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Title: Scaled Spatial Variability of Soil Moisture Fields

Authors
item Choi, M - UNIV. OF NEW HAMPSHIRE
item Jacobs, J - UNIV. OF NEW HAMPSHIRE
item Cosh, Michael

Submitted to: Geophysical Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 15, 2006
Publication Date: January 5, 2007
Citation: Choi, M., Jacobs, J.M., Cosh, M.H. 2007. Scaled spatial variability of soil moisture fields. Geophysical Research Letters. 34(L01401). http://dx.doi.org/10.1029/2006GL028247.

Interpretive Summary: Soil moisture patterns can be represented by simple distribution parameters for a variety of scales when considering 18 different field experiments. These patterns are well represented by negative exponential functions between the mean and the coefficient of variation of soil moisture. Rainfall and topography are the most important physical parameters to understand how surface soil moisture variability changes as soils dry. Soil parameters control the maximum relative variability. The soil moisture variability typically decreases as sampling scale increases, while the soil moisture variability increases as soil depth increases. These common soil moisture variability patterns can provide a feasible methodology to validate land surface models.

Technical Abstract: Soil moisture spatial variability patterns are identified using measurements across different scales and depths from 18 different experiments. The spatial variability patterns are well represented by negative exponential functions between the mean and the coefficient of variation of soil moisture. Rainfall and topography are the most important physical parameters to understand how surface soil moisture variability changes as soils dry. Soil parameters control the maximum relative variability. The soil moisture variability typically decreases as sampling scale increases, while the soil moisture variability increases as soil depth increases. These common soil moisture variability patterns can provide a feasible methodology to validate land surface models.

   
 
 
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