An official website of the United States government
Abstract Satellite‐based evapotranspiration (ET) products such as OpenET and GLEAM are widely used for drought monitoring and ecosystem‐climate studies. However, their ability to accurately capture interannual variability (IAV), a key requirement for such applications, remains under‐evaluated. Here, we assessed IAV in OpenET and GLEAM using an independent water balance approach that combined precipitation, discharge, and GRACE/FO total water storage anomalies across nine river basins in the western United States. Even after accounting for observational uncertainty through a Monte Carlo approach, both products systematically underestimate IAV relative to water balance‐based ET, by more than 60% on average. This result is further supported by long‐term tower measurements from AmeriFlux. We also demonstrated that ET sensitivity to climate and vegetation drivers in OpenET and GLEAM differ substantially from water balance‐based estimates. These findings reveal important limitations in satellite‐based ET products and highlight the need for improved IAV representation to support ecosystem and climate applications.
more »
« less
This content will become publicly available on December 1, 2026
A novel approach to increase accuracy in remotely sensed evapotranspiration through basin water balance and flux tower constraints
Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address this issue, we propose a novel approach: the water balance equivalence (WABE) method, which generates spatially continuous WBET for correcting biases in RSET products. The WABE method computes synthetic WBET by integrating observed WBET and flux tower-derived FLUXCOM ET, which fills the spatial gaps of observed WBET and generates a spatially continuous WBET dataset. Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.
more »
« less
- Award ID(s):
- 2012893
- PAR ID:
- 10708783
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Journal of Hydrology
- Volume:
- 662
- Issue:
- PA
- ISSN:
- 0022-1694
- Page Range / eLocation ID:
- 133824
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
While extensive research has focused on evapotranspiration (ET) from land surface, the spatial distributions of ET of the woodland and forest understorey remain poorly understood. This study developed a method for estimating spatially distributed understorey ET by integrating the Maximum Entropy Production model with airborne thermal imagery. Validation against ground-truth estimation showed good model performance (R2 = 0.93, RMSE = 0.03 mm/h), confirming its efficacy across different land cover types, including open and understory areas. The results revealed significant spatial heterogeneity in understory ET with varying vegetation cover and topographic attributes, and distinct responses to wetting events. This method provides a new tool for estimating the important understory water consumption in forests and woodlands, contributing to assessing ecosystem water use efficiency and improving water resource and vegetation management strategies.more » « less
-
Abstract Large spatio‐temporal gradients in the Congo basin vegetation and rainfall are observed. However, its water‐balance (evapotranspiration minus precipitation, orET − P) is typically measured at basin‐scales, limited primarily by river‐discharge data, spatial resolution of terrestrial water storage measurements, and poorly constrainedET. We use observations of the isotopic composition of water vapor to quantify the spatio‐temporal variability of net surface water fluxes across the Congo Basin between 2003 and 2018. These data are calibrated at basin scale using satellite gravity and total Congo river discharge measurements and then used to estimate time‐varyingET − Pover four quadrants representing the Congo Basin, providing first estimates of this kind for the region. We find that the multi‐year record, seasonality, and interannual variability ofET − Pfrom both the isotopes and the gravity/river discharge based estimates are consistent. Additionally, we use precipitation and gravity‐based estimates with our water vapor isotope‐basedET − Pto calculate time and space averagedETand net river discharge within the Congo Basin. These quadrant‐scale moisture flux estimates indicate (a) substantial recycling of moisture in the Congo Basin (temporally and spatially averagedET/P > 70%), consistent with models and visible light‐basedETestimates, and (b) net river outflow is largest in the Western Congo where there are more rivers and higher flow rates. Our results confirm the importance ofETin modulating the Congo water cycle relative to other water sources.more » « less
-
Evapotranspiration (ET) connects the land to the atmosphere, linking water, energy, and carbon cycles. ET is an essential climate variable with a fundamental importance, and accurate assessments of the spatiotemporal trends and variability in ET are needed from regional to continental scales. This study compared eight global actual ET datasets (ETgl) and the average actual ET ensemble (ETens) based on remote sensing, climate reanalysis, land-surface, and biophysical models to ET computed from basin-scale water balance (ETwb) in South America on monthly time scale. The 50 small-to-large basins covered major rivers and different biomes and climate types. We also examined the magnitude, seasonality, and interannual variability of ET, comparing ETgl and ETens with ETwb. Global ET datasets were evaluated between 2003 and 2014 from the following datasets: Breathing Earth System Simulator (BESS), ECMWF Reanalysis 5 (ERA5), Global Land Data Assimilation System (GLDAS), Global Land Evaporation Amsterdam Model (GLEAM), MOD16, Penman–Monteith–Leuning (PML), Operational Simplified Surface Energy Balance (SSEBop) and Terra Climate. By using ETwb as a basis for comparison, correlation coefficients ranged from 0.45 (SSEBop) to 0.60 (ETens), and RMSE ranged from 35.6 (ETens) to 40.5 mm·month−1 (MOD16). Overall, ETgl estimates ranged from 0 to 150 mm·month−1 in most basins in South America, while ETwb estimates showed maximum rates up to 250 mm·month−1. ETgl varied by hydroclimatic regions: (i) basins located in humid climates with low seasonality in precipitation, including the Amazon, Uruguay, and South Atlantic basins, yielded weak correlation coefficients between monthly ETgl and ETwb, and (ii) tropical and semiarid basins (areas where precipitation demonstrates a strong seasonality, as in the São Francisco, Northeast Atlantic, Paraná/Paraguay, and Tocantins basins) yielded moderate-to-strong correlation coefficients. An assessment of the interannual variability demonstrated a disagreement between ETgl and ETwb in the humid tropics (in the Amazon), with ETgl showing a wide range of interannual variability. However, in tropical, subtropical, and semiarid climates, including the Tocantins, São Francisco, Paraná, Paraguay, Uruguay, and Atlantic basins (Northeast, East, and South), we found a stronger agreement between ETgl and ETwb for interannual variability. Assessing ET datasets enables the understanding of land–atmosphere exchanges in South America, to improvement of ET estimation and monitoring for water management.more » « less
-
NA (Ed.)Satellite-based evapotranspiration (ET) products inform decision-making regarding water availability and plant water use from sub-field to watershed scales. These products are validated using eddy covariance flux towers, where observations are subject to the influence of landscape heterogeneity due to a constantly shifting contributing area, or flux footprint, governed by surface and atmospheric drivers. In agricultural regions with multiple crop types, local heterogeneity may amplify the importance of appropriate grid cell selection for satellite ET comparisons. We evaluate the extent to which different satellite ET products capture both ET magnitudes and spatial variability due to landscape heterogeneity. We compare ECOSTRESS 70m instantaneous and daily ET products to flux tower observations in central Illinois with measurements at two heights, representing different but overlapping flux footprint areas. We estimate satellite ET based on a flux footprint weighting, gridded averages around the tower, and for crop-specific corn or soybean grid cells. In this region, the disALEXI daily ET product has better overall performance relative to the PT-JPL daily product, which is more sensitive to overpass times and tends to overestimate instantaneous ET. However, the PT-JPL model reflects more variability at high spatial resolution. Specifically, a footprint-derived ET improves the data-model comparison relative to disALEXI, and PT-JPL more closely replicates crop-specific and field-specific differences as inferred from the 2-height experimental setup. This study highlights differences in how models integrate spatial inputs, which lead to different representations of spatial variability for the same nominal resolution. This can also have important implications for understanding and predicting field-level differences in land-atmosphere fluxes.more » « less
