Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin
Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discha...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/144406 |
| Acceso en línea: | http://hdl.handle.net/11336/144406 |
| Access Level: | acceso abierto |
| Palabra clave: | ENSO EXTREME EVENTS JOINT PROBABILITY LA PLATA BASIN MONITORING RETURN PERIOD VALIDATION https://purl.org/becyt/ford/1.5 https://purl.org/becyt/ford/1 |
| Sumario: | Understanding and monitoring extreme events is essential, particularly in river discharges from the La Plata Basin, where a large percentage of the economic resources and population of the region are concentrated. In this article, we seek to quantify the relationship between extreme events in discharge and the seasonal climatic index NIÑO 3.4. We start by estimating the phase shift between the index and mean seasonal (trimester) discharge values. Based on this result, we align the series and use the copula method to fit a joint distribution. We end up with a model that is particularly useful for quantifying the probability of occurrence of extreme events and monitoring their return periods. As a final step, we generate predictions and validate the model by splitting the series into training and test datasets. We develop a simple effective model for monitoring discharges using the El Niño Southern Oscillation (ENSO) index. |
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