Comparison of Bathymetric Maps with Different Spatial Resolutions for Reservoir Operation
Öz
The volume of water stored in the reservoir of a dam is the main determinant of the operational efficiency of the facility. As a result of sediment accumulation in a dam reservoir, the volume of water in it decreases, and bathymetric maps should be produced periodically to detect such changes. In this study, the bathymetric map of Seyhan Dam Reservoir with a spatial resolution of 10 m produced in 2019 was used. Using the actual bathymetric map, 13 bathymetric maps of different resolutions with spatial resolution between 20 m and 500 m were produced, and using these maps, the elevation-volume tables that form the basis of the dam operation were extracted. The correlation between these tables and the actual elevation-volume tables was analysed and the linear regression coefficients (K) were calculated between 0.99 and 0.74, mean absolute errors (MAE) between 1.67 and 81.10, Nash-Sutcliffe efficiency coefficients (NSE) between 1.00 and 0.76, and percentage biases (PB) between 0.66% and 37.35%. For models with a resolution between 20 m-100 m, K values were 0.99-0.95, MAE 1.67-13.99, NSE 1.00-0.995 and PB 0.66%-5.72%, but after 100 m, K 0.95-0.74, MAE 13.99-81.10, NSE 0.995-0.763, PB 5.72%-37.35%. By using the bathymetric map with a resolution of 100 m, the elevation-volume table to be used in dam management can be produced with a 95% approach and the number of points used in the model corresponds to 1% of the number of points on the real map. In view of the considerable expense associated with the production of a bathymetric map, it is anticipated that the results of the study, which will facilitate the preparation of bathymetric maps at optimal resolutions, will serve to inform future research by reducing the cost, labor, and time requirements of regular and/or urgent measurements.
Anahtar Kelimeler
Kaynakça
- Pan Z, Glennie C, Fernandez-Diaz JC, Starek M. Comparison of bathymetry and seagrass mapping with hyperspectral imagery and airborne bathymetric lidar in a shallow estuarine environment. International Journal of Remote Sensing, 2016; 37:3, 516-536, https://doi.org/10.1080/01431161.2015.1131869
- Miyamoto M, Kiyota M, Murase H, Nakamura T, Hayashibara T. Effects of Bathymetric Grid-Cell Sizes on Habitat Suitability Analysis of Cold-water Gorgonian Corals on Seamounts. Marine Geodesy, 2017; 40:4, 205-223, https://doi.org/10.1080/01490419.2017.1315543
- Kangsabanik S, Paul M, Biswas S, Bakshi S. Studies on navigational depth of a shipping channel using numerical modelling and bathymetric analysis in the Hooghly estuary, India. ISH Journal of Hydraulic Engineering, 2022; https://doi.org/10.1080/09715010.2022.2076572
- Güvel ŞP, Selek B, Seçkin G. Baraj Rezervuarlarına Sediment Etkisinin Araştırılması: Berdan Barajı Örneği. Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 2017; 32(1), 89-98. https://doi.org/10.21605/cukurovaummfd.310060
- Pınarlık M, Selek Z. Evaluation of Sediment Deposition on Corum Dam Reservoir, IOP Conference Series: Materials Science and Engineering, 2019; 471. http://doi.org/10.1088/1757-899X/471/4/042017
- Akgül MA, Dağdeviren M, Biroğlu İ. Satellite-Derived Bathymetry Using Multi-Temporal Satellite Images, DSI Technical Bulletin, 2018; No.127, p.14-27, January 2018.
- Darama Y, Selek Z, Selek B, Akgül MA, Dağdeviren M. Determination of Sediment Deposition of Hasanlar Dam using Bathymetric and Remote Sensing Studies. Natural Hazards, 2019; 97, 211-227 (2019). https://doi.org/10.1007/s11069-019-03635-y
- Güvel ŞP, Akgül MA, Yurtal R. Investigation of sediment accumulation in Berdan Dam Reservoir using bathymetric measurements and Sentinel-2 Data. Arab J Geosci, 2021; 14, 2723. https://doi.org/10.1007/s12517-021-09089-6
- Akgül MA. Comparison of Bathymetric Maps of a Dam Reservoir Produced by Empirical Methods from Satellite Images with Different Spatial Resolutions with In-Situ Data. J Indian Soc Remote Sens, (2024a); 52, 257–269 (2024). https://doi.org/10.1007/s12524-024-01824-2
- Shintani C, Fonstad MA. Comparing remote-sensing techniques collecting bathymetric data from a gravel-bed river. International Journal of Remote Sensing, 2017; 38:8-10, 2883-2902, https://doi.org/10.1080/01431161.2017.1280636