Comparisons of Global Terrestrial Surface Water Datasets over 15 Years

Abstract

Continental surface water extents and dynamics are key information to model Earth’s hydrological and biochemical cycles. This study presents global and regional comparisons between two multisatellite surface water extent datasets, the Global Inundation Extent from Multi-Satellites (GIEMS) and the Surface Water Microwave Product Series (SWAMPS), for the 1993–2007 period, along with two widely used static inundation datasets, the Global Lakes and Wetlands Database (GLWD) and the Matthews and Fung wetland estimates. Maximum surface water extents derived from these datasets are largely different: ~13 × 106 km2 from GLWD, ~5.3 × 106 km2 from Matthews and Fung, ~6.2 × 106 km2 from GIEMS, and ~10.3 × 106 km2 from SWAMPS. SWAMPS global maximum surface extent reduces by nearly 51% (to ~5 × 106 km2) when applying a coastal filter, showing a strong contamination in this retrieval over the coastal regions. Anomalous surface waters are also detected with SWAMPS over desert areas. The seasonal amplitude of the GIEMS surface waters is much larger than the SWAMPS estimates, and GIEMS dynamics is more consistent with other hydrological variables such as the river discharge. Over the Amazon basin, GIEMS and SWAMPS show a very high time series correlation (95%), but with SWAMPS maximum extent half the size of that from GIEMS and from previous synthetic aperture radar estimates. Over the Niger basin, SWAMPS seasonal cycle is out of phase with both GIEMS and MODIS-derived water extent estimates, as well as with river discharge data.

Satellite‐Derived Global Surface Water Extent and Dynamics Over the Last 25 Years (GIEMS‐2)

“…A monthly estimate of surface water extents was produced for 1993–2007, with a 0.25° × 0.25° spatial resolution: the Global Inundation Extent from Multiple Satellites (GIEMS). Note that another multisatellite product was generated recently, also based on the merging of passive and active microwave satellite observations, the Surface Water Microwave Product Series (SWAMPS) (Schroeder et al, ), but it showed significant limitations (Pham‐DucPham‐Duc, Prigent, Aires, & Papa et al, ).…”

Remote Sensing of Environmental Changes in Cold Regions: Methods, Achievements and Challenges

“…Potential drawbacks from optical-IR sensors can be partially overcome by active [186] and passive [178,[187][188][189] microwave remote sensing. Daily satellite passive microwave observations were used to monitor spatial variability and multi-year trends in surface inundation in permafrost affected regions [29,188].…”

Interannual Variability of Global Wetlands in Response to El Niño Southern Oscillations (ENSO) and Land-Use

“…Numerous studies have been conducted based on remote sensing both at regional and global scale to analyze the wetlands changes (Pham-Duc et al, 2017;Aires et al, 2018;Wohlfart et al, 2018;Li et al, 2019;Powell et al, 2019). Microwave datasets have an advantage of not being affected by the cloud cover with higher sensitivity to detect inundation changes (Schroeder et al, 2015).…”