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University of Bath

Continuous real-time long term monitoring of beach erosion and recovery using LiDAR

This project investigates beach morphodynamics at varying timescales to assess the vulnerability of coastal environments.

An investigation into a variety of issues related to morphological change during storm erosion and recovery and use the knowledge gained to underpin development in predictive modelling tools. This project will investigate beach morphodynamics at timescales ranging from seconds to week by obtaining beach morphology data using a building-mounted Lidar system at two differing sites.

Project outline

A fundamental challenge for Coastal Engineers & Scientists is to determine whether existing sand volumes are adequate to protect coastal areas. A major focus of current research is to develop and improve numerical modelling tools that can be used to undertake this assessment. Development of such models has been hampered by a lack of field data which quantifies morphology change before storm events, during storm events and during the slower and much less studied post-storm recovery phase.

This project will investigate beach morphodynamics at timescales ranging from seconds to week for the following:

  • Gain new insight into the understudied topic of beach recovery including the rate and patterns of morphological changes following storms

  • Investigate coherent patterns of change across the beach face and the relationship with forcing conditions

  • Investigate the relationship between surf-zone bars and swash-zone morphology

  • Compare morphology change at two site under similar conditions


Natural beaches are one of nature’s method of protecting coastal areas, providing a buffer zone which protects the coastal areas from extreme waves and water levels. The reduction in width and volume of beach systems caused by storm erosion dramatically increases the risk to coastal environments. The comes from this project will aid in the assessing the vulnerability of coastal environments with the eventual aim of creating a behavioural model of early warning system.