HR: 1340h
AN: IN43B-1187    [Abstracts]
TI: HydroMet: Real-time Forecasting System for Hydrologic Hazards
AU: Band, L E
EM: lband@email.unc.edu
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: * Shin, D
EM: sdhyok@email.unc.edu
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: Hwang, T
EM: h7666@email.unc.edu
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: Goodall, J
EM: GOODALL@engr.sc.edu
AF: University of South Carolina, 300 Main Street, Columbia, SC 29208, United States
AU: Reed, M
EM: markreed@unc.edu
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: Rynge, M
EM: rynge@renci.org
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: Stillwell, L
EM: lisa@renci.org
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AU: Galluppi, K
EM: galluppi@unc.edu
AF: University of North Carolina, CB#3220, Chapel Hill, NC 27599, United States
AB: Recent devastating floods and severe droughts in North Carolina called attention to the need of a reliable nowcasting and forecasting system for these hydrologic hazards. In response to the demand, HydroMet project was launched by RENCI (Renaissance Computing Institute). On a supercomputer in the institute, we integrated (1) WRF (Weather Research and Forecasting) for the mesoscale numerical weather prediction, (2) RHESSys (Regional Hydro-Ecologic Simulation System) for the distributed modeling of runoff generation and soil moisture, and (3) LDAS (Land Data Assimilation Systems) for upgrading the prediction accuracy of soil moisture and energy. By exploiting the powerful parallel computing architecture, the forecasting system was designed to assimilate and produce massive spatio-temporal data in real-time while recalibrating itself automatically. We applied the system for western and central North Carolina as test sites, and forecasted the propagation of flood waves, and the long-term trends of low channel flow and soil moisture at a fine spatial resolution. As we extend the application of the system over the entire North Carolina, it is expected to provide timely and accurate information about floods and droughts in the area, which is prerequisite for more effective prevention and recovery from the hazards.
DE: 0525 Data management
DE: 1817 Extreme events
DE: 1819 Geographic Information Systems (GIS)
SC: Earth and Space Science Informatics [IN]
MN: 2007 Fall Meeting