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Modelado estadístico del caudal mensual en la baja Cuenca del Plata

Authors: Meis, Melanie; Llano, María Paul;

Modelado estadístico del caudal mensual en la baja Cuenca del Plata

Abstract

Los continuos estudios hidrológicos en la Cuenca del Plata son necesarios no solamente por ser la misma una fuente capaz de proveer energía a diferentes países en Sudamérica, navegabilidad y suministrar agua potable, sino también por los severos daños ocasionados por las frecuentes inundaciones que se producen dicha cuenca. En este trabajo se propuso emplear una modelación estadística basada en modelos estacionales autoregresivos integrados de medias móviles (SARIMA), con el principal objetivo de representar y pronosticar las series temporales del caudal mensual en distintas estaciones de la baja Cuenca del Plata. Se plantearon modelos apropiados para la serie temporal del caudal mensual en la estación Timbúes (Río Paraná) para cinco subperíodos temporales de veinte años desde 1913 a 2012. Para las estaciones de Corrientes, Timbúes y Paso de los Libres se realizó un pronóstico a 32 meses (enero/2013-agosto/2015) teniendo en cuenta el último subperíodo: 1993-2012. La validación de los modelos fue incluida. Además, se realizó un estudio de distintos posibles escenarios a futuro en la estación Corrientes, contrastando los mismos con los valores registrados en ese período. En este sentido, con el análisis realizado, se pretendió encontrar modelos estadísticos que permitan contribuir al monitoreo del caudal mensual en la Cuenca del Plata, con el objetivo de asistir a los tomadores de decisión en la mitigación de los impactos negativos en la región.

Hydrological studies in the La Plata basin are important as it is a source capable of providing water to several countries in South America, a large navigable network and rich in mineral resources. However, the necessity of these studies is highlighted by the frequent floods that occur in it. In this work, it is proposed to employ the statistical modelling through the Seasonal Autoregressive Integrated Moving Average (SARIMA) models, with the aim to represent and forecast the time series for monthly streamflow in different stations in the La Plata Basin. Proper models were proposed for the monthly streamflow time series in Timbúes station (Paraná River) for five subtemporal periods of twenty years from 1913 to 2012. Moreover, for Corrientes, Timbúes and Paso de los Libres stations, a forecast for 32 months (January/2013-August/2015) was carried out taking into consideration the last subperiod, 1993-2012. The validation of the models was considered. Finally, forecast with different future scenarios were done in Corrientes station, and a comparison with the gauged values was included. In this way, it was pretended to find a statistical models in order to contribute to the monitoring of the monthly discharge in the La Plata Basin with the objective to mitigate negative impacts in the region

Fil: Llano, Maria Paula. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Fil: Meis, Melanie. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina

Country
Argentina
Keywords

Pronóstico, PRONOSTICO, ESCENARIOS, SARIMA, CUENCA DEL PLATA, Scenarios, https://purl.org/becyt/ford/1.5, Cuenca del Plata, Escenarios, Forecast, La Plata Basin, https://purl.org/becyt/ford/1

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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