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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 20, issue 4 | Copyright
Hydrol. Earth Syst. Sci., 20, 1459-1481, 2016
https://doi.org/10.5194/hess-20-1459-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Apr 2016

Research article | 19 Apr 2016

Global root zone storage capacity from satellite-based evaporation

Lan Wang-Erlandsson1,2, Wim G. M. Bastiaanssen2,3, Hongkai Gao2,4, Jonas Jägermeyr5, Gabriel B. Senay6, Albert I. J. M. van Dijk7,8, Juan P. Guerschman8, Patrick W. Keys1,9, Line J. Gordon1, and Hubert H. G. Savenije2 Lan Wang-Erlandsson et al.
  • 1Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden
  • 2Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands
  • 3UNESCO-IHE Institute for Water Education, Delft, the Netherlands
  • 4Global Institute of Sustainability, Arizona State University, Tempe, AZ 85287, USA
  • 5Research Domain Earth System Analysis, Potsdam Institute for Climate Impact Research, Potsdam, Germany
  • 6US Geological Survey, Earth Resources Observation and Science Centre, North Central Climate Science Centre, Fort Collins, CO, USA
  • 7Fenner School of Environment and Society, The Australian National University, Canberra, Australia
  • 8CSIRO Land and Water, Canberra, Australia
  • 9Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA

Abstract. This study presents an "Earth observation-based" method for estimating root zone storage capacity – a critical, yet uncertain parameter in hydrological and land surface modelling. By assuming that vegetation optimises its root zone storage capacity to bridge critical dry periods, we were able to use state-of-the-art satellite-based evaporation data computed with independent energy balance equations to derive gridded root zone storage capacity at global scale. This approach does not require soil or vegetation information, is model independent, and is in principle scale independent. In contrast to a traditional look-up table approach, our method captures the variability in root zone storage capacity within land cover types, including in rainforests where direct measurements of root depths otherwise are scarce. Implementing the estimated root zone storage capacity in the global hydrological model STEAM (Simple Terrestrial Evaporation to Atmosphere Model) improved evaporation simulation overall, and in particular during the least evaporating months in sub-humid to humid regions with moderate to high seasonality. Our results suggest that several forest types are able to create a large storage to buffer for severe droughts (with a very long return period), in contrast to, for example, savannahs and woody savannahs (medium length return period), as well as grasslands, shrublands, and croplands (very short return period). The presented method to estimate root zone storage capacity eliminates the need for poor resolution soil and rooting depth data that form a limitation for achieving progress in the global land surface modelling community.

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We present an "Earth observation-based" method for estimating root zone storage capacity – a critical parameter in land surface modelling that represents the maximum amount of soil moisture available for vegetation. Variability within a land cover type is captured, and a global model evaporation simulation is overall improved, particularly in sub-humid to humid regions with seasonality. This new method can eliminate the need for unreliable soil and root depth data in land surface modelling.
We present an "Earth observation-based" method for estimating root zone storage capacity – a...
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