Rainfall-driven Flooding Capability Development Report

Technical Report · Fri Mar 01 04:00:00 EST 2013

DOI:https://doi.org/10.2172/1086768· OSTI ID:1086768

Judi, David R. ^[1]; Tasseff, Byron A. ^[1]

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1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Globally, floods are among the most frequent and costly natural disasters, both socially and economically. Many of these floods result from excess rainfall collecting in streams and rivers, then overtopping banks and flowing overland into urban environments, damaging critical infrastructure. In Fiscal Year 2012, the National Infrastructure Simulation and Analysis Center’s (NISAC) goal was to enhance its existing flood modeling and simulation capability to be able to estimate flooding from rainfall-runoff events. To accomplish this task, NISAC modified the existing flood modeling code-base using commodity high-performance computing hardware, making it more suitable for regional rainfall events. NISAC also implemented new modules within the existing flood code to account for hydrologic processes, such as spatially variable rainfall and infiltration. Analysts subjected the new hydrologic model to a verification and validation process, wherein analysts evaluated the model using a bench-scale experiment and watershed scale rainfall-runoff events. The bench-scale experiment indicated that the new hydrologic model is mass and momentum conserving and can adequately simulate runoff for depths of inches of water. The watershed scale simulations indicated that the hydrologic model is a good predictor of the discharge hydrograph when compared to observations if the input parameters, such as roughness and hydraulic conductivity, are adequately calibrated. The intended use of the hydrologic model is to estimate flood potential during extreme rainfall events. The accuracy of the predictions is largely dependent on the availability of accurate spatial data for soil and roughness parameters. In addition, each simulation should be accompanied with a calibration exercise, which requires historical rainfall and river discharge observations.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: US Department of Homeland Security (DHS); USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC52-06NA25396
• OSTI ID: 1086768
• Report Number(s): LA-UR--13-24778
• Country of Publication: United States
• Language: English

Related Subjects

13 HYDRO ENERGY
42 ENGINEERING
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