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Application of SWOT Satellite for monitoring the 2025 Extreme Floods in Australia’s Channel country River System
* 1 , 1 , 2 , 1
1  Environmental Futures, School of Science, University of Wollongong, Wollongong 2522, New South Wales, Australia
2  The Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Jerusalem 9190500, Israel
Academic Editor: Nikiforos Samarinas

Abstract:

Australia’s Channel Country rivers experienced their highest recorded flood in 2025, caused by extreme rainfall from a monsoonal low-pressure trough. This extreme flood event surpassed the previous record from 1974, as confirmed by the measurements from the few gauging stations operated by the Queensland and South Australian water departments. In addition to the sparse gauging records, satellite imagery indicates that the 2025 flood resulted in the largest satellite derived inundation extent ever observed, surpassing the previous maximum inundation recorded by the Landsat satellites (1987 - 2025).

In this study, we present a novel method for assessing the magnitude of the 2025 extreme flooding event in the Cooper Basin, one of the most severely affected rivers in Australia’s Channel Country. SWOT pixel cloud data, optical satellite imagery, and a Lidar-derived digital elevation model (DEM) were used to assess flood depth and volume. Flood depth hydrographs were validated against water level data at four gauging stations, showing excellent agreement with the best results of ± 11 cm (RMSE) and ± 8.1 cm (MAE). The results were compared with the 100-year recurrence JRC global flood map for the same event in the Cooper Basin highlighting that our proposed approach improves estimations for large-scale inundation predictions. Our results demonstrate the capability of SWOT observations to monitor flood dynamics through transect profiling and volume estimation. Furthermore, the derived peak floodwater depths provide valuable inputs for calibrating hydrodynamic models, improving predictive accuracy and local flood assessments. Overall, this study represents the largest remotely sensed arid zone flood in Australia and highlights the potential for incorporating SWOT observations into the correction and validation of flood models, particularly in data-scarce regions.

Keywords: Extreme flood, Dryland rivers, Channel Country, SWOT satellite, Flood Depth
Comments on this paper
wastedshampo shampo
It's fascinating to see the application of SWOT Satellite for monitoring extreme floods in Australia’s Channel country River System. The use of Bi-LSTM and satellite rainfall estimates in flood prediction is cutting-edge. I wonder how these technologies could be further optimized for real-time flood management. Maybe incorporating run 3
Atul Rai
Thank you for reaching out and your generous comment. We look forward to exploring the coupling of rainfall volume with flood depth. One of the major challenges is the flow lag period, which can take months for water to reach downstream lakes in this complex, anastomosing river system. We would greatly appreciate any new ideas, particularly regarding the estimation of flood peak flow from rainfall, which could be validated against SWOT observations at different locations.
I will explore your article. You can also reach me via my university email.

Best regards,
Atul

wastedshampo shampo
It's fascinating to see the application of SWOT Satellite technology for monitoring extreme floods in Australia. The use of Bi-LSTM and satellite rainfall estimates for flash flood prediction is innovative. I wonder how these methods could be combined for even more accurate predictions. Exciting research! Have you explored sciforum.net/paper/view/25578run 3

wastedshampo shampo
The use of SWOT Satellite for monitoring extreme floods in Australia's Channel country River System sounds fascinating. I wonder how the Bi-LSTM and satellite rainfall estimates could enhance predictions in other regions as well. This innovative approach opens up new possibilities for accurate flood forecasting. Interested readers might also enjoy exploring the game gg



 
 
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