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| Titel |
Using similarity of soil texture and hydroclimate to enhance soil moisture estimation |
| VerfasserIn |
E. J. Coopersmith, B. S. Minsker, M. Sivapalan  |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 8 ; Nr. 18, no. 8 (2014-08-20), S.3095-3107 |
| Datensatznummer |
250120439
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| Publikation (Nr.) |
 copernicus.org/hess-18-3095-2014.pdf |
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| Zusammenfassung |
| 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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