Norman Mueller

Norman Mueller

Lead end user

This project investigated the use of remote sensing data to improve modelled flood forecast skill and value. It developed optimal ways to constrain and update hydrologic flood models using remotely sensed soil moisture data. The project also proposed an algorithm for the monitoring of floods under vegetation, and investigated optimal ways to use remote sensing-derived inundation extent and level to implement and calibrate the hydraulic model. The results of this project enable improved predictions of flow depth, extent and velocity in the floodplain.
Research team:

Resources credited

Type Released Title Download Key Topics
Presentation-Slideshow 17 Oct 2019 Digital Earth Australia PDF icon Save (8.55 MB) flood, forecasting, remote sensing

Send a message to Norman Mueller (via CRC)

User Contact