Vegetated foreshores are increasingly applied as nature-based flood defence measures, yet field evidence quantifying wave attenuation capacity of structurally diverse natural forests under flood conditions remains limited. Furthermore, complex vegetation structure is often overly simplified in spectral wave models.

This study investigates how diverse floodplain forest structure governs wave attenuation and evaluates Terrestrial Laser Scanning (TLS) as a method for deriving vegetation structural parameters across contrasting forest stands. The performance of TLS was evaluated using a reliability framework that defined the maximum distance over which vegetation structure could reliably be extracted from the point clouds.

Within this reliable domain, frontal surface area profiles (a(z)) were reconstructed and implemented in the phase-averaged wave model SWAN to simulate wave attenuation under varying water levels and wave forcing. Attenuation was governed by the interaction between submerged vegetation structure (a(z) Cd(z)) and wave orbital velocities (u(z)), resulting in dissipation proportional to a(z) Cd(z) u(z)³.

Pioneer and managed stands were characterised by concentrated low vegetation structure, limited horizontal patchiness, and structurally similar trees. Under moderate inundation conditions (1.6–4.0 m water depth above the forest floor), these stands produced the strongest wave attenuation with the smallest range of outcomes, with a median of approximately 40% and an interquartile range of 25–55% for a forest width of 100 m.

Late-successional stands, in contrast, were characterised by vertically distributed vegetation structure, pronounced horizontal patchiness, and structurally complex, diverse trees. Under the same conditions, these stands produced lower and more variable attenuation, with a median of approximately 20% and an interquartile range of 5–55%.

These results indicate that vertical vegetation structure primarily controls the magnitude of wave attenuation, whereas horizontal patchiness governs the variability of attenuation within forest stands. However, attenuation varied across hydraulic conditions and vegetation types, indicating that wave attenuation is not a fixed property of forest structure.

Compared to overly simplified, vertically uniform vegetation representations, TLS-derived a(z) profiles improved structural realism and captured depth-dependent attenuation behaviour. By linking high-resolution TLS-derived vegetation structure to wave modelling, this study provides a quantitative framework for evaluating structurally diverse floodplain forests as nature-based flood defences.

This multidisciplinary project, undertaken in collaboration with Community Cloud Forest Conservation (CCFC) in Alta Verapaz, Guatemala, addresses the need for long-term meteorological and hydrological monitoring in the Mestelá River catchment. The tropical montane cloud forest in this region provides essential ecosystem services through canopy cloud water interception and regulation of streamflow, yet continuous, high-quality environmental data remain limited.

To support research and conservation efforts, a 13.5 m scaffolding tower was designed and constructed as a durable, safe, and adaptable measurement platform, engineered for future extension to 25 m. The structural design accounted for local wind loads, dynamic forces, foundation stability, and corrosion resistance, ensuring a projected operational lifespan of 15 years.

Beyond infrastructure, the project developed a hydrological monitoring set-up and a Python-based modelling framework to quantify the canopy water balance and hydrological cycle. Sensor selection, placement, and integration were tailored to capture key meteorological and hydrological variables, including rainfall, fog interception, throughfall, and soil moisture. Data acquisition and storage were configured to function as autonomously as possible under remote, high-humidity cloud forest conditions, while allowing for straightforward periodic maintenance of all components involved.

Recognising that sustainability extends beyond technical performance, the project incorporated cultural and institutional engagement. Workshops and collaborative activities with CCFC staff and local stakeholders were conducted to align the monitoring system with community values, build operational capacity, and foster local ownership. A comprehensive maintenance strategy and guidelines for potential expansion were developed to ensure the continued relevance and adaptability of the system, including options for biodiversity monitoring and additional research applications.

The resulting monitoring platform combines robust engineering, scientific instrumentation, and community integration. It establishes a foundation for long-term data collection that can inform hydrological modelling, climate adaptation strategies, and evidence-based conservation, while embedding the system within the local social and ecological context.