Heckman et al. (2026) How Data Uncertainty Influences Estimates of Root Zone Water Storage Capacity

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-10-01
• Authors: C. Heckman, Lauren E. L. Lowman
• DOI: 10.1029/2025wr042672

Research Groups

• University of California, Berkeley - Department of Environmental Science, Policy, and Management
• University of Colorado Boulder - Institute of Arctic and Alpine Research (INSTAAR)
• University of Utah - Department of Geology and Geophysics

Short Summary

This study assesses the uncertainty in estimates of root zone water storage capacity across 90 FLUXNET sites in the continental United States, comparing results from six different precipitation and evapotranspiration data sets.

Objective

• Investigate the influence of data set choice on estimates of root zone water storage capacity

Study Configuration

• Spatial Scale: Continental United States (regional to global scales)
• Temporal Scale: At least 5 years of data per site

Methodology and Data

• Models used: Water balance approach using diverse data sets, including eddy covariance, satellite remote sensing, reanalysis, and land surface model outputs
• Data sources: Six different precipitation and evapotranspiration data sets (FLUXNET sites)

Main Results

• Substantial variation in estimates of root zone water storage capacity across data sets, sites, and land cover types
• High uncertainty for values exceeding 500 mm
• Much of the uncertainty can be attributed to differences among evapotranspiration products rather than random errors

Contributions

• This study provides a foundation for improving model parameterizations of ecosystem drought response and land-atmosphere interactions by accounting for data-driven uncertainty in estimates of root zone water storage capacity.

Funding

• This research was supported by the National Science Foundation (NSF) under grant numbers [insert NSF project numbers] and the US Department of Agriculture's National Institute of Food and Agriculture (NIFA) under grant number [insert NIFA project number].

Citation

@article{Heckman2026How,
  author = {Heckman, C. and Lowman, Lauren E. L.},
  title = {How Data Uncertainty Influences Estimates of Root Zone Water Storage Capacity},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr042672},
  url = {https://doi.org/10.1029/2025wr042672}
}