Preprints
https://doi.org/10.5194/hess-2020-602
https://doi.org/10.5194/hess-2020-602

  08 Dec 2020

08 Dec 2020

Review status: this preprint is currently under review for the journal HESS.

Technical note: Accounting for snow in the estimation of root-zone water storage capacity from precipitation and evapotranspiration fluxes

David N. Dralle1, W. Jesse Hahm2, K. Dana Chadwick3, Erica McCormick4, and Daniella M. Rempe4 David N. Dralle et al.
  • 1Pacific Southwest Research Station, United States Forest Service, Davis, CA, USA
  • 2Department of Geography, Simon Fraser University, Burnaby, BC, Canada
  • 3Department of Earth System Science, Stanford University, Stanford, CA, USA
  • 4Jackson School of Geosciences, University of Texas at Austin, Austin, TX, USA

Abstract. A common parameter in hydrological modeling frameworks is root-zone water storage capacity (SR[L]), which mediates plant-water availability during dry periods and the partitioning of rainfall between runoff and evapotranspiration. Recently, a simple flux-tracking based approach was introduced to estimate the value of SR (Wang-Erlandsson et al., 2016). Here, we build upon this original method, which we argue may overestimate SR in snow-dominated catchments due to snow melt and evaporation processes. We propose a simple extension to the method presented by Wang-Erlandsson et al. (2016), and show that the approach provides a more conservative minimum estimate of SR in snow-dominated watersheds. This SR dataset is available at 1 km resolution for the continental United States, along with the full analysis code, on Google Colaboratory and Earth Engine platforms. We highlight differences between the original and new methods across the rain-snow transition in the Southern Sierra Nevada, California, USA. As climate warms and precipitation increasingly arrives as rain instead of snow, the subsurface may be an increasingly important reservoir for storing plant-available water between wet and dry seasons; improved estimates of SR will therefore better clarify the future role of the subsurface as a storage reservoir that can sustain forests during seasonal dry periods and episodic drought.

David N. Dralle et al.

 
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David N. Dralle et al.

David N. Dralle et al.

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Short summary
Root zone water storage capacity determines how much water can be stored belowground to support plants during periods without precipitation. Here, we develop a satellite remote sensing method to estimate this key variable at large scales that matter for management. Importantly, our method builds on previous approaches by accounting for snowpack, which may bias estimates from existing approaches. Ultimately, our method will improve large-scale understanding of plant access to subsurface water.