Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2861-2021
https://doi.org/10.5194/hess-25-2861-2021
Technical note
 | 
27 May 2021
Technical note |  | 27 May 2021

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

David N. Dralle, W. Jesse Hahm, K. Dana Chadwick, Erica McCormick, and Daniella M. Rempe

Related authors

Inclusion of bedrock vadose zone in dynamic global vegetation models is key for simulating vegetation structure and function
Dana A. Lapides, W. Jesse Hahm, Matthew Forrest, Daniella M. Rempe, Thomas Hickler, and David N. Dralle
Biogeosciences, 21, 1801–1826, https://doi.org/10.5194/bg-21-1801-2024,https://doi.org/10.5194/bg-21-1801-2024, 2024
Short summary
Event-scale power law recession analysis: quantifying methodological uncertainty
David N. Dralle, Nathaniel J. Karst, Kyriakos Charalampous, Andrew Veenstra, and Sally E. Thompson
Hydrol. Earth Syst. Sci., 21, 65–81, https://doi.org/10.5194/hess-21-65-2017,https://doi.org/10.5194/hess-21-65-2017, 2017
Short summary

Related subject area

Subject: Ecohydrology | Techniques and Approaches: Remote Sensing and GIS
Multi-decadal Floodplain Classification and Trend Analysis in the Upper Columbia River Valley, British Columbia
Italo Sampaio Rodrigues, Christopher Hopkinson, Laura Chasmer, Ryan MacDonald, Suzanne Bayley, and Brian Brisco
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-211,https://doi.org/10.5194/hess-2023-211, 2023
Revised manuscript accepted for HESS
Short summary
Estimating leaf moisture content at global scale from passive microwave satellite observations of vegetation optical depth
Matthias Forkel, Luisa Schmidt, Ruxandra-Maria Zotta, Wouter Dorigo, and Marta Yebra
Hydrol. Earth Syst. Sci., 27, 39–68, https://doi.org/10.5194/hess-27-39-2023,https://doi.org/10.5194/hess-27-39-2023, 2023
Short summary
Simulating carbon and water fluxes using a coupled process-based terrestrial biosphere model and joint assimilation of leaf area index and surface soil moisture
Sinan Li, Li Zhang, Jingfeng Xiao, Rui Ma, Xiangjun Tian, and Min Yan
Hydrol. Earth Syst. Sci., 26, 6311–6337, https://doi.org/10.5194/hess-26-6311-2022,https://doi.org/10.5194/hess-26-6311-2022, 2022
Short summary
Untangling irrigation effects on maize water and heat stress alleviation using satellite data
Peng Zhu and Jennifer Burney
Hydrol. Earth Syst. Sci., 26, 827–840, https://doi.org/10.5194/hess-26-827-2022,https://doi.org/10.5194/hess-26-827-2022, 2022
Short summary
Information-based uncertainty decomposition in dual-channel microwave remote sensing of soil moisture
Bonan Li and Stephen P. Good
Hydrol. Earth Syst. Sci., 25, 5029–5045, https://doi.org/10.5194/hess-25-5029-2021,https://doi.org/10.5194/hess-25-5029-2021, 2021
Short summary

Cited articles

Arkley, R. J.: Soil moisture use by mixed conifer forest in a summer-dry climate, Soil Sci. Soc. Am. J., 45, 423–427, 1981. a
Botter, G., Porporato, A., Rodriguez-Iturbe, I., and Rinaldo, A.: Basin-scale soil moisture dynamics and the probabilistic characterization of carrier hydrologic flows: Slow, leaching-prone components of the hydrologic response, Water Resour. Res., 43, W02417, https://doi.org/10.1029/2006WR005043, 2007. a
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., and Pasteris, P. P.: Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States, Int. J. Climatol., 28, 2031–2064, 2008. a
Daly, C., Smith, J. I., and Olson, K. V.: Mapping atmospheric moisture climatologies across the conterminous United States, PloS One, 10, e0141140, https://doi.org/10.1371/journal.pone.0141140, 2015. a
Dawson, T. E., Hahm, W. J., and Crutchfield-Peters, K.: Digging deeper: what the critical zone perspective adds to the study of plant ecophysiology, New Phytol., 226, 666–671, https://doi.org/10.1111/nph.16410, 2020. a
Download
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.