Morphodynamic analysis and statistical synthesis of geomorphic data
Abstract/Contents
- Abstract
- Many Earth-surface processes are studied using field, experimental, or numerical modeling data sets that, although realistic, only represent a small subset of possible outcomes observed in nature. Acquiring statistically significant quantities of data is often time- and/or cost intensive. Therefore it is not uncommon that a quantitative statement of statistical uncertainty is missing in predictions made from geomorphic data sets. To access such uncertainty for partially or unobserved states of the system, a stochastic model is needed that can mimic spatial as well as temporal variability. In this dissertation, we propose such a stochastic model. One component of the model explains long time-scale behavior using extreme value statistics that model large, but infrequent morphological changes; a second component describes short time-scale behavior by means of multiple-point geostatistics. We propose a Bayesian protocol to first falsify the stochastic model based on the limited time observations thereby improving physical plausibility. Then, we use approximate Bayesian computation to infer the stochastic model parameters from the limited (in time) geomorphic data. We apply our ideas to flume experiments of braided river channels evolving under steady water and sediment flux. Realizations of the stochastic model allow to obtain uncertainty estimates on the observed movement of channels in the flume and on the occurrence of extreme events unobserved in the actual experiment.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Mendes, Júlio Hoffimann |
|---|---|
| Degree supervisor | Caers, Jef |
| Thesis advisor | Caers, Jef |
| Thesis advisor | Mukerji, Tapan, 1965- |
| Thesis advisor | Scheidt, Celine |
| Degree committee member | Mukerji, Tapan, 1965- |
| Degree committee member | Scheidt, Celine |
| Associated with | Stanford University, Department of Energy Resources Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Júlio Hoffimann Mendes. |
|---|---|
| Note | Submitted to the Department of Energy Resources Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Julio Hoffimann Mendes
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
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