A fuzzy classification of the hydrodynamic forcings of the Rhone River plume: An application in case of accidental release of radionuclides

Assessing and modelling the coastal plume dispersion of nuclearized rivers is strategic in case of accidental releases, but taking into account the variation of main hydrodynamic forcings is challenging. This study uses fuzzy c-mean clustering of a 10 years series of discharge and wind speed at the...

Full description

Saved in:
Bibliographic Details
Published in:Environmental modelling & software : with environment data news Vol. 140; p. 105005
Main Authors: Delaval, A., Duffa, C., Pairaud, I., Radakovitch, O.
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01-06-2021
Elsevier Science Ltd
Elsevier
Subjects:
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Assessing and modelling the coastal plume dispersion of nuclearized rivers is strategic in case of accidental releases, but taking into account the variation of main hydrodynamic forcings is challenging. This study uses fuzzy c-mean clustering of a 10 years series of discharge and wind speed at the Rhone River estuary (France) in order to explain the variability of its plume. The method allows to classify the data into 6 scenarios of hydrodynamic forcings that were related to different spatial extensions of the plume, as well as to surface currents measured in-situ. These scenarios were used to simulate the extension and dilution of a radioactive release issued from the river. Based on threshold values of the forcings, a decisional tree is proposed to provide a quick decision tool identifying, in real time, which climatological scenario occurs at the river mouth and the potential plume pattern. •Analyze of 10 years records of discharge and wind conditions at Rhone River mouth.•Fuzzy clustering performed to identify six different hydroclimatological trends.•These trends induce different spreading of the Rhone river plume and contaminants.•Plume shapes identification allows faster decision in case of accidental releases.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2021.105005