Forested watersheds provide important ecosystem services through the provision of high quality freshwater, mitigation of floods, and maintenance of base flows. How alteration of these services under ongoing climate change is mediated by vegetation dynamics is not fully understood. Combining independent remote sensing based vegetation information and distributed hydrological modeling, we investigated the impact of climate‐induced vegetation dynamics on long‐term non‐stationary hydrologic behavior in two forested watersheds in the southern Appalachians. We found significant increases in precipitation‐runoff deficit (defined as annual precipitation minus annual runoff), equivalent to annual evapotranspiration plus storage changes, over the last three decades. This non‐stationary hydrologic behavior was significantly correlated with long‐term and interannual changes in growing season length and subsequent vegetation growth. These patterns in vegetation phenology were attributed primarily to minimum temperature regimes, which showed steeper and more consistent increases than temperature maxima. Using a distributed modeling framework, we also found that the long‐term non‐stationary hydrologic behavior could not be simulated unless full vegetation dynamics, including vegetation phenology and long‐term growth, were incorporated into the model. Incorporating seasonal vegetation dynamics also led to the improved simulation in streamflow dynamics, while its effect spread out through the following dormant seasons. Our study indicates that non‐stationary hydrologic behavior has been closely mediated by long‐term seasonal and structural forest canopy interaction with climate variables rather than directly driven by climatic variables. This study emphasizes the importance of understanding the ecosystem responses to ongoing climate change for predictions of future freshwater regimes.

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Human population growth and urban development are affecting climate, land use, and the ecosystem services provided to society, including the supply of freshwater. We investigated the effects of land use and climate change on water resources in the Yadkin-Pee Dee River Basin of North Carolina, United States. Current and projected land uses were modeled at high resolution for three watersheds representing a forested to urban land use gradient by melding the National Land Cover Dataset with data from the U.S. Forest Service Forest Inventory and Analysis. Forecasts for 2051-2060 of regional land use and climate for scenarios of low (B2) and moderately high (A1B) rates of change, coupled with multiple global circulation models (MIROC, CSIRO, and Hadley), were used to inform a distributed ecohydrological model.Our results identified increases in water yields across the study watersheds, primarily due to forecasts of increased precipitation. Climate change was a more dominant factor for future water yield relative to land use change across all land uses (forested, urban, and mixed). When land use change was high (27% of forested land use was converted to urban development), it amplified the impacts of climate change on both the magnitude and timing of water yield.Our fine-scale (30-m) distributed combined modeling approach of land use and climate change identified changes in watershed hydrology at scales relevant for management, emphasizing the need for modeling efforts that integrate the effects of biophysical (climate) and social economic (land use) changes on the projection of future water resource scenarios.

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