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Sensors 2010, 10(1), 913-932;

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

NOAA–Cooperative Remote Sensing Science & Technology Center, (NOAA-CREST), City University of New York, NY 10031, USA
Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO 80523, USA
National Renewable Energy Laboratory, Golden, CO 80401, USA
Author to whom correspondence should be addressed.
Received: 28 December 2009 / Revised: 11 January 2010 / Accepted: 19 January 2010 / Published: 25 January 2010
(This article belongs to the Section Remote Sensors)
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Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations. View Full-Text
Keywords: soil moisture; kriging; variogram; AGRMET; Oklahoma Mesonet soil moisture; kriging; variogram; AGRMET; Oklahoma Mesonet

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Lakhankar, T.; Jones, A.S.; Combs, C.L.; Sengupta, M.; Vonder Haar, T.H.; Khanbilvardi, R. Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method. Sensors 2010, 10, 913-932.

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