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Assoc Prof Valentijn Pauwels
Project Leader
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Project leadership

Accurate flood predictions are critically important for limiting the damage caused by floods. Flood forecasting systems are based on models that require large volumes of data, such as rainfall forecasts, detailed measurements and high-resolution topography. However, flood forecasts are prone to uncertainty due to a lack of detailed measurements, and possible errors or oversimplifications in the models and/or data sets. Remote sensing is the science of obtaining information about objects or areas from a distance, typically from aircraft or satellites. This research is integrating this type of data on soil moisture and flood extent with rainfall and runoff models, which will lead to more accurate flood predictions. It will develop a remote sensing-aided methodology that can eventually enable forecasting models that predict the volume of water entering the river network to be applied anywhere in Australia.

Supervisory roles

Year Type Citation
2016 Journal Article Grimaldi, S., Li, Y., Pauwels, V. & Walker, J. Remote Sensing-Derived Water Extent and Level to Constrain Hydraulic Flood Forecasting Models: Opportunities and Challenges. Surveys in Geophysics 37, (2016).
2016 Journal Article Li, Y., Grimaldi, S., Walker, J. & Pauwels, V. Application of Remote Sensing Data to Constrain Operational Rainfall-Driven Flood Forecasting: A Review. Remote Sensing 8, (2016).
2016 Report Pauwels, V., Walker, J., Li, Y., Grimaldi, S. & Wright, A. Improving flood forecast skill using remote sensing: Annual project report 2015-2016. (Bushfire and Natural Hazards CRC, 2016).
2016 Conference Paper Li, Y., Grimaldi, S., Wright, A., Walker, J. & Pauwels, V. Improving flood forecast skill using remote sensing data. AFAC16 (Bushfire and Natural Hazards CRC, 2016).
2015 Report Pauwels, V., Walker, J., Li, Y., Grimaldi, S. & Wright, A. Improving flood forecast skill using remote sensing data: Annual project report 2014-2015. (Bushfire and Natural Hazards CRC, 2015).
2015 Conference Paper Li, Y., Grimaldi, S., Pauwels, V., Walker, J. & Wright, A. Combining hydrologic and hydraulic models for real time flood forecasting - non peer reviewed extended abstract. Adelaide Conference 2015 (2015).
2015 Report Pauwels, V. Improving Flood Forecast Skill Using Remote Sensing Data Annual Report 2014. (2015).

Posters credited

Improving flood forecasting skill using remote sensing data


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.

Improving flood forecasting skills using remote sensing data: precipitation retrieval


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


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


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


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

Key Topics:
Ashley Wright Conference Poster 2016


This research introduces model input data reduction using the discrete wavelet transform to the hydrological sciences.

Key Topics:
Improving flood forecasting skill using remote sensing data: rainfall estimation


This project aims to use hydrologic models and data assimilation theory to estimate catchment wide rainfall.

Improving flood forecast skill using remote sensing data: model/remote sensing data fusion


This project investigates the use of remotely sensed soil moisture data and flood extent/level to improve hydrologic and hydraulic modlling for operational flood forecast.

All the resources from our 2016 conference

Research program in detail

Where, why and how are Australians dying in floods?

2015-2016 year in review

Bushfire planning with kids ebook