In many instances hydrogeological parameters obtained by conventional methods for selected localities within an aquifer or an aquitard are not sufficient for adequate regionalization at the scale of the entire layer. Here, we demonstrate an application of the fuzzy kriging method in regionalization of hydrogeological data, in which the set of conventional, crisp values is supplemented by imprecise information subjectively estimated by an expert. It is believed that such an approach eventually may reflect the real-world conditions more closely than a traditional crisp-value approach, because the former does not impose exactness artificially on phenomena which are diffuse by their nature. Spatial interpolation was done for the thickness of one of the major aquitards (till and glaciolacustrine clay) in northwestern Germany. The dataset consists of 329 crisp values from boreholes supplemented by 172 imprecise values defined as fuzzy numbers. It is demonstrated that the reliability of regionalization was higher, compared to regionalization performed with the crisp dataset only. Fuzzy kriging was performed with FUZZEKS (Fuzzy Evaluation and Kriging System) developed at the Ecosystem Research Center at the University of Kiel.
[1]
P. Diamond.
Fuzzy kriging
,
1989
.
[2]
A. Bárdossy,et al.
Geostatistics utilizing imprecise (fuzzy) information
,
1989
.
[3]
J. Piotrowski.
Tunnel-valley formation in northwest Germany—geology, mechanisms of formation and subglacial bed conditions for the Bornhöved tunnel valley
,
1994
.
[4]
A. Bárdossy.
Notes on the robustness of the kriging system
,
1988
.
[5]
J. Klostermann,et al.
Glaciations in north west Germany
,
1986
.
[6]
Marek Kacewicz.
“Fuzzy” Geostatistics - An Integration of Qualitative Description into Spatial Analysis
,
1994
.
[7]
A. Bárdossy,et al.
Kriging with imprecise (fuzzy) variograms. I: Theory
,
1990
.
[8]
Peter A. Burrough,et al.
Fuzzy mathematical methods for soil survey and land evaluation
,
1989
.
[9]
Lotfi A. Zadeh,et al.
Fuzzy Sets
,
1996,
Inf. Control..