ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Comparisons of Global Terrestrial Surface Water Datasets over 15 Years

Pham-Duc, Binh and Prigent, Catherine and Aires, Filipe and Papa, Fabrice (2017) Comparisons of Global Terrestrial Surface Water Datasets over 15 Years. In: JOURNAL OF HYDROMETEOROLOGY, 18 (4). pp. 993-1007.

Full text not available from this repository. (Request a copy)
Official URL: https://doi.org/10.1175/JHM-D-16-0206.1

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: similar to 13 x 10(6) km(2) from GLWD, 5.3 x 10(6) km(2) from Matthews and Fung, similar to 6.2 x 10(6) km(2) from GIEMS, and similar to 10.3 x 10(6) km(2) from SWAMPS. SWAMPS global maximum surface extent reduces by nearly 51% (to similar to 5 x 10(6) km(2)) 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.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the AMER METEOROLOGICAL SOC, 45 BEACON ST, BOSTON, MA 02108-3693 USA
Department/Centre: Division of Biological Sciences > Centre for Ecological Sciences
Depositing User: Id for Latest eprints
Date Deposited: 05 Aug 2017 09:36
Last Modified: 05 Nov 2018 12:06
URI: http://eprints.iisc.ac.in/id/eprint/57588

Actions (login required)

View Item View Item