Influence of Vegetation Dynamics on Hydrological and Carbon Responses under Future Climate Scenarios Using SWAT-C

Accurate representation of vegetation dynamics is critical for hydrological modeling and climate change impact assessments. Leaf Area Index (LAI) influences ecohydrological processes, including evapotranspiration, interception, and soil moisture. The conventional Soil and Water Assessment Tool Carbon (SWAT-C) model has a simplified vegetation growth module, which limits the accuracy of the model in decision making. The present study evaluates how improved simulation of LAI affects ecohydrological responses of a watershed under historical and future climate scenarios. The study employed setting up of two models: original SWAT-C as a baseline model, and a modified version of the SWAT-C model with an improved plant growth module to simulate LAI more realistically in forested areas. Both models were calibrated using streamflow, evapotranspiration, and sediment yield using A Multi Algorithm Genetically Adaptive Multiobjective (AMALGAM) optimizer. The climate projections from different bias corrected global circulation models were applied to understand the sensitivity of ecohydrological simulations of streamflow, evapotranspiration, sediment yield, net primary productivity (NPP), biomass, net ecosystem exchange (NEE), soil organic carbon (SOC), and lateral carbon fluxes to vegetation-driven changes in LAI. The differences in the future climate scenarios highlights the influence of vegetation feedbacks on projected hydrological responses and carbon dynamics. This approach provides better insight into vegetation–water–carbon interactions and can support improved strategies for managing water and ecosystem resources under changing climate conditions.