Institute: California
Year Established: 2008 Start Date: 2008-03-01 End Date: 2009-02-28
Total Federal Funds: $17,216 Total Non-Federal Funds: $22,555
Principal Investigators: Brett Sanders
Project Summary: Flooding is the most damaging and fatal of all natural hazards and California is vulnerable on many fronts. Along the coast, low lying terrain is susceptible to inundation from tsunamis and may become increasingly vulnerable to storm surges, depending on future sea level rise. In the Central Valley and Delta, levee breaks pose a threat to hundreds of square miles of terrainlands that are transitioning from agricultural to high value residential and commercial land uses. And levees will be strained further according to Sierra Nevada climate change predictions, which call for an earlier snow melt in sync with Spring rain storms. Southern California is growing increasingly vulnerable to urban flooding. Agricultural and desert lands are being displaced by housing tracts and business parks which effectively cover the landscape with concrete and further burden flood control systems. A necessary element of flood mitigation efforts are flood simulations, and this project aims to advance flood simulation technology. Steady state flood simulations are the basis of FEMA Flood Inundation Rate Maps (FIRMs) used to control insurance pricing in flood prone areas, and dam safety programs create similar maps using unsteady simulations. For example, dam-break simulations show that the northern half of Orange County would be inundated as a consequence of Prado Dam failure (see Fig. 4 of project narrative). An emerging research topic is the use of flood inundation forecasting models to guide evacuation and first-response procedures. This project will focus on how to parameterize 2D high-resolution flood models using remotely sensed terrain and land-cover datasets. We seek a framework to account for urban developments in terms of floodplain storage, conveyance and drag parameters extracted from Digital Terrain Models (DTMs) based on Light Detection and Ranging (LiDAR) and/or Interferometric Synthetic Aperature Radar (IfSAR). Furthermore, we anticipate a scale dependency to these parameters that is driven by computational grid resolution. That is, structures or buildings may or may not be resolved by the computational grid depending on the resolution; and sub-grid scale structures are candidates for parameterization. The situation is not unlike Smagorinskys notion of an eddy viscosity adopted for Large Eddy Simulation (LES), where momentum dissipated by sub-grid scale eddies is budgeted by a parameter (the eddy viscosity) that scales an equivalent diffusive flux. Our research approach will involve a combination of theoretical analysis, benchmark testing, and field-scale simulations to develop and validate a framework for high-resolution flood inundation modeling. Theoretical work will involve a review of shallow-water theory, the basis of high-resolution flood models, and a validation of new mass and momentum conservation equations that explicitly account for obstructions. Benchmark testing will involve simulations of flow around obstructions with well known drag properties (e.g., a cylinder, block, and a cluster of blocks) for which laboratory data exist for comparison purposes. These simulations will be carried out using coarse grids that filter the obstruction, as well as fine grids that resolve the obstruction, to study scale dependencies and obtain prototype modeling guidelines for dealing with obstructions. In a third and final step, field-scale simulations will be carried out to test the prototype guidelines and identify areas where changes are needed. We are particularly interested in balancing accuracy requirements against computational efficiency. For example, flooded streets behave as rivers. But is it necessary to resolve the width of every street with a minimum number of cells? Or, can a block of streets be replaced with a cell that accounts for its overall storage and conveyance properties? The outcome of this study will be a theoretically sound basis to simulate the impact of buildings and other obstructions on flood dynamics, information that can be used for a range of flood inundation studies related to dam and levee failure, tsunami runup and extreme flooding along rivers. Practicing engineers who carry out flood studies can presently do little apart from increasing the Manning coefficient to account for obstructions. Better technology is needed. The results of this study will also provide added value to high resolution DTMs such as LiDAR which have been collected for many parts of California at public expense.