Merging Landsat and airborne LiDAR observations for continuous monitoring of floodplain water extent, depth and volume

Jiawei Hou*, Albert I.J.M. Van Dijk, Luigi J. Renzullo

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)


The Darling River system in Australia is under pressure from water extraction and climate change. Management interventions such as environmental flow releases require understanding of water storage dynamics and the connectivity of floodplains and wetlands. Such knowledge can be gleaned from the long observational record of the Landsat series of satellite sensors and high (<5 m) resolution digital elevation models derived from airborne light detection and ranging (LiDAR). Here, for the first time, we develop and demonstrate an approach to reconstruct 16-day floodplain water dynamics, including extent, depth, and volume for a long Landsat time series (1987 to present). Time series mapping of surface water extent at 5-m resolution was achieved by topographic downscaling of Landsat-derived surface water data. We propose a simple and effective algorithm to restore missing data in the images caused by, e.g., cloud and shadows, swath edges and the Landsat 7 Scan Line Corrector (SLC) failure, thereby increasing the number of useable images five-fold. The 5-m surface water extent maps clearly delineate the narrow river channel and the boundary of floodplain wetlands. They can capture the development, peak and retreat of flood events. By combining Landsat and airborne LiDAR observations, we produced time series of surface water depth mapping at 5-m resolution, accounting for the degree of hydraulic surface water connectivity. Based on these maps, we derived 16-day floodplain volume dynamics for 1987 to present. The correlation coefficient between upstream river flow records and floodplain volume time series was 0.88, indicating that the estimates were robust. The algorithms developed can be used for ongoing very high-resolution mapping to assist in managing human water use and environmental health in the Murray-Darling Basin.

Original languageEnglish
Article number127684
JournalJournal of Hydrology
Publication statusPublished - Jun 2022
Externally publishedYes


  • Floodplain
  • Landsat
  • LiDAR
  • Water depth
  • Water extent
  • Water volume


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