W. Sinowski et K. Auerswald, Using relief parameters in a discriminant analysis to stratify geological areas with different spatial variability of soil properties, GEODERMA, 89(1-2), 1999, pp. 113-128
The spatial variation of soil properties within landscapes is controlled by
the soil forming factors relief, parent material, climate, organisms, and
time. Although this relation is a paradigm in soil survey, it is rarely con
sidered in the analysis of spatial variability of soil properties. Homogene
ous soil units are mostly mapped according to the soil properties found clo
se to the soil surface. Nevertheless, a large heterogeneity may occur at gr
eater depths for soils developed in two different geological strata. This i
s often the case in former periglacial areas where pleistocene sediments co
ver older strata. The aim of this paper is to show how discriminant analysi
s can be used to objectively determine the soil depth at which geology chan
ges. This information may then help to develop better soil surveys and impr
ove the geostatistical regionalization of soil properties. The study area i
s a 1.5 km(2) soilscape 50 km north of Munich with large variability in rel
ief and parent material. At 450 nodes of a rectangular 50 x 50 m grid; fund
amental soil properties were measured for each soil horizon. Relief paramet
ers were calculated using a Digital Elevation Model (DEM) derived from more
than 4000 elevation measurements. Parent material of the soils may be sedi
ments of the tertiary period (TS) or quaternary sediments (QS). Altogether,
86 soil horizons were classified with confidence to TS and 496 to QS. They
were the training data set for a discriminant analysis to distinguish hori
zons of TS from horizons of QS. In addition to several relief parameters, t
he horizons' depth position within the soils was used as a discriminant var
iable. The discriminant functions classified 87% of TS and 85% of QS traini
ng data set horizons correctly by using elevation above sea level, depth, s
lope and upslope watershed area as independent variables. Solving the discr
iminant functions with respect to the boundary depth between QS and TS and
applying the result to the DEM yielded a map of boundary depth for each loc
ation of the study area. At 19 locations within the study area, the predict
ions were validated with an independent data set. The root of the mean squa
red differences between the measurement and the prediction was 7.5 cm for t
his second data set. This is within the uncertainty of measurement. Boundar
y depth was finally used to divide the study area into separate areas of th
e two strata dependent on the depth of interest within the soil. This allow
ed separate variogram calculations for each stratum and depth. The resultin
g variograms for soil texture showed a larger spatial variability for strat
um TS than for QS. Consequently, four times as many locations must be measu
red for stratum TS than for QS to obtain the same precision of spatial inte
rpolation. (C) 1999 Elsevier Science B.V. All rights reserved.