Enhancing forest ecosystem simulation in the TASC model through the integration of the DAYCENT forest model

Abstract

Forest ecosystems play a crucial role in sequestering atmospheric carbon in the form of biomass and soil organic carbon, while also providing high quality water supply through water and nutrient cycling. The lack of state-of-the-art forest growth processes in the Terrestrial and Aquatic Sciences Convergence (TASC) model limits its capability to support watershed management in forested watersheds. To address this gap, we integrated the DAYCENT model-based forest growth algorithms into the TASC model (TASC-Forest) to provide detailed representation of forest growth dynamics, such as biomass production, allocation, death, and decomposition of leaf litter, root, and woody components. We optimized parameters related to tree growth, soil properties, and hydrologic processes, and evaluated the improved model's ability to simulate monthly net ecosystem exchange (NEE), ecosystem respiration, and evapotranspiration (ET) observed at seven AmeriFlux sites. The results show that the TASC-Forest generally performs well in simulating NEE, ecosystem respiration, and ET across multiple forest biomes: deciduous, evergreen, and mixed. The TASC-Forest substantially outperformed the TASC model in simulating NEE and ET. The KGE values increased from 0.61 and 0.48 to 0.82 and 0.76 for NEE, and from 0.56 and 0.48 to 0.84 and 0.80 for ET during calibration and validation, respectively, across seven forest sites. Sensitivity analysis indicates that forest productivity and ET are most sensitive to parameters regulating temperature and soil moisture effects on tree growth, and soil moisture control parameters. The enhanced TASC model will serve as a valuable tool for the integrated assessment and management of carbon, nutrient, and water cycling, particularly in forested ecosystems.