Forests play a significant role in the hydrological cycle by increasing water use through tree transpiration, reducing soil evaporation, providing local cooling, and altering soil hydrological properties. The nature of these interactions depends on individual tree species’ functional traits, intra- and interspecific interactions, and stand age. In the short term, individuals acclimate to local conditions by adjusting their photosynthetic activity in response to temperature and water availability. As such, over time, changes in forest cover, whether through afforestation or deforestation, will affect water availability in the forest and downstream. To simultaneously predict basin-level water and carbon dynamics, representations of vegetation in hydrological models must capture processes such as soil-water-plant interactions, plant acclimation, forest dynamics, and diversity in forest age and species composition.</p> <p>In this paper we advanced the capability of the Geographical Environmental and Behavioural model (GEB), a hydrological model with agent-based representations of management decisions, by coupling it with the Plant Functional Acclimation and Trait Evolution model (PlantFATE), a dynamic trait-based vegetation model built on eco-evolutionary principles, to improve hydrological response to changes in forest cover and composition. We evaluated the coupling against the default GEB model outputs by simulating a portion of the Ghod Sub-basin in Maharashtra, India. We further explored various afforestation scenarios using the GEB-PlantFATE coupling with two levels of tree species diversity as represented by species richness (low and high biodiversity scenarios with 1 and 10 species, respectively).</p> <p>We show that GEB-PlantFATE significantly improved the representation of feedbacks between the forests and hydrology with respect to the individual models alone. Our results show that the coupled model is able to better represent the changing species composition, NPP and size distribution under a changing hydrological and climatological environment, and the feedback from drought-adapted forest species to soil moisture. Forests simulated in GEB-PlantFATE could maintain photosynthesis under lower soil water content with respect to GEB only, and optimise photosynthesis better when higher water content was available. Accordingly, we found two relatively high-water tolerant species as being the most successful in the high biodiversity scenarios. Finally, afforestation generally increased soil water content, with high biodiversity having a larger effect, likely due toindividual trees size. Overall, differences in NPP and transpiration rate between the high and low biodiversity scenarios could be primarily attributed to the faster growth rate of the low biodiversity species. The coupling represents a first step towards investigating forest biodiversity and eco-hydrological interactions in a hydrological model. We demonstrate the coupling on a relatively small basin, but the model can be applied to other regions to evaluate trade-offs between afforestation, forest use, and other water demands. This work indicates the potential that the coupled GEB-PlantFATE can more accurately simulate the advantages and disadvantages of afforestation, and the impact of climate change on the ecohydrological system.