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Frappart, F., Papa, F., Guntner, A., Werth, S., da Silva, J.S., Tomasella, J., Seyler, F., Prigent, C., Rossow, W.B., Calmant, S. and Bonnet, M.-P. (2011) Satellite-Based Estimates of Groundwater Storage Variations in Large Drainage Basins with Extensive Floodplains. Remote Sensing of Environment, 115, 1588-1594.
https://doi.org/10.1016/j.rse.2011.02.003

has been cited by the following article:

• TITLE: Integrating Radar Altimeters and Optical Imagery Data for Estimating Water Volume Variations in Lakes and Reservoirs (Case Study: Lake Nasser)

  AUTHORS: Hala M. Ebaid, Medhat Aziz

  KEYWORDS: Radar Altimetry, Water Volume Change, Landsat 8, Lake Nasser, Egypt

  JOURNAL NAME: Journal of Geographic Information System, Vol.9 No.6, December 1, 2017

  ABSTRACT: Monitoring of variations in water for lakes and reservoirs is a requirement for meeting human needs and assessing ongoing climatic changes. However, regular gauging networks fail to provide the information needed for water volume data. The aim of this study is to evaluate an approach to estimate water volume variation for the southern part of Lake Nasser in Egypt without in-situ gauge measurements and bathymetry maps. Combination of both Hydroweb satellite altimetry and Landsat 8 satellite imagery data was used. As compared to in-situ water levels, satellite altimetry provided accurate water levels variations for Lake Nasser; the RMSE was 0.28 m, with excellent agreement (R2 is 0.98). The lowest water level of altimetry database i.e. 174.57 m was used as a reference level for estimating water volumes variations for the study duration 8/2014-6/2015. All water altimetry levels were converted to differences of recorded water level above the lowest altimetry Level (ΔWL). Series of Landsat 8 imagery data were selected to extract surface areas corresponding to radar altimetry water levels dates. Areas-ΔWL relationship model was established as a polynomial function: A = f(ΔWL), and therefore, the relationship of the water volume above the lowest water level for the study time (ΔV) and ΔWL was obtained through the analytical integration of (Area-ΔWL) model. Another approach (Heron method) was also applied for estimating water volume variations. Validation of these two approaches showed that estimated water volume variations above reference water level using both methods i.e. integration and Heron agreed well with in-situ measurements of volume variation deduced from recent bathymetry map and in-situ water levels (R2 for both methods = 0.98). The RMSE for integration method is 323.89 MCM and for Heron method was 318.09 MCM, being approximately 13.2% of the mean volume variations above the lowest reference water level for mean surface area ≈658 km2. Another byproduct for these approaches was the modeling for a remote detecting water level. Once the F(L) relationship is set up for a given region, future Landsat images can be utilized to track water levels freely of radar altimetry. Finally it can be concluded that remote sensing resources (satellites radar altimeters and optical satellite images) that are openly accessible these days represent a great opportunity to remotely monitor reservoir water capacity and help in examining and observing hydrological and water driven procedures.