Falsification and corroboration of conceptual hydrological models using geophysical data

Details

Serval ID
serval:BIB_290A87DAED2E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Falsification and corroboration of conceptual hydrological models using geophysical data
Journal
Wiley Interdisciplinary Reviews: Water
Author(s)
Linde N.
ISSN-L
2049-1948
Publication state
Published
Issued date
2014
Volume
1
Pages
151-171
Language
english
Abstract
Geophysical data may provide crucial information about hydrological properties, states, and processes that are difficult to obtain by other means. Large data sets can be acquired over widely different scales in a minimally invasive manner and at comparatively low costs, but their effective use in hydrology makes it necessary to understand the fidelity of geophysical models, the assumptions made in their construction, and the links between geophysical and hydrological properties. Geophysics has been applied for groundwater prospecting for almost a century, but it is only in the last 20 years that it is regularly used together with classical hydrological data to build predictive hydrological models. A largely unexplored venue for future work is to use geophysical data to falsify or rank competing conceptual hydrological models. A promising cornerstone for such a model selection strategy is the Bayes factor, but it can only be calculated reliably when considering the main sources of uncertainty throughout the hydrogeophysical parameter estimation process. Most classical geophysical imaging tools tend to favor models with smoothly varying property fields that are at odds with most conceptual hydrological models of interest. It is thus necessary to account for this bias or use alternative approaches in which proposed conceptual models are honored at all steps in the model building process.
Create date
13/07/2015 10:58
Last modification date
20/08/2019 13:08
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