Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018

Abstract

Abstract. The recent availability of freely and openly available satellite remote sensing products has enabled the implementation of global surface water monitoring at a level not previously possible. Here we present a global set of satellite-derived time series of surface water storage variations for lakes and reservoirs for a period that covers the satellite altimetry era. Our goals are to promote the use of satellite-derived products for the study of large inland water bodies and to set the stage for the expected availability of products from the Surface Water and Ocean Topography (SWOT) mission, which will vastly expand the spatial coverage of such products, expected from 2021 on. Our general strategy is to estimate global surface water storage changes (ΔV) in large lakes and reservoirs using a combination of paired water surface elevation (WSE) and water surface area (WSA) extent products. Specifically, we use data produced by multiple satellite altimetry missions (TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, and Envisat) from 1992 on, with surface extent estimated from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 on. We leverage relationships between elevation and surface area (i.e., hypsometry) to produce estimates of ΔV even during periods when either of the variables was not available. This approach is successful provided that there are strong relationships between the two variables during an overlapping period. Our target is to produce time series of ΔV as well as of WSE and WSA for a set of 347 lakes and reservoirs globally for the 1992–2018 period. The data sets presented and their respective algorithm theoretical basis documents are publicly available and distributed via the Physical Oceanography Distributed Active Archive Center (PO DAAC; https://podaac.jpl.nasa.gov/, last access: 13 May 2020) of NASA's Jet Propulsion Laboratory. Specifically, the WSE data set is available at https://doi.org/10.5067/UCLRS-GREV2 (Birkett et al., 2019), the WSA data set is available at https://doi.org/10.5067/UCLRS-AREV2 (Khandelwal and Kumar, 2019), and the ΔV data set is available at https://doi.org/10.5067/UCLRS-STOV2 (Tortini et al., 2019). The records we describe represent the most complete global surface water time series available from the launch of TOPEX/Poseidon in 1992 (beginning of the satellite altimetry era) to the near present. The production of long-term, consistent, and calibrated records of surface water cycle variables such as in the data set presented here is of fundamental importance to baseline future SWOT products.

Water Resources in Africa under Global Change: Monitoring Surface Waters from Space

“…2.1 ), now make water storage change estimates in lakes and reservoirs available (Hydroweb and DAHITI for instance), including several water bodies in Africa. Notably, Tortini et al ( 2020 ) and Tusker et al ( 2019 ) built on relationships between elevation and surface area from multiple satellite altimetry missions and surface water extent estimated from Terra/Aqua MODIS or Landsat (such as GSW). They estimate continuous surface water storage changes in large lakes and reservoirs globally for 1992–2019, with many targeted lakes in Africa.…”

GLOBMAP SWF: a global annual surface water cover frequency dataset during 2000–2020

“…The MOD09A1 land surface reflectance product (Version 6) (https://search.earthdata.nasa.gov/, last access: 20 November 2021) was used to generate the SWF dataset. This product contains the atmospherically corrected surface spectral reflectance of MODIS 1-7 bands, including three visible bands (red, blue and green), one NIR band and three SWIR bands (1.2, 1.6 and 2.1 µm) (Vermote, 2015). The 8 d composited surface reflectance with low view angle and absence of clouds or cloud shadows and aerosol loading if available are provided at 500 m resolution in the sinusoidal projection.…”

“…Daily global datasets of inland water bodies were generated at 250-500 m resolution (Klein et al, 2017;Ji et al, 2018), and 8 d datasets were also created at 250 m resolution at global (Han and Niu, 2020) and regional (Lu et al, 2019b) scales. Several datasets for reservoirs and large lakes were also produced from MODIS observations at 8 d temporal and 250-500 m spatial resolution (Khandelwal et al, 2017;Tortini et al, 2020;Li et al, 2021). These high-frequency datasets generally directly identify water pixels for each daily or multi-day composite satellite scene using the following steps.…”

Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin

“…However, optical images, as used in Section 3, are not able to provide any information on water volume or lake bathymetry. First approaches exist to derive storage changes and lake bathymetry from remote sensing techniques (for example, Schwatke et al [8] and Li et al [30]), even on a global scale [7], [31]. However, since these approaches also rely on satellite altimetry, they are not able to provide information for all water bodies.…”