Large-scale estimation of evapotranspiration (ET) remains challenging because no direct remote sensing estimates of ET exist and because most data-driven estimation approaches require assumptions about the impact of moisture conditions and biogeography on ET. The surface flux equilibrium (SFE) approach offers an alternative, deriving ET directly from atmospheric temperature and humidity under the assumption that conditions in the atmospheric boundary layer reflect ET's land boundary condition. We present a 4 km resolution, continental United States-wide, daily ET dataset spanning from 1979 to 2025 using the SFE method. The Bowen ratio is first calculated using the SFE method solely based on temperature and specific humidity estimates from gridMET and then converted to ET using net radiation and ground heat fluxes from ERA5-Land. We evaluate its performance using extended triple collocation to estimate the standard deviation of the random error and the correlation coefficient of SFE ET compared to true ET, as well as those of three widely used alternative ET datasets: GLEAM, FluxCom, and ERA5-Land. Despite its extreme simplicity, SFE ET achieves performance comparable to or exceeding the other datasets across large portions of CONUS, particularly in the Western U.S., while requiring no information about land surface, vegetation, or soil properties and no assumptions about ET's response to environmental and climate drivers. Our results support the use of SFE as a scalable, observation-driven method for estimating ET.
more »
« less
Surface Flux Equilibrium Theory‐Derived Evapotranspiration Estimate Outperforms ECOSTRESS, MODIS, and SSEBop Products
Abstract Evapotranspiration (ET) is a critical process influencing energy, water, and carbon cycles. Numerous methods have been developed to estimate ET accurately and robustly across diverse scales. Many of these methods are constrained by reliance on remote sensing data, which is prone to gaps, or by the need for model calibration and training. This study evaluates the performance of the calibration‐free surface flux equilibrium theory (SFET) for ET estimation at 33 Ameriflux sites in the continental USA. SFET‐derived ET estimates are intercompared with widely used continental remote sensing products, including ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station, Moderate Resolution Imaging Spectroradiometer, and SSEBop. Results indicate that SFET consistently outperforms these ET products. SFET's performance is found to be better under wet conditions and clear skies, with reduced accuracy under arid and high evaporative stress conditions. Overall, SFET exhibits significant potential for providing accurate, continuous, long‐term ET estimates, paving the way for operational application in uninstrumented regions over large scales.
more »
« less
- Award ID(s):
- 2317819
- PAR ID:
- 10627205
- Publisher / Repository:
- American Geophysical Union
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 52
- Issue:
- 10
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Root zone water storage capacity () sets the lower limit on the water available to plants and is critical for modeling terrestrial water and carbon fluxes. Due to subsurface heterogeneity in soils, roots, and geology, in‐situ measurements of are infeasible at regional to global scales. Instead, is often estimated using a water balance approach—calculating the difference between precipitation and evapotranspiration to approximate water deficits. This method can be applied using diverse data sets, including those from eddy covariance, satellite remote sensing, reanalysis, and land surface model outputs. However, each data product contains its own uncertainties, and the influence of data set choice on estimates has not been quantified. In this study, we assess the uncertainty in estimates across 90 FLUXNET sites in the continental United States with at least 5 years of data, comparing results from six different precipitation and evapotranspiration data sets. We find substantial variation in estimates across data sets, sites, and land cover types, with particularly high uncertainty for values exceeding 500 mm. Much of this uncertainty can be attributed to differences among evapotranspiration products rather than random errors. Our analysis shows that single data set approaches to quantifying underestimate the variability that emerges when multiple data sets are considered, especially in the Western US. These results underscore the need to account for data‐driven uncertainty when estimating subsurface water storage and provide a foundation for improving model parameterizations of ecosystem drought response and land‐atmosphere interactions.more » « less
-
