Spatial and temporal variability of the unsaturated zone characterised by geophysical and conventional methods H.K. French, Centre for Soil and Environmental Research (Jordforsk) Norway A. Binley, Department of Environmental Science, Lancaster University, UK, N.-O. Kitterød Department of Geophysics, University of Oslo

The Moreppen research station Oslo Airport Gardermoen 4 km 2 km

Simulations of flow and transport based on random fields of the permeability

p47 p45 p43 p41 GPR profiles p41 p43 p45 p47 Moreppen N 10 m Ground Penetrating Radar

depth (m) depth (m) top1 top2 dip1 dip2 dry saturated ~ 0.5 sat. depth (m) c11c16

How do we characterise the spatial variability? Soil Physical data Geophysical data Geophysical images Range Semivariance Time Which data do we use? Time

Sampling points, soil physical data, vertical section SEL2 SEL3 0 m 0.5 m 1.0 m 1.5 m 2.0 m

Semivariogram analysis

From soil physical data to inverted geophysical data Semivariogram Angle: 0, Tolerance: 7 SEL2 SEL3 0 m 0.5 m 1.0 m 1.5 m 2.0 m

Variogram analysis of resistivity data in a horizontal plane 0.2 m depth

Variogram Model for horizontal data Gaussian model Nugget: 3.25 Range: 1.27 Sill: 7.78

Time changes in spatial structure

Semivariograms of resistivity and changes in resistivity show different behaviour Inverted resistivities (at 0.32 m)Ratioed inverted resistivities (at 0.32 m)

Conclusions  All methods give similar size of the range  The semivariance may vary considerably with time, especially during snowmelt, but the range seems to remain fairly constant  Geophysical methods may serve as a supplementary method for characterisation of spatial correlation structure  Electrical methods offer great potential for characterising the dynamics of spatially variable processes