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Sea Level and Coastal Changes

Joint junior research group with MARUM, University of Bremen

Coastal areas are one of the most rapidly evolving systems on Earth. The population density within 100 kilometers of the coastline is nearly 3 times higher than the global average density and 10% of the human population is living less than 10 meters above sea level (especially in the tropical zones). This explains why the evolution of coastal areas is perceived as a relevant problem in need of monitoring, defense or adaptation strategies. Common figures state that the worldwide percentage of beaches under erosion is ~70%. Sea level rise and change in the frequency and intensity of storms are expected to exacerbate the problem, leading to both social and natural negative consequences.

The group has a twofold aim. First, it aims to investigate past interglacials, moments when the earth was warmer than today, in order to gather the elevation of former sea levels and, ultimately, polar ice sheets sensitivity to warmer climates. This work is carried out in collaboration with geologists, ecologists, geophysicists and ice modelers.

Second, the group investigates rates and causes of coastal changes at different time scales in order to understand the sensitivity of different areas to coastal erosion, or to extreme wave events. This work is carried out in collaboration with geologists, sedimentologists, Unmanned Aerial Vehicle and GIS experts and hydrodynamic modelers.

Group Leader

Dr. Alessio Rovere
+49 (421) 23800 - 0

Group page at MARUM more ...

Group page "Coastal Geomorphology" more ...

WG members

Group Leader
Dr. Alessio Rovere

Post Docs
Dr. Daniel Harris

PhD students
Thomas Lorscheid

Dr. Eng. Elisa Casella

Job offers

Information about job offers at ZMT here...


MEDFLOOD is a four-year interdisciplinary project funded by INQUA and launched in 2012 by a team of scientists working in fields concerned with Mediterranean sea-level change. The project has the timely and ambitious aim to build a spatially explicit database of relative sea level markers for the Mediterranean and to use this resource to model risk and help project future flooding in and around the Mediterranean basin.

MIRAMar (Innovative Methodologies for Coastal Environmental Monitoring and Analysis) is a project funded by the European Social Fund, Regione Liguria with a 2 years post doc position co-supervised by the Group Leader. MIRAMar aims to develop innovative methods of survey and analysis for monitoring the evolution of marine and coastal environments, including integration of field data with numerical modelling. Specifically, this project aims to develop advanced techniques for beach monitoring (using Unmanned Aerial Vehicles) in the field of geomorphological variations of low-lying shorelines, particularly in response to extreme events. A nice description of the project can be found in this ‘State of the Art’ blog article by Rebecca Fowler ‘Keeping an eye on coastal erosion

The group collaborates with the PLIOMAX project led by PI Maureen Raymo at Lamont-Doherty Earth Observatory, Columbia University. PlioMax is a five-year research project funded by the US National Science Foundation that aims to increase the accuracy of global sea level estimates for the mid-Pliocene warm period, between 3.3 and 2.9 million years ago. A nice description of why this project has a great importance for understanding future climate changes can be found in this New York Times article, by J. Gillis: How high could the tide go? 

RSLmap and RSLcalc
These two tools were built by A. Rovere, M. Raymo and colleagues within the framework of PLIOMAX. RSLmap is a map of Pliocene and Pleistocene shorelines from published studies, open for crowd-sourced contributions. RSLcalc is a spreadsheet that can be used for calculating relative sea levels from geological field data. In addition to containing fields for essential observations and metadata, the spreadsheet contains equations that can calculate the position of a former sea level, corrected for tectonics using inserted observational values and incorporating uncertainty measured in the field.