Improving the Operational Simplified Surface Energy Balance Evapotranspiration Model Using the Forcing and Normalizing Operation

Gabriel B. Senay, Gabriel E.L. Parrish, Matthew Schauer, MacKenzie Friedrichs, Kul Khand, Olena Boiko, Stefanie Kagone, Ray Dittmeier, Saeed Arab, Lei Ji

Research output: Contribution to journalArticlepeer-review

Abstract

Actual evapotranspiration modeling is providing useful information for researchers and resource managers in agriculture and water resources around the world. The performance of models depends on the accuracy of forcing inputs and model parameters. We developed an improved approach to the parameterization of the Operational Simplified Surface Energy Balance (SSEBop) model using the Forcing and Normalizing Operation (FANO). SSEBop has two key model parameters that define the model boundary conditions. The FANO algorithm computes the wet-bulb boundary condition using a linear FANO Equation relating surface temperature, surface psychrometric constant, and the Normalized Difference Vegetation Index (NDVI). The FANO parameterization was implemented on two computing platforms using Landsat and gridded meteorological datasets: (1) Google Earth Engine (GEE) and (2) Earth Resources Observation and Science (EROS) Center Science Processing Architecture (ESPA). Evaluation was conducted by comparing modeled actual evapotranspiration (ETa) estimates with AmeriFlux eddy covariance (EC) and water balance ETa from level-8 Hydrologic Unit Code sub-basins in the conterminous United States. FANO brought substantial improvements in model accuracy and operational implementation. Compared to the earlier version (v0.1.7), SSEBop FANO (v0.2.6) reduced grassland bias from 47% to −2% while maintaining comparable bias for croplands (11% versus −7%) against EC data. A water balance-based ETa bias evaluation showed an overall improvement from 7% to −1%. Climatology versus annual gridded reference evapotranspiration (ETr) produced comparable ETa results, justifying the use of climatology ETr for the global SSEBop Landsat ETa that is accessible through the ESPA website. Besides improvements in model accuracy, SSEBop FANO increases the spatiotemporal coverage of ET modeling due to the elimination of high NDVI requirements for model parameterization. Because of the existence of potential biases from forcing inputs and model parameters, continued evaluation and bias corrections are necessary to improve the absolute magnitude of ETa for localized water budget applications.

Original languageEnglish (US)
Article number260
JournalRemote Sensing
Volume15
Issue number1
DOIs
StatePublished - Jan 2023

Bibliographical note

Funding Information:
This work was performed under the U.S. Geological Survey (USGS) contract 140G0119C0001 in support of the USGS Land Change Science projects such as WaterSMART and Landsat Water Balance.

Publisher Copyright:
© 2023 by the authors.

Keywords

  • ESPA
  • evapotranspiration
  • FANO Equation
  • flux tower
  • google earth engine
  • land surface temperature
  • Landsat
  • SSEBop
  • water balance

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