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ISPRS Int. J. Geo-Inf. 2015, 4(1), 220-235; doi:10.3390/ijgi4010220

Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management

Remote Sensing Division, National Institute for Space Research, São José dos Campos, 12227-010 São Paulo, Brazil
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editors: Linda See and Wolfgang Kainz
Received: 10 June 2014 / Accepted: 26 January 2015 / Published: 2 February 2015
(This article belongs to the Special Issue Spatial Analysis for Environmental Applications)
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Abstract

The generation of reliable information for improving the understanding of hydroelectric reservoir dynamics is fundamental for guiding decision-makers to implement best management practices. In this way, we assessed the performance of different interpolation algorithms to map the bathymetry of the Tucuruí hydroelectric reservoir, located in the Brazilian Amazon, as an aid to manage and operate Amazonian reservoirs. We evaluated three different deterministic and one geostatistical algorithms. The performance of the algorithms was assessed through cross-validation and Monte Carlo Simulation. Finally, operational information was derived from the bathymetric grid with the best performance. The results showed that all interpolation methods were able to map important bathymetric features. The best performance was obtained with the geostatistical method (RMSE = 0.92 m). The information derived from the bathymetric map (e.g., the level-area and level-volume diagram and the three-dimensional grid) will allow for optimization of operational monitoring of the Tucuruí hydroelectric reservoir as well as the development of three-dimensional modeling studies. View Full-Text
Keywords: mapping; reservoir; environmental assessment; environmental management mapping; reservoir; environmental assessment; environmental management
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Curtarelli, M.; Leão, J.; Ogashawara, I.; Lorenzzetti, J.; Stech, J. Assessment of Spatial Interpolation Methods to Map the Bathymetry of an Amazonian Hydroelectric Reservoir to Aid in Decision Making for Water Management. ISPRS Int. J. Geo-Inf. 2015, 4, 220-235.

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