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Assessing local and spatial uncertainty with nonparametric geostatistics

Thiesen, Stephanie 1; Ehret, Uwe 1
1 Institut für Wasser und Gewässerentwicklung (IWG), Karlsruher Institut für Technologie (KIT)

Abstract:

Uncertainty quantification is an important topic for many environmental studies, such as identifying zones where potentially toxic materials exist in the soil. In this work, the nonparametric geostatistical framework of histogram via entropy reduction (HER) is adapted to address local and spatial uncertainty in the context of risk of soil contamination. HER works with empirical probability distributions, coupling information theory and probability aggregation methods to estimate conditional distributions, which gives it the flexibility to be tailored for different data and application purposes. To explore how HER can be used for estimating threshold-exceeding probabilities, it is applied to map the risk of soil contamination by lead in the well-known dataset of the region of Swiss Jura. Its results are compared to indicator kriging (IK) and to an ordinary kriging (OK) model available in the literature. For the analyzed dataset, IK and HER predictions achieve the best performance and exhibit comparable accuracy and precision. Compared to IK, advantages of HER for uncertainty estimation in a fine resolution are that it does not require modeling of multiple indicator variograms, correcting order-relation violations, or defining interpolation/extrapolation of distributions. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000136857
Veröffentlicht am 27.08.2021
Originalveröffentlichung
DOI: 10.1007/s00477-021-02038-5
Scopus
Zitationen: 5
Web of Science
Zitationen: 5
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wasser und Gewässerentwicklung (IWG)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 01.2022
Sprache Englisch
Identifikator ISSN: 1436-3240, 1436-3259
KITopen-ID: 1000136857
Erschienen in Stochastic environmental research and risk assessment
Verlag Springer-Verlag
Band 36
Seiten 173–199
Vorab online veröffentlicht am 15.07.2021
Nachgewiesen in Scopus
Web of Science
Dimensions
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