EventsThe 9th International Electronic Conference on Water Sciences
Published
This submission belongs to the session S7. Remote Sensing, Artificial Intelligence and New Technologies in Water Sciences of the event The 9th International Electronic Conference on Water Sciences
Published date
06 Nov, 2025
Academic Editor
author-avatarNikiforos Samarinas
Citation
Atul Kumar Rai, Timothy J Cohen, Moshe Armon, Samuel K Marx, Application of SWOT Satellite for monitoring the 2025 Extreme Floods in Australia’s Channel country River System, in Proceedings of The 9th International Electronic Conference on Water Sciences, 11 November–14 November 2025, MDPI: Basel, Switzerland
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Application of SWOT Satellite for monitoring the 2025 Extreme Floods in Australia’s Channel country River System

Timothy J Cohen 1
Samuel K Marx 1
1. Environmental Futures, School of Science, University of Wollongong, Wollongong 2522, New South Wales, Australia, Australia
2. The Fredy and Nadine Herrmann Institute of Earth Sciences, the Hebrew University of Jerusalem, Jerusalem 9190500, Israel, Israel
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
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