Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Zeitschriften |
| DOI | 10.1002/2014WR015252 |
| Titel (primär) | Bayesian inversion of Mualem-van Genuchten parameters in a multilayer soil profile: a data-driven, assumption-free likelihood function |
| Autor | Over, M.W.; Wollschläger, U.; Osorio-Murillo, C.A.; Rubin, Y. |
| Quelle | Water Resources Research |
| Erscheinungsjahr | 2015 |
| Department | MET |
| Band/Volume | 51 |
| Heft | 2 |
| Seite von | 861 |
| Seite bis | 884 |
| Sprache | englisch |
| Keywords | Model Inversion; Vadose Zone; Likelihood Function; Validation |
| UFZ Querschnittsthemen | RU5; |
| Abstract | This paper introduces a hierarchical simulation and modeling framework that allows for inference and validation of the likelihood function in Bayesian inversion of vadose zone hydraulic properties. The likelihood function or its analogs (objective functions and likelihood measures) are commonly assumed to be multivariate Gaussian in form, however this assumption is not possible to verify without a hierarchical simulation and modeling framework. In this paper, we present the necessary statistical mechanisms for utilizing the hierarchical framework. We apply the hierarchical framework to the inversion of the vadose zone hydraulic properties within a multi-layer soil profile conditioned on moisture content observations collected in the uppermost four layers. The key result of our work is that the goodness-of-fit validated likelihood function form provides empirical justification for the assumption of multivariate Gaussian likelihood functions in past and future inversions at similar sites. As an alternative, the likelihood function needs not be assumed to follow a parametric statistical distribution and can be computed directly using non-parametric methods. The non-parametric methods are considerably more computationally demanding and to demonstrate this approach we present a smaller dimension synthetic case study of evaporation from a soil column. The main drawback of our work is the increased computational expense of the inversion. This article is protected by copyright. All rights reserved. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=15534 |
| Over, M.W., Wollschläger, U., Osorio-Murillo, C.A., Rubin, Y. (2015): Bayesian inversion of Mualem-van Genuchten parameters in a multilayer soil profile: a data-driven, assumption-free likelihood function Water Resour. Res. 51 (2), 861 - 884 10.1002/2014WR015252 |
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