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Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability

Open access
CHIEW, FRANCIS H. S., McMAHON, THOMAS A.·2002·Hydrological Sciences Journal

Abstract

El Niño Southern Oscillation (ENSO) has been linked to climate anomalies throughout the world. This paper presents an overview of global ENSO-streamflow teleconnection and identifies regions where the relationship may be exploited to forecast streamflow several months ahead. The teleconnection is investigated by fitting a first harmonic to 24-month El Niño streamflow composites from 581 catchments worldwide and the potential for forecasting is investigated by calculating the lag correlation between streamflow and two indicators of ENSO. The analyses indicate clear ENSO-streamflow teleconnections in many catchments, some of which are consistent across large geographical regions. Strong and regionally consistent ENSO-streamflow teleconnections are identified in Australia and New Zealand, South and Central America, and weaker signals are identified in some parts of Africa and North America. The results suggest that the ENSO-streamflow relationship and the serial correlation in streamflow can be used to successfully forecast streamflow. The streamflow forecasts can be used to help manage water resources, particularly in systems with high interannual variability in Australia, southern and drier parts of Africa and some areas of North America.

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Metadata

Authors
CHIEW, F. H. S., & McMAHON, T. A.
Venue
Hydrological Sciences Journal
Published
2002-06
Volume
47
Issue
3
Pages
505-522
ISSN
  • 0262-6667 (ISSN-L)
  • 2150-3435
OpenAlex
W1984231257
Cited by
228
References
0
FWCI
3.41
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. https://app.cochat.ai/papers/10.1080/02626660209492950
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CHIEW, F. H. S., & McMAHON, T. A. (2002). Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability. Hydrological Sciences Journal. https://doi.org/10.1080/02626660209492950

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.