DYCOVE: A Python package for coupling dynamic vegetation processes with hydro-morphodynamic models

Vegetation growth in coastal environments plays an important role in shaping coastal morphology (Kirwan et al., 2016; Kleinhans et al., 2018; Mariotti & Fagherazzi, 2010; Schwarz et al., 2018; Temmerman et al., 2005, 2007). Hydrodynamic and morphodynamic (numerical) models are used widely for understanding the processes that impact coastal systems, and they inform management strategies for coastal protection and ecosystem preservation. In these models, vegetation effects are incorporated via friction, with increasing roughness effects for taller and denser vegetation that alters flow velocities and sediment transport. However, roughness is commonly assumed as being constant, a key limitation as vegetation is not static in space and time: processes such as colonization, growth, mortality and species interactions determine dynamic patterns of biomass that depend on environmental conditions. As a result, dynamic vegetation representations are necessary to determine their interactions with local hydrodynamics and morphodynamics in numerical models. This work presents an open-source Python modeling framework DYCOVE (DYnamic COastal VEgetation) that is dynamically coupled with the numerical models Delft3D Flexible Mesh (DFM) and ANUGA, with capabilities to be expanded to other models. DYCOVE represents life-cycle dynamics of multiple vegetation species in coastal environments through detailed ecological processes that are functions of environmental conditions, resulting in spatial and temporal updates of friction effects in the numerical model. The model reproduces realistic vegetation patterns and roughness distributions, a prerequisite to test how vegetation complexity affects hydro-morphodynamics in coastal systems. DYCOVE is designed to prioritize straightforward modeling of coastal vegetation dynamics, accessibility for all user levels, and smooth implementation of additional ecological and biological processes relevant to the study of biophysical interactions.