Articles | Volume 14, issue 5
https://doi.org/10.5194/esurf-14-801-2026
https://doi.org/10.5194/esurf-14-801-2026
Research article
 | 
07 Oct 2026
Research article |  | 07 Oct 2026

Forecasting coastal dune mobility: a logistic regression model driven by meteorological data and climate indices

Mauricio Toffani and Silvio Casadío

Data sets

TsoLa model Mauricio Toffani and Silvio Casadio https://doi.org/10.5281/zenodo.21996832

Model code and software

TsoLa model Mauricio Toffani and Silvio Casadio https://doi.org/10.5281/zenodo.21996832

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Short summary
This study shows dune mobility can be predicted using a simple statistical method based only on meteorological data from nearby weather stations and freely available climate indices. The model provides an accessible, low-cost way to anticipate future dune behavior. This information is highly valuable for local communities and decision-makers, as it supports better land-use planning and helps reduce potential damage caused by dune migration, contributing to the management of coastal environments.
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