Drone-based surveying of headwaters could bridge the gap between sparse field observations and model simulations to improve understanding of watershed runoff processes
River headwaters are vital for maintaining hydrological, biogeochemical and ecosystem integrity at regional scales. Comprising about 90% of stream length, headwater networks are sensitive to changes in climate and land use. Therefore, an understanding of headwater dynamics, particularly with regards to how and when areas connect and contribute hydrologically to streamflow, is paramount in an uncertain future climate. Yet, after decades of experimental and modelling research, scientific knowledge of the processes driving streamflow in headwaters across multiple time-space scales has important gaps.
Conventional technologies for monitoring stream networks include satellite-based remote sensing, which enables larger-scale observation but lacks the ability to map fine-scale headwater dynamics. Additionally, while ground-based thermal infrared imagery (TIR) can be used to quantify hydrological properties at a high spatial and temporal resolution, it has only a narrow spatial extent, and airborne TIR techniques are costly, mostly limited to the main river stem and cannot detect rapid changes. Now, two complementary technologies – drones and TIR – offer a way to gain greater understanding of headwater networks.
The research team from the UK (Stephen Dugdale and David Hannah) and Germany (Julian Klaus) discuss how drone-based TIR can leverage the full potential of existing technologies by providing high-resolution observations of headwater hydrological processes across multiple spatial and temporal scales. They go on to suggest that the combination of drone-based TIR with standard (red-green-blue, RGB) visible drone imagery could enable the extraction of hydrological networks at resolutions several orders of magnitude greater than existing LiDAR datasets, and note that drone-based TIR has the potential to bridge the gap between sparse field observations and model simulations.
The drone-based TIR approach has yet to be deployed widely, largely due to logistical considerations, such as the need to investigate its performance in different meteorological conditions, the impact of land cover on image performance, and the optimal spatio-temporal scales of data acquisition. Intensive field inspections are required to validate drone-based surveying – an essential step towards the technology gaining acceptance in the hydrology community.
Sade Agard
DETAILS: Water Resour. Res. 58, 2 e2021WR031168 (2022); https://doi.org/10.1029/2021WR031168
