HR: 1340h
AN: B33D-1055    [Abstracts]
TI: On the Spatial and Temporal Sampling of Soil Moisture Fields.
AU: * Manfreda, S
EM: manfreda@princeton.edu
AF: Princeton University, Department of Civil and Environmental Engineering, E-quad., Princeton, NJ 08542 United States
AU: Rodriguez-Iturbe, I
EM: irodrigu@Princeton.EDU
AF: Princeton University, Department of Civil and Environmental Engineering, E-quad., Princeton, NJ 08542 United States
AB: Recent work by Isham et al. [2005 - P. Roy. Soc. A-Math. Phy.] and Rodrìguez-Iturbe et al. [2005 - Water Resour. Res.] has characterized the space-time variability of soil moisture through its analytically derived covariance function which depends on soil properties, vegetation structure and rainfall patterns typical of a region. This paper uses such characterization to address the strategies and methodologies for the sampling of soil moisture fields. The focus is on the estimation of the long-term mean soil moisture and the daily soil moisture averaged over a given area as a function of the network geometry, number of stations, number of sampling days and landscape heterogeneity. It is found that the spatial geometry of the network has a significant impact on the sampling of the average soil moisture over an area in any particular day, while it is much less relevant for the sampling of the long-term mean daily soil moisture. In the latter case, the length of the record is a commanding factor in what concerns the variance of estimation, specially for soils with shallow rooted vegetation. Spatial vegetation heterogeneity plays an important role on the variance of estimation of the soil moisture, being particularly critical for the sampling of the average soil moisture over an area for a given day.
DE: 1848 Monitoring networks
DE: 1854 Precipitation (3354)
DE: 1866 Soil moisture
DE: 1869 Stochastic hydrology
SC: Biogeosciences [B]
MN: Fall Meeting 2005