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Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations
Citation:
Mahoney, D., J. Christensen, H. Golden, C. Lane, G. Evenson, E. White, K. Fritz, E. D'Amico, C. Barton, T. Williamson, K. Sena, AND C. Agouridis. Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations. JOURNAL OF HYDROLOGY. Elsevier Science Ltd, New York, NY, 620(A):129422, (2023). https://doi.org/10.1016/j.jhydrol.2023.129422
Impact/Purpose:
The objective of this study was to develop a process-based, catchment-scale hydrologic model to improve understanding of the spatiotemporal dynamics of headwater streamflow permanence and controls of headwater network streamflow expansion and contraction. Our model suggested that streamflow permanence is highly dynamic in first order reaches with steep slopes and variable contributing areas. The stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model suggests that above a discharge threshold of approximately 1 mm d-1, the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights to the controls of streamflow permanence. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.
Description:
The hillslope and channel dynamics that govern streamflow permanence in headwater systems have important implications for ecosystem functioning and downstream water quality. Recent advancements in process-based, semi-distributed hydrologic models that build upon empirical studies of streamflow permanence in well-monitored headwater catchments show promise for characterizing the dynamics of streamflow permanence in headwater systems. However, few process-based models consider the continuum of hillslope-stream network connectivity as a control on streamflow permanence in headwater systems. The objective of this study was to expand a process-based, catchment-scale hydrologic model to better understand the spatiotemporal dynamics of headwater streamflow permanence and to identify controls of streamflow expansion and contraction in a headwater network. Further, we aimed to develop an approach that enhanced the fidelity of model simulations, yet required little additional data, with the intent that the model might be later transferred to catchments with limited long-term and spatially explicit measurements. This approach facilitated network-scale estimates of the controls of streamflow expansion and contraction, albeit with higher degrees of uncertainty in individual reaches due to data constraints. Our model simulated that streamflow permanence was highly dynamic in first-order reaches with steep slopes and variable contributing areas. The simulated stream network length ranged from nearly 98±2% of the geomorphic channel extent during wet periods to nearly 50±10% during dry periods. The model identified a discharge threshold of approximately 1 mm d−1, above which the rate of streamflow expansion decreases by nearly an order of magnitude, indicating a lack of sensitivity of streamflow expansion to hydrologic forcing during high-flow periods. Overall, we demonstrate that process-based, catchment-scale models offer important insights on the controls of streamflow permanence, despite uncertainties and limitations of the model. We encourage researchers to increase data collection efforts and develop benchmarks to better evaluate such models.
URLs/Downloads:
DOI: Dynamics of streamflow permanence in a headwater network: Insights from catchment-scale model simulations