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The Impact of Asynchronicity on Event‐Flow Estimation in Basin‐Scale Hydrologic Model Calibration1
Authors:John F Joseph  Hatim O Sharif  Jeffrey G Arnold  David D Bosch
Institution:1. Respectively, Research Associate (Joseph) and Associate Professor (Sharif), One UTSA Circle, Department of Civil and Environmental Engineering, University of Texas at San Antonio, Texas 78249;2. Supervisory Agricultural Engineer (Arnold), Grassland Soil and Water Research Laboratory, Temple, Texas 76502;3. Research Hydraulic Engineer (Bosch), Southeast Watershed Research, Tifton, Georgia 31793
Abstract:Abstract: The calibration of basin‐scale hydrologic models consists of adjusting parameters such that simulated values closely match observed values. However, due to inevitable inaccuracies in models and model inputs, simulated response hydrographs for multiyear calibrations will not be perfectly synchronized with observed response hydrographs at the daily time step. An analytically derived formula suggests that when timing errors are significant, traditional calibration approaches may generally underestimate the total event‐flow volume. An event‐adaptive time series is developed and incorporated into the Nash‐Sutcliffe Efficiency objective function to diagnose the potential impact of event‐flow synchronization errors. Test sites are the 50 km2 Subwatershed I of the Little River Experimental Watershed (LREWswI) in southeastern Georgia, and the 610 km2 Little Washita River Experimental Watershed (LWREW) in southwestern Oklahoma, with the Soil and Water Assessment Tool used as the hydrologic model. Results suggest that simulated surface runoff generation is 55% less for LREWswI when the daily time series is used compared with when the event‐adaptive technique is used. Event‐flow generation may also be underestimated for LWREW, but to a lesser extent than it may be for LREWswI, due to a larger portion of the event flow being lateral flow.
Keywords:rivers/streams  watersheds  runoff  surface water hydrology  nonlinear dynamics  uncertainty analysis  computational methods
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