Storms are key drivers of coastal dynamics and are responsible for the largest short-term morphological changes in coastal barriers (c.f. Masselink and van Heteren, 2014). Storms produce very significant hazards that endanger life and properties in developed coastal areas, and modification and/or fragmentation of habitats along natural coastlines (Ferreira et al. 2017). Along European coastlines the impact of storm-induced coastal flooding will increase markedly by the end of the century, with annual damages potentially rising up to 961 billion euros and affecting over 3.5 million people every year (Vousdoukas et al., 2018a). Globally, the number of people living below the projected annual coastal flooding levels will increase to 630 million by 2010 (Kulp and Strauss, 2019).
The impacts of storms are spatially and temporally diverse, but primarily dependent on the magnitude of a storm’s hydrodynamic forcing and the morphology of the coastal barrier, as conceptualized in the Sallenger (2000) storm impact scale. Impacts can range from minor beach erosion to widespread inundation and disintegration of entire coastal sections, with a range of associated hazards that are commonly described using either forcing or morphology parameters. However, to fully characterize a coastal hazard it is necessary to use a suite of indicators that combine the forcing mechanisms with realistic coastal morphology elements to determine the effects of the coastal processes acting on the coastal system, i.e. process-based indicators (Ferreira et al., 2017). For storms impacting coastal barriers, the most significant storm-induced hazards are erosion, overwash (overtopping) of natural (or engineered) barriers and inundation, which can be described by a range of indicators such as shoreline or dune retreat, overwash/overtopping discharge or inundation extent. These can be determined using a wide range of models, from simple empirical approximations to high-resolution coupled numerical modelling frameworks (e.g. Zou et al., 2013; Plomaritis et al., 2018).
Models to assess storm-induced coastal hazards are often applied at local to regional scales. However, recent advances in modelling of storm hydrodynamic forcing (e.g. Muis et al., 2016) and remotely-sensed characterization of coastal morphology (e.g. Kulp and Strauss, 2018) have broaden the spatial coverage of applications to global scales. Aided by new data processing tools for coastal analysis (e.g. Luijendjik et al., 2018) and detailed projections of extreme hydrodynamic forcing under a changing climate (Vousdoukas et al., 2018b), future temporal changes in storm-induced coastal hazards can be more comprehensively assessed.
This project aims to evaluate storm-induced coastal hazards at global scale, specifically overwash/overtopping and inundation of natural/engineered coastal barriers using a range of process-based indicators. It will also explore potential changes due to rising sea levels and climate change. To achieve this, the project’s specific objectives are to:
1) Characterize the morphology of natural and engineered barriers using global-scale remotely sensed topographic datasets, validated with high-resolution LIDAR data for a range of representative coastal locations, and determine relevant storm-induced hydrodynamic forcing conditions.
2) Implement a comprehensive set of process-based morphodynamic indicators to determine storm-induced overwash/overtopping potential and inundation extent in natural/engineered coastal barriers at global scale.
3) Explore the spatial variability and contrasted exposure to storm hazards in natural and engineered barriers, determining the relative contribution of different processes and considering potential impacts of a changing climate and rising sea levels.
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Storm impacts in coastal barriers
This project will use a combination of remotely sensed data processing and modelling techniques, meteorological and oceanographic data, statistical and spatial analysis alongside field surveys in specific coastal areas, in order to generate novel understanding of storm-induced coastal hazards in natural and engineered barriers at a global scale.
To characterize coastal barriers different remotely sensed global topographic datasets (including SRTM, ASTER and SAR products) will be assessed against high-resolution LIDAR datasets and field data. Validation will be performed for a range of coastal barriers around the globe, including southern Portugal, Scotland and the US east coast. Topographic data will be integrated with bathymetric and land cover datasets in order to characterise the nearshore and inland sections adjacent to coastal barriers. Representative storm-induced hydrodynamic forcing conditions, including extreme wave parameters and storm-surge levels, will be compiled for the present from global reanalysis and for future conditions based on global climate model projections.
The morphological and hydrodynamic datasets will be integrated to compute a range of process-based morphodynamic indicators of storm-induced coastal hazards. Specifically we will focus on overwash/overtopping potential and inundation extent in natural and engineered barriers, for current conditions and for the years 2050 and 2100 based on climate projections. Specific process-based indicators will be defined according to a sensitivity analysis that considers the limitations of global datasets, alongside an uncertainty analysis based on ensemble predictions. The application of process-based indicators will be assessed against higher resolution implementation and field verification in southern Portugal. Results from the application of process-based indicators will be explored to identify spatial variability patterns and obtain insights regarding the relative contribution of different morphodynamic processes to storm-induced coastal hazards at a global scale. The findings of this project will contribute to improved understanding and management of coastal vulnerability to storms and how they will evolve in the future.
To achieve this the student will be supervised by a multi-institutional team composed by scientists in the Universities of Stirling (Loureiro, Marino), Heriot-Watt (Zou) and Algarve (Ferreira).
Literature review; compilation and validation of topographic datasets and characterization of coastal barriers; integration of bathymetric and land cover datasets; Attendance of UK Young Coastal Scientists and Engineers Conference.
Selection and calculation of storm hazard process-based indicators; sensitivity and uncertainty analysis; 2-week field survey in southern Portugal; data integration and drafting of baseline results. Attendance of 2022 Coastal Engineering conference (in Rome).
Implementation of process-based indicators at global scale for present and future conditions; data analysis and drafting of results for publication. Attendance of 2023 Coastal Sediments conference (in US).
Finalize manuscripts/chapters; submit thesis.
The student will receive extensive training-trough-research under the guidance of the supervisory team, which will be complemented by specific training activities to equip the student with the skills and expertise to become an independent researcher. Specific training in research methods will include programming with Python and Matlab for analysing topographic data, mining hydrodynamic modelling datasets and perform statistical analysis, geospatial technologies for data integration and analysis, fieldwork design and instrumentation. These will be complemented by training in core scientific skills (writing, presentation and science communication) and transferable skills (data management, task coordination and exploitation of results with end users).
The student will also participate in IAPETUS2 training and events, which will complement the personal training plan.
References & further reading
Ferreira et al., 2017. Earth-Science Reviews 173: 159-167.
Kulp and Strauss, 2018. Remote Sensing of Environment 206: 231-239.
Kulp and Strauss, 2019. Nature Communications 10: 4844.
Luijendjik et al., 2018. Scientific Reports 8: 6641.
Masselink and van Heteren, 2014. Marine Geology 352, 321-347.
Muis et al., 2016. Nature Communications 7: 11969.
Plomaritis et al., 2018. Coastal Engineering 134: 124-133.
Sallenger, 2000. Journal of Coastal Research 16, 890-895.
Vousdoukas et al., 2018a Nature Climate Change 8: 776-780.
Vousdoukas et al., 2018b. Nature Communications 9: 2360.
Xie et al., 2019. Coastal Engineering 150: 39-58.
Zou et al., 2013. Q. J. R. Meteorol. Soc. 139: 298-313
For informal enquiries, or if you are interested in applying, contact Dr Carlos Loureiro (email@example.com)