The role of reservoir geometry: Theoretical analysis and derivation of generalized elevation-area-storage relationships

C. Karaisa, The role of reservoir geometry: Theoretical analysis and derivation of generalized elevation-area-storage relationships, Diploma thesis, 131 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, March 2022.



Depth – area – storage relationships are the most important factors for both the design and the function of reservoir in order to control the multiple purposes of water management including flood protection, hydropower energy and water supply and irrigation. Previous land surface modeling studies used simplified depth – area – storage relationships for reservoir modeling. Generally, the most widely used relationship for the estimation of the three characteristic geometrical variables of reservoirs are power law storage – area – depth relationships that use a shape factor and a scale factor for each pair (e.g. depth – storage power law, depth – area power law) and whose accuracy is very high. The aim of this study is to develop generalized elevation – area – storage power type relationships, with the shape parameter kept stable, and subsequently, emphasizing to the elevation – storage equation, to investigate how the two factors are dependent to the typical shape of the reservoir. To begin with, the theoretical analysis was based on data originating from the Global Reservoir Geometry Database, which is a global-scale reservoir storage – area – depth dataset including 6.824 major reservoirs. For each reservoir, the storage-area-depth relationships were derived from an optimal geometric shape selected iteratively from, eventually, three possible regular geometric shapes and export the generalized equations. In order to test this framework, 38 hypothetical reservoirs were created by using Google Earth and ArcGIS. After a long procedure, it was determined that the factors of the aforementioned relationship (i.e., scale and shape factor) depend on the surrounding landscape characteristics, such as the terrain slope, riverbed slope, the bed width and the mean width of the reservoir. Therefore, by using data from 16 Greek Dams, it was confirmed that the storage of a reservoir, as a function of its depth, depends on the surrounding terrain slope and the riverbed slope, which is easily-calculated. For the evaluation of the results, two statistical performance criteria, Nash-Sutcliffe efficiency coefficient (NSE) and root-mean-square error (RMSE), were used to compare the simulated and real depth – storage curves. Lastly, for validation purpose, the exported relationships that were described in the previous chapters, were tested in 7 new existing reservoirs, simulated before and after the filling for safe evaluation.

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