A Class-Kriging Predictor for Functional Compositions with Application to Particle-Size Curves in Heterogeneous Aquifers
| Autor: | Piercesare Secchi, Alberto Guadagnini, Alessandra Menafoglio |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
geography
Hydrogeology geography.geographical_feature_category 0208 environmental biotechnology Aquifer 02 engineering and technology Geostatistics 15. Life on land 01 natural sciences Field (geography) Hierarchical database model Geostatistics · Functional compositions · Clustering · Particle-size curves · Groundwater · Hydrogeology Physics::Geophysics 020801 environmental engineering 010104 statistics & probability Bayes' theorem Mathematics (miscellaneous) Kriging General Earth and Planetary Sciences 0101 mathematics Biological system Cluster analysis Geomorphology Geology |
| Zdroj: | Mathematical Geosciences |
| ISSN: | 1874-8961 |
| DOI: | 10.1007/s11004-015-9625-7 |
| Popis: | This work addresses the problem of characterizing the spatial field of soil particle-size distributions within a heterogeneous aquifer system. The medium is conceptualized as a composite system, characterized by spatially varying soil textural properties associated with diverse geomaterials. The heterogeneity of the system is modeled through an original hierarchical model for particle-size distributions that are here interpreted as points in the Bayes space of functional compositions. This theoretical framework allows performing spatial prediction of functional compositions through a functional compositional Class-Kriging predictor. To tackle the problem of lack of information arising when the spatial arrangement of soil types is unobserved, a novel clustering method is proposed, allowing to infer a grouping structure from sampled particle-size distributions. The proposed methodology enables one to project the complete information content embedded in the set of heterogeneous particle-size distributions to unsampled locations in the system. These developments are tested on a field application relying on a set of particle-size data observed within an alluvial aquifer in the Neckar river valley, in Germany. |
| Databáze: | OpenAIRE |
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