A Novel Hydrologic Disaster Forecasting and Response (HDFR) System for Improving Transportation Management

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Tuesday, 4 February 2014: 1:45 PM
Room C210 (The Georgia World Congress Center )
Felipe Hernandez, University of Pittsburgh, Pittsburgh, PA; and L. Li, S. Lochan, X. Liang, Y. Liang, and W. Teng

It is fundamentally important for the Pennsylvania Department of Transportation (PennDOT) to provide timely and accurate forecasts at the road level for heavy snow, ice, rainfall events, and stream discharges for small and intermediate rivers. Such forecasts help PennDOT improve its emergency response decision-making, such as road/bridge closures and detours. To address the challenges faced by PennDOT, a Hydrologic Disaster Forecasting and Response (HDFR) system is being developed, which incorporates an innovative spatial data fusion and assimilation framework. The HDFR system, using data from NASA, NOAA, and other data sets, and those from two hydrological models, can provide effective hydrologic forecasts at the road level. In particular, the HDFR system will (1) allow the automated inflow of satellite data from NASA data centers and data sets from other heterogeneous sources, through its open data modeling environment and (2) effectively integrate and fuse the data to derive multi-scale information. The latter, together with forecasts from hydrological modeling at the road level, can provide critically needed information for PennDOT's emergency management. Initial development of the system and investigations of a case study will be presented and discussed.