Evolution of thermokarst in East Siberian ice-rich permafrost

Thermokarst lakes and basins are major components of ice-rich permafrost landscapes in East Siberian coastal lowlands and are regarded as indicators of regional climatic changes. We investigate the temporal and spatial dynamics of a 7.5 km**2, partly drained thermokarst basin (alas) using field investigations, remote sensing, Geographic Information Systems (GIS), and sediment analyses. The evolution of the thermokarst basin proceeded in two phases. The first phase started at the Pleistocene/Holocene transition (13 to 12 ka BP) with the initiation of a primary thermokarst lake on the Ice Complex surface. The lake expanded and persisted throughout the early Holocene before it drained abruptly about 5.7 ka BP, thereby creating a > 20 m deep alas with residual lakes. The second phase (5.7 ka BP to present) is characterized by alternating stages of lower and higher thermokarst intensity within the alas that were mainly controlled by local hydrological and relief conditions and accompanied by permafrost aggradation and degradation. It included diverse concurrent processes like lake expansion and stepwise drainage, polygonal ice-wedge growth, and the formation of drainage channels and a pingo, which occurred in different parts of the alas. This more dynamic thermokarst evolution resulted in a complex modern thermokarst landscape. However, on the regional scale, the changes during the second evolutionary phase after drainage of the initial thermokarst lakes were less intense than the early Holocene extensive thermokarst development in East Siberian coastal lowlands as a result of a significant regional change to warmer and wetter climate conditions.

GPS raw data (control points and ground control points) from the Liguria Region, Borghetto Santo Spirito, Italy

Monitoring the impact of sea storms on coastal areas is fundamental to study beach evolution and the vulnerability of low-lying coasts to erosion and flooding. Modelling wave runup on a beach is possible, but it requires accurate topographic data and model tuning, that can be done comparing observed and modeled runup. In this study we collected aerial photos using an Unmanned Aerial Vehicle after two different swells on the same study area. We merged the point cloud obtained with photogrammetry with multibeam data, in order to obtain a complete beach topography. Then, on each set of rectified and georeferenced UAV orthophotos, we identified the maximum wave runup for both events recognizing the wet area left by the waves. We then used our topography and numerical models to simulate the wave runup and compare the model results to observed values during the two events. Our results highlight the potential of the methodology presented, which integrates UAV platforms, photogrammetry and Geographic Information Systems to provide faster and cheaper information on beach topography and geomorphology compared with traditional techniques without losing in accuracy. We use the results obtained from this technique as a topographic base for a model that calculates runup for the two swells. The observed and modeled runups are consistent, and open new directions for future research.