Spatio-temporal analysis of remotely sensed rainfall datasets retrieved for the transboundary basin of the Madeira river in Amazonia

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Vinicius Alexandre Sikora de Souza
http://orcid.org/0000-0002-5902-6139
Daniel Medeiros Moreira
http://orcid.org/0000-0002-8915-094X
Otto Corrêa Rotunno Filho
http://orcid.org/0000-0003-2763-4401
Anderson Paulo Rudke
http://orcid.org/0000-0003-2970-5453
Claudia Daza Andrade
http://orcid.org/0000-0001-6074-152X
Lígia Maria Nascimento De Araujo
https://orcid.org/0000-0002-3635-851X

Abstract

Rainfall is recognized to represent the most important driving force of the hydrologic cycle. To properly represent the spatio-temporal rainfall variability continues to be an enormous hydrological task when using commonly sparse, if available, rain gauges network. Therefore, the present study devoted a special effort to analyze the robustness of some satellite rainfall products, notably the so-called datasets hereafter named as (i) CHIRP (Climate Hazards Group InfraRed Precipitation), (ii) CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), (iii) 3B42 and (iv) 3B42RT of the Tropical Rainfall Measuring Mission (TRMM),  to adequately represent the pluviometric regime in the Madeira river basin. To assess the accuracy of acquired remotely sensed rainfall products, comparisons to observational available rain gauges usually taken as ground-truth in the literature, despite their well-known limitations, were performed. Wavelet analysis was also used to validate the performance of the referred satellite products by means of extracting the corresponding cycles, frequencies, and tendencies along the available time series across the studied basin. The results showed that the data sources CHIRPS and CHIRP better represent the pluviometric phenomenon by means of their monthly accumulated rainfall in the Madeira river basin when compared to 3B42 and 3B42RT products taking into account rain gauges as baseline information. The CHIRPS product performed the best among the selected rainfall estimators for the Madeira river basin. Further analysis brought up also another very interesting result related to non-rainfall periods, which is usually not reported. However, such evaluation is quite important in hydrology when examining run sequences of droughts and consequent effects in the water balance at the watershed scale. Highly accurate estimates in the sense of identifying non-rainfall periods by remotely sensed information was achieved what represents an additional and valuable asset of satellite rainfall products. It is worthwhile to say that this perspective does deserve to receive much more attention in the literature in order to deeply discuss the water-energy-food nexus.

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Author Biographies

Vinicius Alexandre Sikora de Souza, Civil Engineering Program, Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ).

Doctor of Civil Engineering

Daniel Medeiros Moreira, Department of Hydrology, Companhia de Pesquisa de Recursos Minerais (CPRM), Geological Survey of Brazil

Doctor of Civil Engineering

Otto Corrêa Rotunno Filho, Civil Engineering Program, Alberto Luiz Coimbra Institute for Postgraduate Studies and Research in Engineering (COPPE), Federal University of Rio de Janeiro (UFRJ)

Doctor of Civil Engineering

Anderson Paulo Rudke, Federal University of Minas Gerais

Master of Environmental Engineering

Claudia Daza Andrade, Federal Rural University of Rio de Janeiro

Doctor of Civil Engineering

Lígia Maria Nascimento De Araujo, Brazilian National Water Agency

Doctor of Civil Engineering

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