Evaluating hydrological model structure using tracer data within a multi-model framework Hilary McMillan 1, Doerthe Tetzlaff 2, Martyn Clark 3, Chris Soulsby.

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Evaluating hydrological model structure using tracer data within a multi-model framework Hilary McMillan 1, Doerthe Tetzlaff 2, Martyn Clark 3, Chris Soulsby 2 1 National Institute of Water and Atmospheric Research, New Zealand. 2 School of Geosciences, University of Aberdeen 3 National Centre for Atmospheric Research, Boulder, Colorado Aims 1. Use tracer data to choose between model structures with similar dynamics 2. Show how tracer response is affected by interaction of model structure, parameters and mixing assumptions Case Study: Loch Ard, Scotland Water-Tracking Method FUSE multi-model framework was modified to track distributions of water age in each store and flux. Outflow age distributions, transit time distributions and tracer dynamics can be derived. Results Differences in tracer response could be explained by differences in model transit time distribution Model ‘virtual experiments’ allow transit time behaviour to be explored We tested which transit time characteristics lead to good model performance At Loch Ard a FUSE model could be designed which simulated both runoff and tracer dynamics Key choices were a structure with single upper zone variable and Topmodel lower zone architecture Tracer SimulationSeasonalitySensitivity Structure vs Calibration Some parameters (e.g. upper soil zone depth) control transit times equally with model structure Transit Time Simulation Model simulates flow but not tracers Model simulates flow and tracers Models which perform well have strong seasonal variation in MTT Transit time distributions for fast flow pathways ( 30 days, seasonality is less important. Mixing Assumptions Does saturation excess flow mix with soil water? Flow partitioning between surface and soil water was found to have only a small effect on transit times so the simplifying assumption of no mixing was acceptable But very different model structures can produce similar hydrographs pe ep To choose between model structures we use diagnostic tests which target individual model components using data types such as flow, soil moisture, and here tracers Models with physically realistic structures are needed to produce good forecasts under a wide range of conditions FUSE (Framework for Understanding Structural Errors) allows modular testing of popular hydrological model components Definitions: Transit Time Distribution (TTD) Histogram of time taken for water to exit the catchment, i.e. the breakthrough curve Mean Transit Time (MTT) Mean of the Transit Time Distribution 12 years of data was used: rainfall, flow and weekly samples of chloride. Chloride in rainfall originates from sea-salt and the concentration varies seasonally due to wind speed and direction -- The story -- Loch Ard Burn 10 is a small (0.9km 2 ) catchment forested with Sitka spruce. Soils are poorly drained gleys and storm runoff is dominated by the upper soil horizons. Tree roots and exposed bedrock allow deeper recharge. Contact: Model is more sensitive to store depth when store response is more nonlinear High MTT in summer Low MTT in winter Models with single upper zone variable Time-varying Mean Transit Times Time (days) Flow (mm) Linear Tank 2 Linear Tanks Topmodel Measured Flow Time Flow (mm) Time Less mixing Time (days) TTD with variable mixing More mixing Frequency i i i D Transit Time Distributions Vary Lower Zone Size Vary Upper Zone Size Nash Score Lower Zone Size (mm)Upper Zone Size (mm) Frequency Time (days) Rain (mm) Flow (mm) Chloride (mg/L) Modelled tracer series Models with split upper zone variables Chloride (mg/L) Date Steady state transit time distributions Frequency Baseflow only Time (days) All flow Seasonal Transit Time Distributions % of flow Less mixing More mixing Loch Ard Catchment H31F-1227