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Discussion papers
https://doi.org/10.5194/essd-2019-219
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-2019-219
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 02 Jan 2020

Submitted as: data description paper | 02 Jan 2020

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This preprint is currently under review for the journal ESSD.

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

Riccardo Tortini1, Nina Noujdina1, Samantha Yeo1, Martina Ricko2, Charon M Birkett3, Ankush Khandelwal4, Vipin Kumar4, Miriam E Marlier5, and Dennis P Lettenmaier1 Riccardo Tortini et al.
  • 1Department of Geography, University of California - Los Angeles, Los Angeles, CA, USA
  • 2KBRwyle Inc., Greenbelt, MD, USA
  • 3NASA Goddard Space Flight Center, Greenbelt, MD, USA
  • 4Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA
  • 5Institute of the Environment and Sustainability, University of California - Los Angeles, Los Angeles, CA, USA

Abstract. The recent availability of freely and openly available satellite remote sensing products has enabled the implementation of global surface water monitoring to 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 goal is 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 from 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 WSE and WSA for a set of 347 lakes and reservoirs globally for the 1992–2018 period. The data sets presented are publicly available and distributed via NASA’s Jet Propulsion Laboratory’s Physical Oceanography Distributed Active Archive Center (PO DAAC; https://podaac.jpl.nasa.gov/). 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 near-present. The production of long-term, consistent, and calibrated records of surface water cycle variables such as the data set presented here is of fundamental importance to baseline future SWOT products.

Riccardo Tortini et al.

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Status: open (until 27 Feb 2020)
Status: open (until 27 Feb 2020)
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Riccardo Tortini et al.

Data sets

Pre SWOT Hydrology Global Lake/Reservoir Surface Inland Water Height GREALM V2 C. M. Birkett, M. Ricko, and X. Yang https://doi.org/10.5067/UCLRS-GREV2

Pre SWOT Hydrology Global Lake/Reservoir Surface Inland Water Area Extent V2 A. Khandelwal and V. Kumar https://doi.org/10.5067/UCLRS-AREV2

Lake and Reservoir Storage Time Series V2 R. Tortini, N. Noujdina, S. Yeo, A. Khandelwal, V. Kumar, C. M. Birkett, M. Ricko, X. Yang, and D. P. Lettenmaier https://doi.org/10.5067/UCLRS-STOV2

Riccardo Tortini et al.

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Short summary
We present a global collection of satellite-derived time series of surface water volume changes for 347 lakes and reservoirs for 1992–2018. These changes were estimated using a statistical relationship between water surface elevation and area measured from satellite, even during periods when either elevation or area was not available. These records represent the most complete global surface water time series, and they are of fundamental importance to baseline future satellite missions.
We present a global collection of satellite-derived time series of surface water volume changes...
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