As part of the PRA project "EcoClimate," coordinated by the Gruppo di Ecologia trofica of Sapienza's Department of Environmental Biology in collaboration with the Consiglio nazionale delle ricerche - Istituto di ricerca sulle acque (CNR-IRSA, Rome) and Istituto di scienze polari (CNR-ISP, Messina and Rome), a hydrographic drone, specially configured for work at extreme latitudes, was used for the first time to obtain very high-resolution 2D and 3D bathymetry of lake basins in the Svalbard Islands in the Arctic Circle. The acquired data will allow the researchers to calculate with unprecedented accuracy the water volumes, and turnover times of Arctic lakes and predict their evolution according to the expected environmental conditions in the region for the near future.

"The drone used was designed and adapted precisely for this purpose: small, lightweight and easily transportable - says David Rossi (CNR-IRSA), head of the experiment. It allowed us to reach lakes at the foot of glaciers that had never been mapped before. The results obtained and volumetric calculations of the lakes will, then, be correlated with ecological data to obtain unique information on these delicate aquatic ecosystems."

"Although the use of drones is becoming commonplace in polar research activities, this is the first time a hydrographic drone has been used on land to study Arctic lake ecosystems," adds Eoardo Calizza (Sapienza University of Rome), project coordinator. " This is part of the highly interdisciplinary approach that characterises the PRA project 'EcoClimate': the aim is to understand how climate change will affect the structure and functioning of these delicate ecosystems, which are considered biodiversity hotspots and carbon sinks at the highest latitudes."

The tests were made possible by specially-made instrumentation provided and configured by Seafloor System Inc. for the portable hydrographic drone and the Italian company Microgeo for the Global Navigation Satellite System (GNSS) antenna. Data acquired through the newly tested technology will be combined with ecological data to reconstruct trophic networks, microbiological data to study lake metabolism, satellite images and field radiometric measurements to study snow and vegetation dynamics.