Quantifying riparian vegetation dynamics and flow interactions for Nature Based Solutions using novel environmental sensing techniques.

Associate Professor Julian Leyland, UoS; Professor Stephen Darby, UoS

This project aims to deliver a step-change in our understanding of vegetation and flow interactions in river corridors, with an emphasis on creating a baseline for Nature Based Solution approaches to sustainable river management.


Vegetation, and Large Woody Debris (LWD) specifically, has a significant effect on river flows, channel morphology and carbon storage. These interactions are conceptually well understood: the flow resistance introduced by the presence of vegetation and LWD leads to changes in flow which modulate water and sediment transport resulting in changes in river form and flooding. Similarly, these water-vegetation interactions control carbon storage and sequestration in the riparian zone. Yet, attempts to quantify the flow-vegetation dynamics, for example in numerical models, remain elusive due to difficulties in accurately estimating the complex interactions through time. This represents a major limitation as vegetation is ubiquitous in natural river corridors and is often used as part of Nature Based Solutions to flood management and in river restoration schemes. This project will address these knowledge gaps using state-of-the-art environmental sensing techniques and a vegetation functional groups framework in conjunction with spatial ecological techniques to deliver a data-driven model of river corridor vegetation-flow functioning.



A key challenge in quantifying vegetation-flow interactions (essentially vegetative roughness) is the inherent structural complexity and large spatial extent of vegetation. This project will employ novel high-resolution surveying techniques [1, 2] to characterise the 3D structure of debris dams. Specifically, the student will deploy Southampton’s Terrestrial Laser Scanners (TLS) and UAV based Laser Scanners to evaluate the 3D structure of vegetation across a range of representative field sites. In addition, dye-dilution techniques will be used to estimate hydraulic roughness based on flow retardation using the Aggregated Dead Zone (ADZ) approach [3]. The resulting data sets will be synthesised to provide a novel physically-based relationship between vegetation structure and resulting flow resistance, as well as estimates of plant functioning and biomass. UAVs and Structure from Motion (SfM) techniques will be used to assess reach-scale (and beyond) distributions of vegetation to allow upscaling of the findings from the high-resolution techniques, with key applications to Nature Based Solutions approaches to Natural Flood Management and river restoration generally.


University of Southampton, Highfield Campus

The INSPIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered at the University of Southampton and hosted within the School of Geography and Environmental Science at Highfield Campus. Opportunities are available for the student to engage with key applied and research stakeholders via our excellent links, including with the Environment Agency. The supervisors are experts in the field of fluvial geomorphology and high-resolution survey techniques, as well as applied spatial ecology. Full training will be provided in relevant measurement, monitoring, remote sensing and statistical techniques.

Eligibility & Funding Details: 

Please see https://inspire-dtp.ac.uk/how-apply for details.


Background Reading: 


[1] Leyland, J., Hackney, C.R., Darby, S.E., Parsons, D.R., Best, J.L., Nicholas, A.P., Aalto, R. and Lague, D., 2017. Extreme flood‐driven fluvial bank erosion and sediment loads: direct process measurements using integrated Mobile Laser Scanning (MLS) and hydro‐acoustic techniques. Earth Surface Processes and Landforms, 42(2), pp.334-346.


[2] Tomsett, C. and Leyland, J., 2021. Development and Testing of a UAV Laser Scanner and Multispectral Camera System for Eco-Geomorphic Applications. Sensors, 21(22), p.7719.


[3] Carling, P.A., Leyland, J., Kleinhans, M.G., Besozzi, L., Duranton, P., Trieu, H. and Teske, R., 2020. Quantifying fluid retention due to natural vegetation in a forest floodplain analogue using the aggregated dead zone (ADZ) dilution approach. Water Resources Research, 56(9), p.e2020WR027070.