The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps
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...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-09-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02559-4 |
| _version_ | 1827635657829253120 |
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| author | David J. Penton Jin Teng Catherine Ticehurst Steve Marvanek Andrew Freebairn Cherry Mateo Jai Vaze Ang Yang Fathaha Khanam Ashmita Sengupta Carmel Pollino |
| author_facet | David J. Penton Jin Teng Catherine Ticehurst Steve Marvanek Andrew Freebairn Cherry Mateo Jai Vaze Ang Yang Fathaha Khanam Ashmita Sengupta Carmel Pollino |
| author_sort | David J. Penton |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T15:30:39Z |
| format | Article |
| id | doaj.art-df9094f06ac04e78a5316d41b226cd52 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-03-09T15:30:39Z |
| publishDate | 2023-09-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-df9094f06ac04e78a5316d41b226cd522023-11-26T12:19:07ZengNature PortfolioScientific Data2052-44632023-09-0110111110.1038/s41597-023-02559-4The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth mapsDavid J. Penton0Jin Teng1Catherine Ticehurst2Steve Marvanek3Andrew Freebairn4Cherry Mateo5Jai Vaze6Ang Yang7Fathaha Khanam8Ashmita Sengupta9Carmel Pollino10Commonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationMurray-Darling Basin AuthorityCommonwealth Scientific and Industrial Research OrganisationCommonwealth Scientific and Industrial Research OrganisationAbstract 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.https://doi.org/10.1038/s41597-023-02559-4 |
| spellingShingle | David J. Penton Jin Teng Catherine Ticehurst Steve Marvanek Andrew Freebairn Cherry Mateo Jai Vaze Ang Yang Fathaha Khanam Ashmita Sengupta Carmel Pollino The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps Scientific Data |
| title | The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps |
| title_full | The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps |
| title_fullStr | The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps |
| title_full_unstemmed | The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps |
| title_short | The floodplain inundation history of the Murray-Darling Basin through two-monthly maximum water depth maps |
| title_sort | floodplain inundation history of the murray darling basin through two monthly maximum water depth maps |
| url | https://doi.org/10.1038/s41597-023-02559-4 |
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