How to better understand flooding: High-resolution modeling and data assimilation

Hurricane Harvey poured the unprecedented amount of rainfall and left significant damages in the Houston and adjoining coastal areas. However, the spatiotemporal evolution of the surface water inundation occurred in the Houston, the fourth-largest city in US, has yet to be fully understood primarily due to complexity and breadth of this flood. A retrospective inundation mapping using a high-resolution (10 m) urban flood model will show how this extreme rainfall was translated into flooding in the Houston metropolitan area and be verified with a variety of observations. In the latter half of the seminar, we will briefly explore recent advances in hydrologic data assimilation including Hydro-DART, ensemble WRF-Hydro within the data assimilation research testbed (DART), and the conditional bias-penalizing Kalman filter (CBPKF) which minimizes a weighted sum of error variance and expectation of Type-II CB.