Print Email Facebook Twitter Reservoir Characterization using a Geometric Approach Title Reservoir Characterization using a Geometric Approach Author Khandelwal, Anshul (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Eisemann, Elmar (mentor) Hildebrandt, Klaus (mentor) van de Giesen, Nick (graduation committee) Liem, Cynthia (graduation committee) Degree granting institution Delft University of Technology Date 2018-09-17 Abstract Quantifying the anthropogenic impacts such as reservoir characterization is a big challenge in the field of water management. In this work, a computer graphics based geometric approach is presented which can predict the underlying topology of large-scale reservoirs. The proposed algorithm uses freely available, satellite based landscape data of the surrounding regions to predict reservoir characteristics. The premise of the presented approach is that the slope of the surrounding landscape is an important determinant to understand the underlying landscape of the reservoirs. This method outperforms the existing state-of-the-art techniques used to estimate the storage capacities drastically, both in terms of estimated maximum volume stored and estimated volume area curves. Evaluation of the geometric model presented is done on 28 reservoirs using the HydroSHEDs data which was developed using the Shuttle RADAR Topography Mission conducted by NASA. This HydroSHEDs data was obtained in 2000 which acts as ground truth data for the reservoirs built after 2000. Further, model parameters are introduced to improve the modeling capabilities of the reconstructed reservoirs. This approach further intensifies the case of using computer graphics techniques for raster based analysis and provides a platform for further research in the field of water management. Subject Reservoir CharacterizationComputer GraphicsOptimizationWater ManagementDigital Elevation Models To reference this document use: http://resolver.tudelft.nl/uuid:dec3c264-d652-4370-864c-1f9ea18cbd2a Part of collection Student theses Document type master thesis Rights © 2018 Anshul Khandelwal Files PDF Anshul_4620410_ThesisFinal.pdf 8.2 MB Close viewer /islandora/object/uuid:dec3c264-d652-4370-864c-1f9ea18cbd2a/datastream/OBJ/view