Multi-sensor data inputs rainfall estimation for flood simulation and forecasting

• Published in: CHUSER 2012 - 2012 IEEE Colloquium on Humanities, Science and Engineering Research
• Main Author: Wardah T.; Suzana R.; Huda S.Y.S.N.; Kamil A.A.
• Format: Conference paper
• Language: English
• Published: 2012
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877665713&doi=10.1109%2fCHUSER.2012.6504342&partnerID=40&md5=032d3f7719b92f8ec9e2bf36d2a020d3

The research project focused on new techniques in rainfall forecasting and flood monitoring, using multi-sensor data rainfall inputs from the Doppler weather radar, geostationary meteorological satellite and numerical weather prediction (NWP) models. Improved Z-R equations for radar rainfall have been derived for category monsoon and category rain-rate with bias ranging from 1.1 to 1.3. In addition, the rainfall forecasts produced from two NWP models namely the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) are statistically verified with the observed rain for case studies of Kelantan River basin and Klang River basin. The research also investigated the correlation between the images of visible and infrared geostationary meteorological satellite (metsat) to rainfall depth and developed a satellite-based rainfall estimation. Finally, a hydrodynamic model of case study river basin had been developed for an integrated hydro-meteorological flood monitoring system, using one of the multi sensor data rainfall inputs. © 2012 IEEE.