Embracing Uncertainty: Using Probabilistic Weather Forecasts to Make Ensemble Hydraulic Predictions at Remote Low-Water Crossings

Autor: Heidi R. Howard, Daniel R. Gambill, Francina Dominguez, S. Matus
Rok vydání: 2020
Předmět:
Zdroj: Journal of Hydrometeorology. 21:953-969
ISSN: 1525-7541
1525-755X
DOI: 10.1175/jhm-d-19-0238.1
Popis: Low-water crossings are structures designed to be overtopped during high river flows. These structures are usually constructed in remote locations, making timely emergency response difficult in case of flooding. In this work, five historical flooding events were hindcasted at a remote low-water crossing in central Texas. An ensemble of model-simulated precipitation forcing cascades uncertainty through hydrologic and hydraulic models. Each precipitation ensemble member corresponds to an independent model run, resulting in an ensemble 24-h streamflow forecast initialized at 0000 UTC. In addition to the hydrologic conditions, the forecast is expanded to predict river hydraulics, through flow velocity and depth. Analysis of the five hindcast events indicates that cascading probabilistic precipitation through hydrologic and hydraulic models adds robustness to river forecasts compared to deterministic methods. The approach provides a means to communicate the uncertainty of predictions through the ensemble spread. Analysis of deterministic hazard thresholds suggest that a hydraulic stability threshold, calculated as the multiplication of flow velocity and depth, is a useful alternative approach to NWS high-water categories for communicating hydrologic/hydraulic risk, as well as associated model uncertainty in the simplest manner possible.
Databáze: OpenAIRE
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