Comparison of Bathymetric Maps of a Dam Reservoir Produced by Empirical Methods from Satellite Images with Different Spatial Resolutions with In-Situ Data

• Published in: Journal of the Indian Society of Remote Sensing Vol. 52; no. 2; pp. 257 - 269
• Main Author: Akgül, Mehmet Ali
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 01-02-2024; Springer Nature B.V
• Subjects: Bathymetry; Correlation coefficient; Correlation coefficients; Dams; Drinking water; Earth and Environmental Science; Earth Sciences; Flood control; Flood irrigation; Flood mapping; Irrigation; Irrigation water; Landsat; Landsat satellites; Lidar; Measurement methods; Measuring methods; Photogrammetry; Regression coefficients; Remote sensing; Remote Sensing/Photogrammetry; Research Article; Reservoir sedimentation; Reservoirs; Satellite imagery; Satellites; Sonar; Storage capacity; Satellite-derived bathymetry; Landsat 8 OLI; Sentinel-2 MSI; Remote sensing
• ISSN: 0255-660X; 0974-3006
• DOI: 10.1007/s12524-024-01824-2

The volume of water stored in the reservoir is the most important and often used parameter in dam planning, regardless of whether it is used for irrigation, drinking water, or flood control. Although photogrammetric techniques are used to assess storage capacity during the design phase, bathymetric measuring methods are used throughout dam operation. Nowadays, these maps are also created using sonar, lidar, and satellite-derived bathymetry (SDB) in addition to the classic methods of string sounders and sounder battens. Bathymetric maps should be updated regularly to appropriately manage dam operations due to sedimentation entering the dam reservoir. As technology advances, bathymetric maps may be created faster, more precisely, and at a lower cost. One of these methods is SDB, which is commonly used today. In this study, the US National Oceanic and Atmospheric Administration (NOAA) recommended log ratio transformations (LRT) method was employed. The Berdan Dam, chosen as the study area, is located in southern Türkiye and has been built for irrigation, flood control, power, and drinking water. The relationship between the bathymetric map produced by the sonar technique in July 2019 and the SDB maps produced on the same day by the Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) satellites was examined. Pearson correlation coefficient (r), mean absolute error (MAE), Nash–Sutcliffe efficiency coefficient (NSE), and percent bias (PB) statistics were 0.67, 16.43, − 3.74, − 96.8 for Landsat 8 OLI and 0.70, 16.09, − 3.59, − 94.88 for Sentinel-2 MSI. Sentinel-2 MSI regression coefficients were validated by applying them to Landsat 8 RWD, and the r value of the validation was found to be 0.63. The study results showed that the Sentinel-2 MSI satellite for SDB provided more precise bathymetric maps than the Landsat 8 OLI, but the Landsat 8 OLI data were found to be better than the Sentinel-2 MSI data as the depth increased.