Abstract
Aswan High Dam Lake (AHDL) is one of the most relevant hot spots at both local and global levels after construction of the Grand Ethiopian Renaissance Dam (GERD) was announced. The management of AHDL is a vital task, which requires the input of reliable information such as the lake bathymetry, water level, and the water surface area. Traditional, bathymetric methods are still very expensive and difficult to operate. Nowadays, satellite data and remote sensing techniques are easily accessible. In particular, datasets produced by operational missions are freely and globally available, and may provide efficient and inexpensive solutions for the retrieval of quantitative parameters concerning strategic water bodies, such as AHDL. This work identifies the performance of Sentinel-3A optical imagery data in the visible and NIR bands from the two optical instruments SLSTR and OLCI, and proposes the integration with Sentinel-3A radar altimetry from SRAL instrument applied to AHDL. This preliminary and first study investigated the relationship between the reflectance data and in situ data for water depth after a bathymetric campaign in the deep-water region using statistical regression models. These statistical models showed promising results in terms of correlation value (R2 > 0.8) and normalized root mean square errors (NRMSE < 0.4). Also, Heron’s formula was applied to combine optical imagery and Sentinel-3 altimetry water level datasets to estimate water storage variations in AHDL. In addition, equations governing the relationship between water level, water surface area, and water volume were analyzed. The work is very useful for all authorities and stakeholders dealing with large water bodies.
Highlights
Remote Sensing (RS) and Geographical Information Systems (GIS) technologies are widely used in the monitoring and management of natural resources such as lakes, due to their advantages of frequent coverage, saving the efforts and cost by the frequent and regular maintenance of traditional on-site measurement systems
We investigated the relationship between the reflectance of optical imagery from two instruments, Sea and Land Surface Temperature Radiometer (SLSTR) and Ocean and Land Color Instrument (OLCI) instruments, hosted by the Sentinel-3A platform and in situ water depth data
The spatial position of the Nubia Lake dataset was used to build a simple model based on a quadratic equation in the calibration phase. Those points were called “test set” and their number was 45 points, while the spatial position of 22 points assigned to the Khor Allaqi dataset, represented the model’s validity relationship between in situ measured depth and corresponding reflectance from green, red, and NIR band for SLSTR and OLCI instruments in the validation phase; those points are called the “Validation set”
Summary
Remote Sensing (RS) and Geographical Information Systems (GIS) technologies are widely used in the monitoring and management of natural resources such as lakes, due to their advantages of frequent coverage, saving the efforts and cost by the frequent and regular maintenance of traditional on-site measurement systems. The new perspective of free and public satellite data is inspiring new observational opportunities in areas where it was not previously possible to support the study of hydrological and hydraulic processes. All these factors make satellite remote sensing an attractive tool for global reservoir monitoring. Stumpf [12] developed the Lyzenga methodology by utilizing a ratio transformation using the blue/green spectral bands for estimating depth and assumed that depth driven change is larger than the corresponding benthic albedo-driven change This method has been adapted and widely applied to the bathymetric mapping of shallow marine environments [13,14]. A good playground in this paper was found in the
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