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A GIS-based assessment of maximum potential hydropower production in La Plata basin under global changes
, Institute for Water Education, Westvest 7, PO Box 3015, 2601 DA Delft, Netherlands.ORCID iD: 0000-0002-7575-8989
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2013 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 50, p. 103-114Article in journal (Refereed) Published
Abstract [en]

Population growth, economic development, urbanization, changes in hydrological regimes and land use are the main drivers affecting allocation and exploitation of water resources. The pressure exerted by these global changes on the five countries -Argentina, Bolivia, Brazil, Paraguay and Uruguay- located in La Plata Basin over the last decades has raised the need for assessing trends in future electricity demand and energy production in the basin.The aim of this research is to assess whether (and when) shortage and vulnerabilities in terms of hydropower generation are to be expected in La Plata basin in the next decades. The methodology proposed has focused on two aspects to reach the objectives: 1) assessment of hydropower production and electricity demand in the basin over the last twenty years (1987-2008), in order to establish growing trends for the next thirty years; 2) computation of maximum potential hydropower using the newly developed Arc-GIS based tool VAPIDRO-ASTE. The assessment and calculation have been applied to La Plata River and its main tributaries: Paranaiba, Grande River, Tiete, Paranapanema, Iguaçu, Uruguay, Negro River, Paraguay and Paraná. The first outcomes of this research show that La Plata Basin has high hydropower potential. About 40% of the hydropower potential is already used to produce and supply energy. Out of the remaining 60% potential, about 25% could hardly be exploited because of environmental issues or low cost/benefit ratio. Thus, the estimated residual potential hydropower is about 35% of the maximum potential hydropower calculated.

Place, publisher, year, edition, pages
2013. Vol. 50, p. 103-114
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Ocean and River Engineering
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URN: urn:nbn:se:kth:diva-248551DOI: 10.1016/j.renene.2012.06.019Scopus ID: 2-s2.0-84863832360OAI: oai:DiVA.org:kth-248551DiVA, id: diva2:1303388
Note

QC 20190618

Available from: 2019-04-09 Created: 2019-04-09 Last updated: 2019-06-14Bibliographically approved

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