1. Parameterisation by combination of different levels of process-based model physical complexity John Pomeroy 1, Olga Semenova 2,3, Lyudmila Lebedeva 2,4 and Xing Fang 1 1 Centre for Hydrology, University of Saskatchewan, Saskatoon, Canada 2 Hydrograph Model Research Group, www.hydrograph-model.ru 3 State Hydrological Institute, Saint Petersburg, Russia 4 Saint Petersburg State University, Russia

2. Levels of physical complexity in hydrological models Subsurface Surface Physically-basedConceptual + + Is the process basis suitable to data availability?

3. Initially planned activities * * * * * 1)Refine and confirm parameterisation of a physically- based model describing surface and near-surface processes at small- scale research basin 2) Use modelled outcomes to estimate the parameters of more conceptual process-based model 3) Apply the process-based model in larger scale where data availability is sparser

4. Study area Yukon River at Eagle, 345 000 km 2 Wolf Creek Research Basin, 195 km 2 Grangerwatershed, 8 km 2 * *

5. Similar principles of model development The Cold Regions Hydrological Model (CRHM), Canada Hydrograph Model, Russia is distributed such that the water balance for selected surface areas can be computed; is sensitive to the impacts of land use and climate change; does not require the presence of a stream in each land unit; is flexible: can be compiled in various forms for specific needs; is suitable for testing individual process algorithms. DOES NOT REQUIRE CALIBRATION Single model structure for watersheds of any scale Adequacy to natural processes while looking for the simplest solutions Use of physically- observable parameters MINIMUM OF MANUAL CALIBRATION

6. Processes Both models: precipitation, temperature, relative humidity, solar radiation CRHM: wind speed Infiltration into soils (frozen and unfrozen) Snowmelt (prairie & forest) Radiation Evapotranspiration Wind flow over hills Snow transport Interception (snow & rain) Sublimation (dynamic & static) Soil moisture balance Runoff, interflow Routing (hillslope & channel) Forcing data Hydrograph CRHM

7. Spatial variability of snow accumulation due to redistribution by blowing snow Infiltration of snowmelt water into frozen soils Actual evapotranspiration rates from different landscapes Common Processes of the Hydrograph and CRHM models

8. Spatial variability of snow cover physically-based two-dimensional blowing snow transport and sublimation model statistical accounting for snow redistribution at the moment of snowfall HydrographCRHM CRHM simulated variability of snow cover over different landscapes at the Granger watershed

9. Infiltration of snowmelt water into frozen soils where C is a coefficient = 2, S 0 is the surface saturation (mm 3 ·mm 3 ), S I is the average soil saturation (water + ice) of 0-40 cm soil at the start of infiltration (mm 3 ·mm 3 ), T I is the average temperature of 0-40 soil layer at start of infiltration (K), and t 0 is the infiltration opportunity time (h). North-facing slope South-facing slope Hydrograph CRHM Zhao and Gray approach where H q is surface flow (mm), H – snowmelt depth (mm), f * - infiltration coefficient in frozen ground, f 0 – infiltration coefficient in unfrozen ground, S i – ice content of a layer, n – coefficient (4 – sand, 5 – loam sand, 6 – loam, 7 – clay)

10. Assessment of evapotranspiration rates Granger & Gray Actual ET method: Actual ET is calculated using a combination of energy balance, aridity feedback and aerodynamic tranfer, so no knowledge of soil moisture status is required for this module. To ensure continuity, evaporation is taken first from any intercepted rainfall store, then from the upper soil layer and then from the lower soil layer and restricted by water supply Use of seasonal potential evaporation coefficients: actual ET depends on air aridity and moisture availability in soil and interception storages. In this study evaporation rates were estimated by calibration of soil parameters according to soil moisture observations Hydrograph CRHM Correlation between actual evaporation simulated by CRHM and the Hydrograph models

11. Verification of the Hydrograph model parameterization at point scale Forest Site: observed and simulated soil moisture content at 0.15 m depth Alpine Tundra Site: observed and simulated soil temperature at 0.15 m depth

12. Results of runoff modelling at Granger watershed (8 km 2 ), 1999 – 2001 1999 2000 2001 NS 19990.93 20000.73 20010.79

13. Wolf Creek basin, 195 km 2

14. Conclusions 1.CRHM blowing snow transport and redistribution module was verified in Wolf Creek basin and used to develop the information needed to set the Hydrograph parameters. 2.The comparison of infiltration into frozen ground routine showed that both models produce similar results in spite of application of different approaches. 3.The comparison of evaporation rates as well shows the coincidence between the models approaches. It means that in case of absence of observed soil moisture data the Hydrograph model could rely on the CRHM estimates. 4.The results of runoff and state variables simulations can be considered satisfactory given the scarcity of the data. 5.The use of estimated parameters in upscaled application of the Hydrograph model to the Yukon River will be explored as a next step. Future collaboration may create new possibilities and opportunities which would not otherwise exist. Science should not know barriers for collaboration.

15. Acknowledgements We appreciate invaluable help of Michael Allchin, Richard Janowicz, Sean Carey and Yinsuo Zhang in this project The attendance to EGU was made possible only with the support of the German-Russian Otto-Schmidt Laboratory for Polar and Marine Research