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UC Davis shows eddy covariance network; OpenET comparisons vary and energy-balance issues remain
Summary
UC Davis researchers presented two to three years of eddy covariance and soil-moisture data across six Delta sites, showed where OpenET matched tower measurements and where it deviated (notably during senescence/post-harvest), and flagged energy-balance-closure and site-footprint issues requiring further QA and subgroup review.
UC Davis researchers reported progress from a six-site eddy covariance and soil-probe network meant to ground-truth OpenET and better quantify evapotranspiration (ET) across Delta island management types.
Kosina Suwatadev (UC Davis) described the sensor layout (six towers with eddy covariance, meteorological sensors, soil moisture profilers and pressure transducers), noted the project runs through the end of next year, and showed site-level results for cumulative water use across 2024 and 2025. She said eddy covariance often acts as the gold standard but acknowledged energy-balance-closure problems that require quality-assurance protocols, gap filling and inter-site comparisons. "We still don't know where the problem is," Suwatadev said of the energy-balance closure issue, and she invited a technical subgroup to examine siting, footprint filtering and processing choices.
Comparisons with OpenET ensemble outputs showed reasonable agreement in some seasons (green-canopy periods) and larger discrepancies during senescence and bare-soil periods. Suwatadev said some crops (e.g., safflower with deep roots) produce "unaccounted water" in shallow sensor boxes because root uptake extends below measured depths, and that smoke or advected carbon can complicate carbon-flux interpretation.
Why it matters: UC Davis' work provides the ground observations needed to validate remote-sensing ET products and to refine local water budgets. The team emphasized that these are preliminary, quality-checked results and that data processing choices matter for final estimates.
Next steps: UC Davis will continue data collection, improve QA, and meet with interested DMEC partners to resolve siting and energy-balance issues so that results can be used confidently for modeling and reporting.
