Abstract
River discharges are traditionally modeled by employing a standard power-law methodology. Recently, the Bayesian approached has successfully been applied to improve the estimates of the standard power-law. In this article, an extension to the standard power-law based on Bayesian B-splines is developed and tested on data sets from 61 different rivers. The extended model is evaluated against the standard power-law using two measures, the Deviance Information Criterion and Bayes factor. The extended model captures deviations in the data from the standard power-law but reduces to the standard power-law when that model is adequate. The standard power-law is inadequate for 26% of the rivers while the extended model provides an adequate fit in all of those cases and for the remaining 74% of the rivers the extended model and the power-law model both give adequate fit with almost identical estimates.
| Original language | English |
|---|---|
| Pages (from-to) | 1-20 |
| Number of pages | 20 |
| Journal | Stochastic Environmental Research and Risk Assessment |
| Volume | 26 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2012 |
Bibliographical note
Funding Information: The work presented here is based on Kristinn M. Ingimarsson’s Master’s thesis at the School of Engineering and Natural Sciences at the University of Iceland. The thesis was written under the direction of Associate Research Professor of Statistics Birgir Hrafnkelsson at the Science Institute and Professor of Environmental Engineering Sigurdur M. Gardarsson at Faculty of Civil and Environmental Engineering both at the University of Iceland and in cooperation with Arni Snorrason, Chief of the Icelandic Meteorological Office. This work was funded by the Icelandic Centre for Research (RANNIS-070241021) and has no conflict of interests. We thank the Icelandic Centre for Research for its support.Other keywords
- B-spline smoothing functions
- Bayesian inference
- Discharge rating curves
- Hydrology
- Standard power-law