Seminar: Dr. Behzad Nazari, University of Texas, Arlington
high-resolution flash flood prediction for large urban areas
Location
Technology Research Center (TRC) : 206
Date & Time
April 13, 2018, 2:00 pm – 3:00 pm
Description
UMBC
Center for Urban Environmental Research and Education
Spring 2018 Seminar Series
presents
Dr. Behzad Nazari
Dept. of Civil Engineering
University of Texas at Arlington
"Toward real-time high-resolution flood forecasting for large urban areas: a case study in the Dallas-Fort Worth Metroplex”
Friday, April 13, 2018
2:00 PM
TRC 206, UMBC
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Parking policy
Parking passes for off-campus guests in the TRC lot are required at the cost of $4.00 per car. Parking passes may be picked up and paid for (cash only) before seminar by stopping by the CUERE office in TRC 102 /105 and seeing a staff member. Please contact us at 410-455-1763 with any questions regarding logistics.
View our web site at http://cuere.umbc.edu
2:00 PM
TRC 206, UMBC
This seminar series http://cuere.umbc.edu/seminar-series/ is free and open to the public.
**********************************************************************************
Parking policy
Parking passes for off-campus guests in the TRC lot are required at the cost of $4.00 per car. Parking passes may be picked up and paid for (cash only) before seminar by stopping by the CUERE office in TRC 102 /105 and seeing a staff member. Please contact us at 410-455-1763 with any questions regarding logistics.
View our web site at http://cuere.umbc.edu
Abstract
The ability to forecast flow, depth, and velocity in flooding events is one of the most important needs in highly populated urban areas. Urbanization and climate change highlight the necessity to understand and accurately predict water-related hazards in urban areas due to extreme precipitation. Towards that end, this study initially assesses the impact of changes in precipitation magnitude and imperviousness on urban inundation in a flooding prone urban catchment in the Dallas-Fort Worth Metroplex. Consequently, this study focuses on identifying potential alternatives to the conventional inundation models to improve operational viability of real-time flood forecasting in urban areas by downscaling coarse-resolution model output. Taking advantage of high-resolutions physiographic information, the problem is then transformed into developing efficient methods for routing flow in a network of 1D channels to represent sub-grid variability of hydraulic parameters within coarse 2D cells. Accordingly, two existing methods for such a routing problem are discussed, i.e., the diffusion wave routing and nonlinear routing with power-law storage functions. Each of the aforementioned methods is then solved innovatively to improve their efficiency for real-time routing of flow through many small streams quickly over a large area. The diffusion wave routing is solved using two continuous-time discrete-space methods to obtain explicit quasi-analytical solutions. On the other hand, the nonlinear routing problem with power-law storage function is solved by an implicit analytical solution. The proposed solutions offer new pathways for simple and efficient modeling of flood waves in real-world applications with minimal computational effort that makes them suitable candidates for flood forecasting in large urban areas.