Improving SWAT-C simulation of terrestrial carbon using a new forestry module: A case study in the St. Croix River Basin

Forests play an integral role in the terrestrial ecosystem, especially carbon cycling, as it dominates carbon exchange due to its high carbon sequestration potential as well as high biomass density. As a result, tracking forest biomass, carbon storage, and exchange is vital to the efforts of carbon monitoring as well as climate mitigation policies. Although there have been multiple efforts to estimate forest biomass and carbon storage at a single snapshot in time, there is a need for tracking the temporal changes at regional and global scales. Understanding the temporal variability in terrestrial carbon fluxes is also critical to accurately estimating carbon in aquatic systems. This study evaluated the capability of the SWAT-Carbon (SWAT-C) model to capture the spatial and temporal variability in estimating forest biomass, carbon storage, and net primary productivity (NPP) after incorporating a new forestry module based on 3PG, a forest growth model. The new forestry module expands on the limited capabilities of the default forest module in SWAT-C and allows for improved forest biomass assimilation, partitioning, LAI estimation based on foliage biomass, and losses from litterfall that can be varied according to the plant functional type. The model was evaluated by performing a case study in the St. Croix River Basin and publicly available remote sensed data products as well as snapshot datasets of biomass and carbon were used to initialize the forest biomass and age as well as constrain and calibrate the model for forest biomass and carbon simulation. The calibrated model was then used to estimate annual forest biomass and carbon at HUC-12 level for the study watershed from 2000 to 2020. This study demonstrates the potential of the modified SWAT-C model as an effective tool for estimating terrestrial forest biomass and carbon storage at regional scale.