Fluvial palaeohydrology in the 21st century and beyond

Professor Kenneth J. Gregory was a major contributor to fluvial palaeohydrologicalresearch. Beginning in the early 1980s, under his influence, rapid internationalgrowth of the discipline was accompanied by major advances in research methodsand techniques. Current research emphases include applicatio...

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Bibliographic Details
Published in:Earth Surface Processes and Landforms
Main Authors: Baker, Victor R., Benito, Gerardo, Brown, Antony G., Carling, Paul A., Enzel, Yehouda, Greenbaum, Noam, Herget, Jürgen, Kale, Vishwas S., Latrubesse, Edgardo M., Macklin, Mark G., Nanson, Gerald C., Oguchi, Takashi, Thorndycraft, Varyl R., Dor, Yoav Ben, Zituni, Rami
Format: Article in Journal/Newspaper
Language:English
Published: John Wiley & Sons 2022
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Online Access:http://hdl.handle.net/10261/266389
Description
Summary:Professor Kenneth J. Gregory was a major contributor to fluvial palaeohydrologicalresearch. Beginning in the early 1980s, under his influence, rapid internationalgrowth of the discipline was accompanied by major advances in research methodsand techniques. Current research emphases include applications of quantitative modelling and meta-analysis; the correlation of fluvial events to other records,notably palaeolacustine records; and methods for application to diverse issues ofriver engineering and management. The international expansion and detailed analyses of fluvial palaeohydrology are exemplified by recent studies done in Fennoscandia, the Mediterranean region, India, Israel, Australia, Pacific humid islandarcs, and South America. Future developments will involve expanded work withother academic disciplines, such as archaeology, as well as applications to practical problems arising from future climatic change and related environmental hazards, particularly extremes. Remote sensing and high-resolution topography data and tools (e.g. LiDAR) will facilitate new discoveries of ancient exceptional flooding phenomena (megaflooding and superfloods) on Earth and on the palaeofluvial forms of Earth-like planets. New opportunities will also arise from the increased use of machine learning and artificial intelligence for analyses of big data. Time devoted to the preparation of this state-of-the-science review was supported by the institutions listed as author affiliations. Peer reviewed