Identifying potentially neglected sources of uncertainty in flood frequency estimation using a multi-model framework
Abstract
Stochastic flood frequency (FF) estimation using hydrologic models is typically approached using Monte Carlo methods where the precipitation inputs, model parameters, and model initial conditions are varied for many simulations and return periods are then estimated empirically. However, the uncertainties in these FF estimates may be larger than currently appreciated because these approaches neglect components of the modeling chain such as model structure, or may not properly sample from the plausible model parameter values. We explore these key components of the modeling chain by expanding from a single to multi-model setup using the Framework for Understanding Structural Errors (FUSE) and varying model parameters using values consistent with historical meteorological uncertainty.
We do this through the use ofan ensemble precipitation and temperature dataset for the CONUS for developing an ensemble of internally consistent hydrologic model states and parameters for four FUSE model instances mimicking well-known hydrologic models such as PRMS, HEC-HMS, VIC, and SAC-SMA. We explore the differences in FF estimates for the different model structures given the exact same generation methodology, which is key to properly understanding model structural uncertainty. The use of internally consistent parameters (and their ranges), model states and meteorology is an improvement over the current more ad-hoc parameter and state perturbations. Additionally, we explore differences in FF estimates due to weather sequencing after the extreme precipitation input event (e.g. no precipitation following event vs continue with past weather traces). Finally, sensitivity analysis using the Distributed Evaluation of Local Sensitivity Analysis (DELSA) was performed for each model structure to better understand the relative impact of model parameters across multiple model structures on FF estimates.- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H41L2262S
- Keywords:
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- 1821 Floods;
- HYDROLOGYDE: 1869 Stochastic hydrology;
- HYDROLOGYDE: 4313 Extreme events;
- NATURAL HAZARDSDE: 4315 Monitoring;
- forecasting;
- prediction;
- NATURAL HAZARDS