Understanding and Mitigating Hazards


Floods in Queensland
Floods in Queensland

Project Status:

The objective of the project is to demonstrate the utility of coupled hydrologic/hydraulic model forecasting and data assimilation using remotely sensed data for potential operational use.

Flood forecasting systems aim at predicting the arrival time, water depth and velocity of the flood wave in each point downstream. They are an essential tool in emergency management, supporting local response actions and communication of warnings to the public.

Significant progress has been made internationally in the development of flood models, but they are still prone to a significant error, due to errors and uncertainties in the rainfall data and the model structure and parameters.

Remote sensing can be a helpful tool for operational water management, and particularly for flood forecasting. In this project remote sensing data is being used in two ways:

  1. Estimated soil moisture profiles from hydrologic models will be improved through the merging of these model predictions with remotely sensed surface soil moisture values. This is expected to have a beneficial impact on modelled hydrographs.
  2. Estimated flood inundations and water levels from hydraulic models will be improved through merging these model results with remotely sensed observations of flood inundations or water levels. This is expected to improve the predictive capability of the hydraulic model.

Overall, using remote sensing data in flood forecasting is expected to lead to better early warning systems, management of floods, and post-processing of flood damages.

The project has two test sites – on the Clarence River in New South Wales, and the Condamine River in Queensland – and is acquiring the required data to meet objectives. It has also selected the hydrologic and hydraulic models to be used in the study, and focused on research utilisation of the project by looking at the optimal application of the coupled models in a data assimilation framework. Publications are being written on this work.

The research is expected to lead to improved flood peak estimates, better mapping of flood extents, and improved flood warnings.

Clarence River, Grafton, NSW
9 May, 2016
CRC research is testing a new approach to flood forecasting using satellite technology, which may be the key to better mitigation.
The HydroSurveyor working near Rogan's Bridge on the Clarence River.
12 February, 2016
A team of CRC researchers has been measuring the shape and depth of the Clarence River bed in northern New South Wales as part of moves to improve flood forecasting for the area.
Improving flood forecasting skill using remote sensing data
25 Aug 2014

Accurate, timely and precise Forecast precipitation is the “holy grail” of flood forecasting; this project aims to use observation constrained hydrologic models to estimate precipitation.

Key Topics:
Improving flood forecasting skills using remote sensing data: precipitation retrieval
18 Aug 2015

Accurate, timely and precise forecast precipitation is the "Holy Grail" of flood forecasting; this project aims to use observation constrained hydrologic models to estimate precipitation.

Key Topics:
Improving Flood Forecast Skill Using Remote Sensing Data - Hydraulic Component
18 Aug 2015

Accurate flood forecast is essential to save lives and reduce damages.How far can we get using remote sensing data to calibrate and constrain in real time a Coupled Hydrologic - hydraulic model?

Improving Flood Forecasting Skill Using Remote Sensing Data - Hydrological Component
18 Aug 2015

Flood forecasts suffer from various SOURCES of uncertainties. This project investigates the benefit of using remotely sensed soil moisture data for hydrological model calibration and updating. A real-time forecasting system constrained by soil moisture and flow data is being developed.

Stefania Grimaldi Conference Poster 2016
14 Aug 2016

The use of remote sensing data in operational flood forecasting is currently receiving increasing attention.

Key Topics:

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