PhD Studentship: HInterMap Drone-based Mapping to Improve Monitoring and Understanding of Headwater and Intermittent Streams

Intermittent streams (c. 50% of world rivers) and headwaters (c. 90% of rivers) are key riverine systems for hydrology, ecology and water quality, which are poorly monitored and lack data (Dugdale et al. 2022; Mainstone et al. 2018; Datry et al. 2016). Streams are often flagged as intermittent based on downstream flows, but where or how they dry is not known. Capturing the evolution of river habitat and connectivity as streams dry out is particularly important (Dugdale et al. 2022) for process hydrology, river ecology (e.g. refugia during drought, loss of physical in-channel habitat, loss of longitudinal connectivity, loss of lateral connectivity with riparian area, floodplain and wetlands), and water quality (pools are considered to favour algae blooms). Unpiloted Aerial Vehicles (UAVs), more commonly called drones, are a potential way to address these issues (Kelleher et al. 2016). River habitat monitoring can also benefit from using UAV data, which can provide fast higher resolution updates than traditional techniques. Figure 1 shows an example of mapping an intermittent chalk river in the UK. This research is relevant to other water-dependent systems faced with similar issues (e.g. wetlands) and could complement research on UAV-based water quality surveys in larger rivers. Beyond the riverine environment, the project would also explore potential to link with terrestrial UAV applications (e.g. biodiversity).

While the primary focus of this project in on headwaters and intermittent streams, the techniques and approaches developed by the student could be explored within the context of other river types or topics (e.g. thermal regime of contrasting river typologies or of groundwater-fed systems, mapping thermal refugia, longitudinal temperature change).

For further information on this project and details of how to apply, please click on the 'Apply' button above.

Further information on how to apply for a CENTA studentship can be found on the CENTA website: https://centa.ac.uk/apply/

Please be aware that the successful applicant for this project would be registered at the University of Birmingham but would be based with the UK Centre for Ecology and Hydrology,

Funding notes:

This project is offered through the CENTA3 DLA, funded by the Natural Environment Research Council (NERC). Funding covers: annual stipend, tuition fees (at home-fee level), Research Training Support Grant.

Academic requirements: at least a 2:1 at UK BSc level or a pass at UK MSc level or equivalent.

International students are eligible for studentships to a maximum of 30% of the cohort. Funding does not cover any additional costs relating to moving or residing in the UK. International applicants must fulfil the University of Birmingham’s international student entry requirements, including English language.  Further information: https://www.birmingham.ac.uk/postgraduate/pgt/requirements-pgt/international/index.aspx.

References:

Carbonneau et al (2020) ‘UAV-based training for fully fuzzy classification of Sentinel-2 fluvial scenes’. Earth Surf. Process. Landforms, 45, 3120–3140.

Carbonneau et al 2020) ‘Adopting deep learning methods for airborne RGB fluvial scene classification’. Remote Sensing of Environment, 251.

Datry et al (2016) ‘One for all, all for one: A global river research network’, Eos, 97, https://doi.org/10.1029/2016EO053587.

Dugdale et al (2022) ‘Looking to the skies: Realizing the combined potential of drones and thermal infrared imagery to advance hydrological process understanding in headwaters’. Water Res Research, 58.

Kelleher et al (2018) ’Drones in geoscience research: The sky is the only limit’, Eos, 99, https://doi.org/10.1029/2018EO092269.

Mainstone, C. et al. (2018) Developing a coherent framework for assessing priority freshwater habitats in England. Natural England JP016.

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