Interannual variability of surface water extent at the global scale, 1993–2004

Abstract

[1] Land surface waters play a primary role in the global water cycle and climate. As a consequence, there is a widespread demand for accurate and long-term quantitative observations of their distribution over the whole globe. This study presents the first global data set that quantifies the monthly distribution of surface water extent at ∼25 km sampling intervals over 12 years (1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004). These estimates, generated from complementary multiple-satellite observations, including passive (Special Sensor Microwave Imager) and active (ERS scatterometer) microwaves along with visible and near-infrared imagery (advanced very high-resolution radiometer; AVHRR), were first developed over 1993-2000. The ERS encountered technical problems in 2001 and the processing scheme had to be adapted to extend the time series. Here we investigate and discuss the adjustments of the methodology, compare the various options, and show that the data set can be extended with good confidence beyond 2000, using ERS and AVHRR mean monthly climatologies. In addition to a large seasonal and interannual variability, the new results show a slight overall decrease in global inundated area between 1993 and 2004, representing an ∼5.7% reduction of the mean annual maximum in 12 years. The decrease is mainly observed in the tropics during the 1990s. Over inland water bodies and large river basins, we assess the variability of the surface water extent against related variables such as in situ river discharges, altimeter-derived and in situ river/floodplain water level heights, and precipitation estimates. This new 12 year data set of global surface water extent represents an unprecedented source of information for future hydrological or methane modeling.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

“…The second experiment ("Experiment 2-trans") was a transient historical simulation from 1901-2009, using observed climate and atmospheric CO 2 concentration ([CO 2 ]), with the final (equilibrium) state of Experiment 1-equil as its initial state. Some models require observed fractional inundation values as an input; these were provided and cover the period 1993-2004 by the Global Inundation Extent from Multi-Satellites (GIEMS) dataset (Prigent et al, 2007;Papa et al, 2010). Thus, the period 1993-2004 was selected from Experiment 2-trans for comparison of model results.…”

“…There are several wetland distribution maps that were used for our simulations: (i) remotely sensed inundation area from GIEMS (Prigent et al, 2007;Papa et al, 2010) (Fig. 1), (ii) northern peatland distribution from NCSCD (Northern Circumpolar Soil Carbon Database; Tarnocai et al, 2007Tarnocai et al, , 2009 (Fig.…”

“…GIEMS is derived from a complementary suite of satellite observations including passive microwave observations (SSM/I (special sensor microwave/imager) emissivities), active microwave observations (ERS scatterometer), along with AVHRR-NDVI (Advanced Very High Resolution Radiometer-normalized difference vegetation index). The complete methodology is described in detail in Prigent et al (2007) and Papa et al (2010) Fig. 2.…”

“…Both this parameter and the area fraction of hummocks within the peatland were calibrated to optimize the match with global inundation datasets. For the optimized runs (Experiment 3), the global daily AMSR-E/QuickSCAT-based dataset of Schroeder et al (2010) was used; for all other runs, the GIEMS dataset was used (Prigent et al, 2007;Papa et al, 2010). Parameters for the CH 4 emissions model were calibrated to optimize the in situ observations of Glagolev et al (2010) across West Siberia.…”

Three decades of Landsat-derived spring surface water dynamics in an agricultural wetland mosaic; Implications for migratory shorebirds

“…In recent years, several global inundation analyses have been released that have moved from static, coarse scale (>1 km) products (e.g., Bontemps et al, 2011;Lehner and Döll, 2004;Verpoorter et al, 2014) to more dynamic offerings, such as the Global Inundation Extent from Multi-Satellites (Fluet-Chouinard et al, 2015) and the MODIS water mask (Carroll et al 2009). Studies of wetland dynamics at global scales have typically focused on relatively short time periods with coarse spatial resolution (e.g., Papa et al, 2010;Prigent et al, 2007;25-km grid cells), and therefore have been unable to capture smaller wetland features, or account for longer term cyclical hydrologic variability.…”