Publications

Karki, R; Qi, J; Gonzalez-Benecke, CA; Zhang, X; Martin, TA; Arnold, JG (2023). SWAT-3PG: Improving forest growth simulation with a process-based forest model in SWAT. ENVIRONMENTAL MODELLING & SOFTWARE, 164, 105705.

Abstract
This study developed a new process-based forest module for the Soil and Water Assessment Tool (SWAT), based on the Physiological Process in Predicting Growth (3-PG) model (SWAT-3PG). The new model allows for improved biomass assimilation, partitioning (stem, foliage, root), and losses (root turnover, foliage loss, mortality). Evaluation at field-scale showed that SWAT-3PG can replicate the different forest biomass components for evergreen forests well. Testing for deciduous and mixed forests sites using remote-sensed data showed that the model can simulate leaf area index (LAI), net primary productivity (NPP) and actual evapotranspiration (AET) reasonably well and can be used to constrain SWAT-3PG when lack of field data. Sensitivity analysis of SWAT3PG showed its potential in evaluating the impacts of management and climate on forested ecosystems. SWAT3PG can also be of importance to forest managers as it can estimate variables such as plant height, diameter at breast height (DBH), and basal area.

DOI:
10.1016/j.envsoft.2023.105705

ISSN:
1873-6726