4.5 Article

Quantifying and modelling the ENSO phenomenon and extreme discharge events relation in the La Plata Basin

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2020.1843655

Keywords

La Plata Basin; extreme events; monitoring; ENSO; joint probability; return period; validation

Funding

  1. Consejo Nacional de Investigaciones Cientificas y Tecnicas [11220130100806]
  2. ANPYCT [PICT-201-0377]
  3. Universidad de Buenos Aires [20020170100330BA]

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This study quantifies the relationship between extreme events in river discharges in the La Plata Basin and the NINO 3.4 seasonal climate index, developing a simple yet effective model for monitoring discharges. The research aligns series and uses the copula method to fit a joint distribution, enabling the quantification of extreme event probabilities and return periods. By splitting the series into training and test datasets, predictions are generated and the model is validated.
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 NINO 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 Nino Southern Oscillation (ENSO) index.

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