A Bayesian hierarchical approach to multivariate nonstationary hydrologic and infrastructure frequency analysis
Abstract
Nonstationary analysis of hydrologic extremes is crucial for accurately estimating risk in a changing climate. Traditional hydrologic frequency analysis is conducted independently for each variable of interest, such as precipitation, streamflow, and reservoir level. However, these variables are closely related by physical processes animated by large scale climate drivers - El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO). Specifically, these climate connections modulate the seasonal precipitation extremes, driving the hydrologic extremes and consequently, the extremes in reservoir levels and the infrastructure risk. The climate drivers impact nonstationarity in the hydrologic extremes and also in the infrastructure risk. We present a Bayesian hierarchical framework for conducting nonstationary frequency analysis of multiple hydrologic variables. A Gaussian elliptical copula is used to model the joint distribution of all variables, while allowing the marginal distributions to remain as Generalized Extreme Value (GEV). We demonstrate the utility of this framework with a joint frequency analysis model of annual peak snow water equivalent (SWE), annual peak flow, and annual peak reservoir elevation at Taylor Park dam in Colorado, USA. Aforementioned indices of large scale climate drivers are used as covariates to model temporal nonstationarity. The Bayesian framework provides the posterior distribution of the model parameters and, consequently, the return levels. Results show that performing a joint frequency analysis reduces the uncertainty in the return level estimates and better captures the multivariate dependence, compared to an independent model.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMNH51B1941B
- Keywords:
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- 4303 Hydrological;
- NATURAL HAZARDSDE: 4313 Extreme events;
- NATURAL HAZARDSDE: 4321 Climate impact;
- NATURAL HAZARDSDE: 4333 Disaster risk analysis and assessment;
- NATURAL HAZARDS