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Title: Upscaling of point soil moisture measurements to field averages at the OPE3 test site.

Author
item DE LANNOY, G - GHENT UNIVERSITY
item HOUSER, P - GEORGE MASON UNIVERSITY
item VERHOEST, N - GHENT UNIVERSITY
item PAUWELS, V - GHENT UNIVERSITY
item Gish, Timothy

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/13/2007
Publication Date: 7/15/2007
Citation: De Lannoy, G.J., Houser, P.R., Verhoest, N.E., Pauwels, V.R., Gish, T.J. 2007. Upscaling of point soil moisture measurements to field averages at the OPE3 test site. Journal of Hydrology. 343:1-11.

Interpretive Summary: To better understand how point soil moisture values relate to field-scale estimates of soil moisture a comprehensive evaluation of soil water dynamics was studied at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) research site in Beltsville. Spatially averaged soil moisture from 48 probes, distributed over 52 acres, represented field-scale soil moisture very well, and better than any individual probe. Additionally, soil moisture observations from the Soil Climate Analysis Network (SCAN) underestimated spatial soil moisture estimates at all depths. Although some soil moisture sensors represented field averages for a specific depth no probe location was representative of the entire field site. Also, terrain analysis of soil moisture showed no correlation with soil moisture suggesting a complex subsurface hydrology. The variability of individual sensors relative to field mean soil moisture estimates suggests that a full three dimensional hydrologic model would be more beneficial for estimating soil water dynamics than data assimilation. This research will help modelers more accurately simulate soil water dynamics at the field and watershed scales.

Technical Abstract: To better understand how point soil moisture values relate to field-scale estimates of soil moisture a comprehensive evaluation of soil water dynamics was studied at the Optimizing Production Inputs for Economic and Environmental Enhancement (OPE3) research site in Beltsville, Maryland. The ranking of the sensors based on the time-mean difference between the point values and the spatial mean was similar over different periods of time. However, the differences for the individual sensors showed a temporal variation that was strongly dependent on the period of time studied. Due to the complex hydrology of the field, it was impossible to determine terrain characteristics likely to yield representative soil moisture values. Average point measurement subsets were found to better represent the OPE3 field mean soil moisture profile than the individual layers. Point measurements from a nearby Soil Climate Analysis Network (SCAN) site showed similar temporal variability as the spatial OPE3 field means, but with an almost constant offset. Simple statistical methods, as well as models in both the time and frequency domain were explored to scale up point measurements to field average soil moisture. Cumulative distribution function (cdf) matching generally provided the best estimates.