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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 18, issue 8 | Copyright
Hydrol. Earth Syst. Sci., 18, 3095-3107, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 20 Aug 2014

Research article | 20 Aug 2014

Using similarity of soil texture and hydroclimate to enhance soil moisture estimation

E. J. Coopersmith1, B. S. Minsker1, and M. Sivapalan1,2 E. J. Coopersmith et al.
  • 1Department of Civil & Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
  • 2Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA

Abstract. Estimating soil moisture typically involves calibrating models to sparse networks of in situ sensors, which introduces considerable error in locations where sensors are not available. We address this issue by calibrating parameters of a parsimonious soil moisture model, which requires only antecedent precipitation information, at gauged locations and then extrapolating these values to ungauged locations via a hydroclimatic classification system. Fifteen sites within the Soil Climate Analysis Network (SCAN) containing multiyear time series data for precipitation and soil moisture are used to calibrate the model. By calibrating at 1 of these 15 sites and validating at another, we observe that the best results are obtained where calibration and validation occur within the same hydroclimatic class. Additionally, soil texture data are tested for their importance in improving predictions between calibration and validation sites. Results have the largest errors when calibration–validation pairs differ hydroclimatically and edaphically, improve when one of these two characteristics are aligned, and are strongest when the calibration and validation sites are hydroclimatically and edaphically similar. These findings indicate considerable promise for improving soil moisture estimation in ungauged locations by considering these similarities.

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