ABSTRACT BackgroundRemote sensing (RS) technologies provide unprecedented opportunities to assess forest structure at broad spatial scales. Light detection and ranging (LiDAR) is a powerful tool that offers detailed vertical information, but its consistent high‐resolution coverage can be limited across vast areas and quantifying understory vegetation remains challenging due to occlusion. Conversely, while high‐resolution RGB imagery is more accessible and valuable for large‐scale analyses, it comes with higher uncertainty and only captures canopy‐level information. Integrating RGB data with ecological theory and existing LiDAR‐derived products (e.g., canopy height models, CHM) allows us to enhance predictions and broaden the applicability of forest size structure mapping from the understory to the canopy, particularly through tree size–abundance relationships. TheoryTree size and abundance generally follow known distributions, where smaller trees are exponentially more common than larger trees. This pattern emerges from fundamental ecological constraints, including volume packing, metabolic scaling and light competition, which collectively govern forest self‐organisation across spatial scales. Proposed ApproachWe present a workflow that integrates size‐abundance scaling theory with RGB data and CHMs to improve predictions of forest structure. By estimating tree size distributions from RGB imagery, we extend the applicability of ecological scaling models to broader spatial scales and offer an approach that complements traditional methods. AssessmentWe apply this approach to forest monitoring networks, including NEON and ForestGEO, to assess its accuracy and generalisability across a range of forests (e.g., subtropical pine, boreal, low and dry, tall and dense) in North America. Our results show that RGB‐based estimates can successfully recover size‐abundance distributions from the understory to the canopy. Future DirectionsFurther refinement of our approach could enhance predictions by incorporating species classifications from hyperspectral data and using more spatially or taxonomically specific allometric equations. These additions would enable more precise scaling of tree diameter from remote sensing data.more » « less
-
Abstract This paper reviews the current state of high‐resolution remotely sensed soil moisture (SM) and evapotranspiration (ET) products and modeling, and the coupling relationship between SM and ET. SM downscaling approaches for satellite passive microwave products leverage advances in artificial intelligence and high‐resolution remote sensing using visible, near‐infrared, thermal‐infrared, and synthetic aperture radar sensors. Remotely sensed ET continues to advance in spatiotemporal resolutions from MODIS to ECOSTRESS to Hydrosat and beyond. These advances enable a new understanding of bio‐geo‐physical controls and coupled feedback mechanisms between SM and ET reflecting the land cover and land use at field scale (3–30 m, daily). Still, the state‐of‐the‐science products have their challenges and limitations, which we detail across data, retrieval algorithms, and applications. We describe the roles of these data in advancing 10 application areas: drought assessment, food security, precision agriculture, soil salinization, wildfire modeling, dust monitoring, flood forecasting, urban water, energy, and ecosystem management, ecohydrology, and biodiversity conservation. We discuss that future scientific advancement should focus on developing open‐access, high‐resolution (3–30 m), sub‐daily SM and ET products, enabling the evaluation of hydrological processes at finer scales and revolutionizing the societal applications in data‐limited regions of the world, especially the Global South for socio‐economic development.more » « less
-
Abstract Global forests are increasingly lost to climate change, disturbance, and human management. Evaluating forests' capacities to regenerate and colonize new habitats has to start with the seed production of individual trees and how it depends on nutrient access. Studies on the linkage between reproduction and foliar nutrients are limited to a few locations and few species, due to the large investment needed for field measurements on both variables. We synthesized tree fecundity estimates from the Masting Inference and Forecasting (MASTIF) network with foliar nutrient concentrations from hyperspectral remote sensing at the National Ecological Observatory Network (NEON) across the contiguous United States. We evaluated the relationships between seed production and foliar nutrients for 56,544 tree‐years from 26 species at individual and community scales. We found a prevalent association between high foliar phosphorous (P) concentration and low individual seed production (ISP) across the continent. Within‐species coefficients to nitrogen (N), potassium (K), calcium (Ca), and magnesium (Mg) are related to species differences in nutrient demand, with distinct biogeographic patterns. Community seed production (CSP) decreased four orders of magnitude from the lowest to the highest foliar P. This first continental‐scale study sheds light on the relationship between seed production and foliar nutrients, highlighting the potential of using combined Light Detection And Ranging (LiDAR) and hyperspectral remote sensing to evaluate forest regeneration. The fact that both ISP and CSP decline in the presence of high foliar P levels has immediate application in improving forest demographic and regeneration models by providing more realistic nutrient effects at multiple scales.more » « less
An official website of the United States government

