Revistas UPV. Editorial UPV

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    Monitoreo de la variación del almacenamiento de agua en la cuenca del Medio y Bajo Paraná a partir de datos GRACE, GRACE FO, TRMM y GLDAS
    (Universitat Politècnica de València, 2021-07-21) Cornero, C.; Pereira, A.; Matos, A. C. O. C.; Pacino, M. C.; Blitzkow, D.; Agencia Santafesina de Ciencia, Tecnología e Innovación
    [EN] GRACE (Gravity Recovery and Climate Experiment) is a satellite mission that can monitor mass distributions in the Earth system, which is closely related to the consequences of climate change. This gravimetric satellite allows to obtain monthly variations of the Earth’s gravity field, which can be associated with water mass variations, after removing the effects of oceanic tides and solid Earth, as well as non-tidal oceanic and atmospheric contributions. In this work, data from GRACE (2002-2017) and GRACE FO (since 2018) were used to analyze the variation of the water mass in the Middle and Low Paraná river basin. The interpretation of the results was carried out by associating the mass anomalies derived from GRACE data with information from the TRMM global rainfall mission. Monthly maps of GRACE water mass variations and TRMM precipitation were produced, which made possible a thorough analysis at a regional level of this mass redistribution in the basin, and its connection to the El Niño and La Niña events that took place in the period under study. The water deficits shown in the 2009 GRACE maps are, in fact, related to the intense episode of La Niña that occurred in the period 2008-2009; while the excess of water storage depicted on the 2016 and 2019 maps is connected to the El Niño phenomenon. Moreover, GRACE has also detected drought events in different sectors between 2011-2012, together with floods in the years 2007 and 2010. Monthly GRACE-derived water storage changes were compared with the independent components of the water balance in the region using different hydrological models estimates. Finally, the temporal variations of the groundwater and the soil part (surface water, soil moisture) were analyzed using the Global Land Data Assimilation System GLDAS. The variables showed a good correlation between them, reaching values of r = 0.80.