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1.1 Statistical analyses of meteorological data from the coastal zone of Ecuador and in the Río Paute basin to determine inter annual variability patterns in Ecuador.
1.2 Correlation between precipitation, Sea Surface Temperature (SST), and Southern Oscillation Index (SOI) to identify El Niño signal.
1.3 Analyze dry periods in the Río Paute region related to the presence of El Niño in Ecuador and to hydroelectric production.
2.1 General layout of the Río Paute project.
2.2 Statistical analyses of Río Paute hydropower production since its starting operation and its relation to climate variability.
2.3 Prediction of hydroelectric power production.
2.4 Analyses of dry periods and their consequences on Ecuador's energy production.
2.5 Analysis of the decision-making process to mitigate the impact of dry periods in Ecuador.
3.1 Simulate daily precipitation based on observed daily precipitation.
3.2 Generate streamflow from precipitation data using a rainfall-runoff model.
3.3 Simulate hydroelectric power production.
3.4 Statistics of simulated hydroelectric power generation.
4.1 Identify decision variables and management scenarios.
4.2 Optimize hydroelectric power production for normal years and for dry periods.
4.3 Analyze and tabulate results.
4.4 Estimate potential information value.
5.1Social and economical impacts of reduced energy production.
5.2 Institutional aspects related to energy shortage management.
5.3 Decision making process and public response capability.
Slide show: Final presentation by mini-project participants
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Page Last Updated: January 15, 2000 Contact Information: Guillermo Podestá, Institute Science Coordinator e-mail: gpodesta@rsmas.miami.edu Telephone: 1.305.361.4142 FAX: 1.305.361.4622