Scientific Data (Sep 2023)

The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps

  • David J. Penton,
  • Jin Teng,
  • Catherine Ticehurst,
  • Steve Marvanek,
  • Andrew Freebairn,
  • Cherry Mateo,
  • Jai Vaze,
  • Ang Yang,
  • Fathaha Khanam,
  • Ashmita Sengupta,
  • Carmel Pollino

DOI
https://doi.org/10.1038/s41597-023-02559-4
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Abstract With growing concerns over water management in rivers worldwide, researchers are seeking innovative solutions to monitor and understand changing flood patterns. In a noteworthy advancement, stakeholders interested in the changing flood patterns of the Murray Darling Basin (MDB) in Australia, covering an area of 1 million km2, can now access a consistent timeseries of water depth maps for the entire basin. The dataset covers the period from 1988 to 2022 at two-monthly timestep and was developed using remotely sensed imagery and a flood depth estimation model at a spatial resolution of ≈30 m, providing a comprehensive picture of maximum observed inundation depth across the MDB. Validation against 13 hydrodynamic model outputs for different parts of the MDB yielded a mean absolute error of 0.49 m, demonstrating reasonable accuracy and reliability of the dataset. The resulting dataset is best suited to system-wide analysis but might also be useful for those interested in the history of flooding at specific locations in the system. We provide the dataset, visualization tools, and examples to support ongoing research.