Linking Long-Term Water Balances and Statistical Scaling to Estimate River Flows along the Drainage Network of Colombia
Publication: Journal of Hydrologic Engineering
Volume 12, Issue 1
Abstract
Long-term average river discharges as well as peak and low flows of different return periods are estimated along the entire river network of Colombia, through the conjoint use of the long-term water balance in the river basins and the framework of statistical scaling, taking the average flow field as the scaling variable. Estimation of the long-term water balance considers the spatial variability of hydrologic fields, in which drainage basins are considered the basic hydrological control volumes for estimation. A systematic effort has been made to estimate the long term average precipitation field combining rain gauge measurements with existing handmade expert maps as an input trend for a universal Kriging interpolation technique. Evaluation of estimates for actual and potential long-term evapotranspiration was implemented using diverse methods. Results were tested using the long term water balance equation against 200 streamflow gauging stations. No method for actual evapotranspiration showed significant superiority. Overall, we conclude that the magnitude of errors arises fundamentally from deficiencies in the data and the sparsity of the observations.
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Acknowledgments
This work has been supported by UPME from the Ministry of Mining and Energy of Colombia, by COLCIENCIAS, by DIME from Universidad Nacional de Colombia, and by the Interamerican Institute for Global Change Research (IAI). The first author is grateful to CIRES (U. Colorado, Boulder) for support as a Visiting Fellow. The writers thank H. Diaz, V. K. Gupta, P. R. Waylen, E. Machado, and A. Jaramillo and three anonymous reviewers for helpful comments. To the Distributed Active Archive Center (DAAC) at the Goddard Space Flight NASA Center, for providing access to radiation data sets, to the USGS for access to the GTOPO30 data, to LBA project for precipitation data from the Amazon, to K. Dunne for providing the water holding capacity data, and to Empresas Públicas de Medellin (EPM), Corporación del Valle del Cauca (CVC), and Cenicafé for providing access to data.
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Published In
Journal of Hydrologic Engineering
Volume 12 • Issue 1 • January 2007
Pages: 4 - 13
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© 2007 ASCE.
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Received: Jun 3, 2003
Accepted: Apr 26, 2006
Published online: Jan 1, 2007
Published in print: Jan 2007
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