Evidence Based Hydraulic and Geomorphic Complexity of Large Wood Interventions for Habitat Creation

Large wood (LW) has become an essential tool in river restoration due to its ability to enhance habitat heterogeneity and restore natural processes disrupted by human activities such as channelisation.  This work presents findings from 2-year field monitoring across 4 restoration sites in the UK, aimed at quantifying the effects of various LW interventions on geomorphic changes and hydraulic complexity.

The sites including in our monitoring have been selected for the diverse type of interventions, catchment type (ranging from stream orders 3rd to 6th), and LW complexity that has been used for restoration, for example, Stage-0 (Holnicote, Somerset, UK and Tattiscombe, Devon, UK), complex dams and deflectors (Magdalen Farm, Somerset, UK), simple deflectors (Mosterton, Somerset). The monitoring process encompassed the quantification of surface velocity variations around LW installations through a drone-based large scale particle image velocimetry (LSPIV) method coupled with the structural complexity and type of LW, and measurement of LW-induced geomorphic changes using high-resolution RTK drone surveys and walk-overs using Leica GNSS unite. To identify the impact of LW on restoration, we employed a control (unwooded) versus impact (restored) design for Magdalen and Mosterton farms combined with a before‑and‑after monitoring approach for Holnicote and Tattiscombe.

For the first objective, LSPIV was employed to acquire spatially continuous velocity fields across selected rivers reaches within the sites, mitigating the methodological limitations of traditional point-measurement techniques near complex LW structures. LSPIV surveys were conducted during contrasting low (Q₉₀-Q₉₉) and high (Q₁₀-Q₄) flow conditions at intervention and upstream control reaches. Velocity analyses quantified spatial heterogeneity using coefficient of variation in velocity, revealing consistent formation of distinct wake zones (reduced velocity) and acceleration zones near wood features. For example, in LW jams in Mosterton, a cross-section with 33.34% wood cover exhibited a velocity coefficient of variation 195.82% higher than the control reach (unwooded), with P value equal to 3.9×10⁻⁴⁴ (Wilcoxon test) confirming that LW significantly drives flow variability. The observed hydraulic heterogeneity defines three functional zones: high‑energy, erosion‑ or scour‑prone reaches; low‑energy, depositional zones; and intermediate turbulent‑mixing areas. By overlaying these flow‑zone maps onto concurrent drone‑derived orthophotos, we can relate flow patterns to specific geomorphic responses such as pool development, bar migration, or bank erosion. This will allow us to predict where erosional and depositional processes are most likely to occur under different LW configurations and flow conditions.