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Title: SPATIAL AND TEMPORAL CHARACTERISTICS OF SOIL MOISTURE IN AN INTENSIVELY MONITORED AGRICULTURAL FIELD (OPE3)

Author
item DE LANNOY, G - LAB OF HYDROLOGY & WATER
item VERHOST, N - LAB OF HYDROLOGY & WATER
item HOUSER, P - GEORGE MASON UNIVERSITY
item Gish, Timothy
item VAN MEIRVENNE, M - DEPT. OF SOIL MANAGEMENT

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/21/2006
Publication Date: 12/6/2006
Citation: De Lanney, G.J.M., Verhost, N.E.C., Houser, P.R., Gish, T.J. Van Meirvenne, M. 2006. Spatial and temporal characteristics of soil moisture in an intensively monitored agricultural field (OPE3). Journal of Hydrology. 331:719-730.

Interpretive Summary: Plant growth and yield as well as the behavior of agricultural chemicals is strongly tied to soil moisture. Knowledge of how soil water changes in space and time is critical to understanding and modeling crop production and chemical behavior at the field scale. Over 10 million soil moisture observations during a 1-year period where evaluated on a 21 ha watershed at the USDA-ARS Beltsville Agricultural Research Center, Beltsville, Maryland so that guidelines can be developed for modeling soil water dynamics. Results indicate that the temporal and spatial patterns of surface and subsurface soil moisture are not related. Furthermore, although individual sensors were found to be representative of the field-average for that depth, no single location was found to exhibit soil moisture values that were representative of all depths. As a result, surface and subsurface soil water dynamics cannot be accurately modeled from observations from any single depth. This information can be used to help scientist understand where and when to monitor soil moisture so that field scale water dynamics can be effectively modeled.

Technical Abstract: A four-dimensional data set of soil moisture has been analyzed for spatial and temporal characteristics. Over 10 million soil moisture observations during a 1-year period where evaluated on a 21 ha watershed at the USDA-ARS Beltsville Agricultural Research Center, Beltsville, MD. Temporal variability in surface soil moisture was observed to decrease with time. In addition, as the average surface soil moisture increased, the corresponding standard deviation increased. However, the opposite was true for soil water contents below 80 cm. Although temporal autocorrelations increased with depth the cross correlation between sensors decreased with depth. The evolution of spatially averaged soil moisture and its standard deviation in the time domain again reveal different features for the upper layers relative to the deeper soil layers. Thus, individual sensors were found to be representative of the field-average for that depth, but depth no single location was found to be representative of average soil moisture values for all depths. As a result, surface and subsurface soil water dynamics cannot be accurately modeled from observations from any single depth. This information can be used to help scientist understand where and when to monitor soil moisture so that field scale water dynamics can be modeled effectively.