Resumen
Geotechnical data are increasingly utilized to aid investigations of coastal erosion and the development of coastal morphological models; however, measurement techniques are still challenged by environmental conditions and accessibility in coastal areas, and particularly, by nearshore conditions. These challenges are exacerbated for Arctic coastal environments. This article reviews existing and emerging data collection methods in the context of geotechnical investigations of Arctic coastal erosion and nearshore change. Specifically, the use of cone penetration testing (CPT), which can provide key data for the mapping of soil and ice layers as well as for the assessment of slope and block failures, and the use of free-fall penetrometers (FFPs) for rapid mapping of seabed surface conditions, are discussed. Because of limitations in the spatial coverage and number of available in situ point measurements by penetrometers, data fusion with geophysical and remotely sensed data is considered. Offshore and nearshore, the combination of acoustic surveying with geotechnical testing can optimize large-scale seabed characterization, while onshore most recent developments in satellite-based and unmanned-aerial-vehicle-based data collection offer new opportunities to enhance spatial coverage and collect information on bathymetry and topography, amongst others. Emphasis is given to easily deployable and rugged techniques and strategies that can offer near-term opportunities to fill current gaps in data availability. This review suggests that data fusion of geotechnical in situ testing, using CPT to provide soil information at deeper depths and even in the presence of ice and using FFPs to offer rapid and large-coverage geotechnical testing of surface sediments (i.e., in the upper tens of centimeters to meters of sediment depth), combined with acoustic seabed surveying and emerging remote sensing tools, has the potential to provide essential data to improve the prediction of Arctic coastal erosion, particularly where climate-driven changes in soil conditions may bias the use of historic observations of erosion for future prediction.