015 with spatial and temporal resolutions of 0.05° and 8 days, respectively. The T/ET dataset is based on a model-data fusion method that integrates the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with multivariate observational datasets (transpiration and evapotranspiration). The dataset is driven by satellite-based leaf area index (LAI) data from GLASS and GLOBMAP, and climate data from the Chinese Ecosystem Research Network (CERN). Observational annual T/ET were used to validate the model, with R2 and RMSE values were 0.73 and 0.07 (12.41%), respectively. The dataset provides significant insight into T/ET and its changes over the Chinese terrestrial ecosystem and will be beneficial for understanding the hydrological cycle and energy budgets between the land and the atmosphere.