Stochastic dynamics of coastal dune vegetation
- Carlo Camporeale,
- Melissa Latella
Carlo Camporeale
Politecnico di Torino Dipartimento di Ingegneria dell'Ambiente del Territorio e delle Infrastrutture
Corresponding Author:[email protected]
Author ProfileMelissa Latella
Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici
Author ProfileAbstract
This work introduces a physically-based model to capture the
spatio-temporal dynamics of dune vegetation under stochastic
environmental disturbances. In analogy with other transitional disturbed
environments, the model evaluates vegetation cover, within a cross-shore
dimensionless framework, in response to random wind speed and runup. The
wind speed is modeled as a compound Poisson process with
Gamma-distributed properties, facilitating the computation of
up-crossing times for various thresholds. The dune topography is
represented by a swash zone with a Gaussian shape and a monotonic
landward increase, parameterized by slope, wavelength, and height. Key
disturbance conditions affecting vegetation---runup-induced flooding in
the swash zone and wind-induced scour on the backshore and crest---are
addressed through threshold-based analysis. The model uses a
state-dependent dichotomic process for vegetation dynamics, where growth
and decay are influenced by external forcing and vegetation state.
Analytical solutions of the master equation for the vegetation
distributions reveal the impact of stochastic factors on vegetation
growth and stability. Sensitivity analysis identifies dune steepness,
forcing magnitude and variability, and relative roughness as critical
parameters. These factors significantly affect vegetation distribution,
with increased steepness leading to higher vegetation density at the
backshore and reduced density at the shorefront. Also, a Suitability
Index to assess analytically dune stability based on disturbance and
topographic features is introduced. Validation against satellite imagery
and high-resolution real elevation data from the U.S. coastline confirms
the model's robustness and accuracy. The results enhance understanding
of dune vegetation dynamics and offer a framework for coastal
restoration strategies.26 Sep 2024Submitted to ESS Open Archive 27 Sep 2024Published in ESS Open Archive