Assessing Information Transfer Between ENSO and Streamflow in Brazilian Rivers

Assessing Information Transfer Between ENSO and Streamflow in Brazilian Rivers | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 8 April 2025 V1 Latest version Share on Assessing Information Transfer Between ENSO and Streamflow in Brazilian Rivers Authors : Nathalli Rogiski da Silva 0000-0001-6634-1105 [email protected] and Daniel Detzel 0000-0003-2841-6502 Authors Info & Affiliations https://doi.org/10.22541/au.174412092.22152996/v1 217 views 103 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Climate variability is one of the factors that impact a watershed’s hydrological cycle. El Niño – Southern Oscillation (ENSO) is a large-scale climatic phenomenon that alters atmospheric circulation and, consequently, can influence precipitation patterns in certain regions. Changes in precipitation directly affect other hydrological processes, such as streamflow. Therefore, understanding the influence of ENSO is crucial for the planning and operation of water resource systems. This study evaluates the impact of ENSO on the streamflows of Brazilian rivers using information theory. Specifically, it aims to identify the information flow between indices characterizing the phenomenon and streamflow time series. Information transfer was analyzed using effective transfer entropy (ETE), also considering the lag between detecting a change in ENSO state and observing corresponding streamflow variations. Additionally, the relation between these processes was assessed using Kendall’s Tau. The analysis was applied to nine indices commonly used to characterize ENSO, encompassing both atmospheric and/or oceanic components, and to streamflow data from 148 Brazilian hydropower plants (HPPs) within the National Interconnected System. While no clear pattern of information transfer emerged, results indicate temporal and spatial variability of ENSO’s influence. In contrast, the relationship between processes exhibited a more distinct pattern: most HPPs in the equatorial regions experience reduced streamflow during warm ENSO events, whereas the opposite trend is observed in other parts of the country. Furthermore, time played a key role in the analysis, as maximum information transfer generally occurred mainly with lags exceeding one month, regardless of the ENSO index analyzed. Supplementary Material File (manuscript.docx) Download 2.44 MB Information & Authors Information Version history V1 Version 1 08 April 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords el niño-southern oscillation (enso) information theory streamflow timeseries transfer entropy Authors Affiliations Nathalli Rogiski da Silva 0000-0001-6634-1105 [email protected] Universidade Federal do Parana View all articles by this author Daniel Detzel 0000-0003-2841-6502 Universidade Federal do Parana View all articles by this author Metrics & Citations Metrics Article Usage 217 views 103 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Nathalli Rogiski da Silva, Daniel Detzel. Assessing Information Transfer Between ENSO and Streamflow in Brazilian Rivers. Authorea . 08 April 2025. DOI: https://doi.org/10.22541/au.174412092.22152996/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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