Project Details
Description
In recent decades, Costa Rica's climate has been experiencing changes in its behavioral patterns that impact multiple human activities. One of the most important effects is related to river flow volume, which is reflected in water levels for human consumption, irrigation for agricultural production, livestock, recreational access to rivers, natural disaster threats such as floods or landslides due to soil saturation, as well as energy generation in a country where 77% of the electrical grid is supported by hydroelectric plants (ICE, 2021).
Organizations such as CONELECTRICAS have been making empirical efforts to try to reduce the effects of climate change so that the energy requirements of electricity demand can be met. However, the creation of a management plan with an automated system of real-time mathematical models that identify correlations between environmental variables and their effect on the flow levels of the San Lorenzo River, and predictive models that allow for the identification of trends to take early preventive actions that minimize the impact of the plant's electrical production, is crucial
This project's goal is to create a climate management plan coordinated with CONELECTRICAS that includes exploratory and predictive mathematical models, generated from climate-based data and other measurements available to the organization and the National Meteorological Institute in real time. This data is accessed through an automated system that receives new information, incorporates it into the databases, and continuously calibrates the models. The project is limited to the area surrounding the San Lorenzo River basin, so the hydroelectric plant can continue to meet the energy demand for industrial and domestic operations in the area served by the company
Organizations such as CONELECTRICAS have been making empirical efforts to try to reduce the effects of climate change so that the energy requirements of electricity demand can be met. However, the creation of a management plan with an automated system of real-time mathematical models that identify correlations between environmental variables and their effect on the flow levels of the San Lorenzo River, and predictive models that allow for the identification of trends to take early preventive actions that minimize the impact of the plant's electrical production, is crucial
This project's goal is to create a climate management plan coordinated with CONELECTRICAS that includes exploratory and predictive mathematical models, generated from climate-based data and other measurements available to the organization and the National Meteorological Institute in real time. This data is accessed through an automated system that receives new information, incorporates it into the databases, and continuously calibrates the models. The project is limited to the area surrounding the San Lorenzo River basin, so the hydroelectric plant can continue to meet the energy demand for industrial and domestic operations in the area served by the company
Research Lines
1. Química pura y aplicada (Incluye: energía y cambio climático, energías limpias, química verde, impacto ambiental, gestión del riesgo, manejo de residuos, calidad del agua y manejo de cuencas hidrográficas, salud ocupacional e higiene ambiental, sostenibilidad y desarrollo local, recursos naturales y agroindustria. Metrología y normalización, química de materiales, agroalimentaria, espectroscopía, seguridad química, química analítica, electroquímica, ingeniería química, bioquímica, nanotecnología, química industrial, cristalografía, productos naturales, química medicinal).
2. Investigación educativa, tecnológica y científica en el área de las matemáticas, estadísticas, ciencia de los datos y matemáticas aplicadas
2. Investigación educativa, tecnológica y científica en el área de las matemáticas, estadísticas, ciencia de los datos y matemáticas aplicadas
| Status | Active |
|---|---|
| Effective start/end date | 1/01/25 → 31/12/26 |
Keywords
- environmental models
- energy matrix
- management plan
- Climate change
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