1. Assessment of Runoff Engineering Characteristics in Conditions of the Shortage of Hydrometeorological Data in North-Eastern Russia O.M. Semenova State Hydrological Institute; Gidrotehproekt Ltd, St. Petersburg, Russia L.S. Lebedeva St. Petersburg State University; Nansen Centre, St.Petersburg, Russia I.N. Beldiman "Khotugu Oruster" (the North Rivers), Yakutsk, Russia Hydrograph Model Research Group St. Petersburg, Russia www.hydrograph-model.ru

2. Agenda Tasks of geotechnical site investigations and construction in rich by natural resources North-East of Russia Poor hydrometeorological network which was significantly diminished in the last 20 years Observed environmental changes which impact differently in various permafrost landscapes Permafrost as the factor governing hydrological processes Statistical approach based on extrapolation of observational data and currently used in design engineering practice is not reliable any more www.hydrograph-model.ru

3. Goal To develop unified approach (modelling tool) for assessment of design flood characteristics in changing environment which may be applied in various permafrost conditions Requirements to the model Process-oriented deterministic model Physically observable parameters with the possibility to estimate them a priori and systematize by typical landscapes Ability to port parameters to ungauged watersheds without calibration www.hydrograph-model.ru

4. Series of daily meteorological data Research strategy Deterministic hydrological model Physically observable parameters Stochastic weather generator Ensembles of climate projections Series of simulated runoff Numerical evaluation of runoff characteristics in probabilistic mode Historical re-analysis www.hydrograph-model.ru

5. Bare rocks Bush tundra Larch forest Riparian vegetation Deep active layer, Subsurface runoff Shallow active layer, surface runoff www.hydrograph-model.ru Variety of landscapes and complex process interactions

6. Common approaches for permafrost hydrology modelling Large scale hydrological models (LSS) integrated into climate modelling systems Crude representation of processes without their specification in different conditions The output values for runoff and variable states are averaged by large territories OR Development of refined physically- based models of specific processes Calibration-based, require specific data Applicable in very limited cases Both not reliable in assessment of runoff characteristics www.hydrograph-model.ru

7. The Hydrograph Model www.hydrograph-model.ru Process-based ( explicitly includes all processes ) Observable parameters, no calibration ( can be obtained apriori ) Common input daily data ( air temperature and moisture, precipitation ) Free of scale problem ( from soil column to large basin ) initially developed by Prof. Yury Vinogradov

8. Typical landscapes Soil horizons:

9. Physical properties of the soils driving the processes of active layer formation www.hydrograph-model.ru Moss and lichen PeatClay with inclusion of rocks Bedrock Density, kg/m350017202610 Porosity, %90805535 Water holding capacity, % 606020-40137 Infiltration coefficient, mm/min 100.0005- 0.5 0.00050.05-1 Heat capacity, J/kg*0C1930 840750 Heat conductivity, W/m* 0 C 0.8 1.21.5 Wilting point, %86-842-3

10. Results of modelling active layer dynamics Simulated (green) and observed (black) thawing depths in the bare rock site, m Simulated (pink) and observed (black) thawing depths in the larch forest site, m simulated observed simulated observed

11. Results of runoff modelling at the Kolyma water-balance station watersheds www.hydrograph-model.ru Гидрографы на малых водосборах и картинки Yuzhny Creek, 0.27 km 2, 1978, m 3 /s Sparse forest Severny Creek, 0.33 km 2, 1979, m 3 /s Bush tundra

12. Results of runoff modelling at the Kolyma water-balance station watersheds 12 Kontaktovy Creek, 21.2 km 2, 1978, m3/s Morozova Creek, 0.63 km 2, 1977, m 3 /s Bare rock Landscape distribution: Bare rock – 32 % Bush tundra – 29 % Sparse forest – 21 % Larch forest – 18 %

13. Verification of the modelling results on poorly studied basins www.hydrograph-model.ru

14. Results of runoff modelling at poorly gauged basins www.hydrograph-model.ru The Ayan-Yuryakh river, 9560 км 2, 1978-1979. Mountainous relief and absence of meteorological stations. Input data were interpolated from stations located outside the basin The Tenke river, 1820 км 2, 1978-1979.

15. Extrapolation of observed runoff series with simulations using historical meteorological data www.hydrograph-model.ru Detrin river, 5630 км 2, 1978-1979 Two meteostations within basin The Ayan-Yuryakh river, 9560 км 2. Distribution curves of maximum discharges: Observed 1977-1984 Simulated 1957-1984 simulatedobserved

16. Estimation of maximum runoff distribution curves using stochastic weather generator The Tenke River basin, 2.2 km from the mouth of the Nilkoba River (1820 km 2 ) 1 – observed; 2 – simulated on the basis of available historical data; 3 - the 1000-year-long series obtained on the basis of DS-modeling www.hydrograph-model.ru

17. Conclusions The Hydrograph Model demonstrates adequate representation of permafrost processes in terms of active layer and runoff dynamics Good agreement between observed and simulated active layer depth and runoff is achieved for small watersheds of the KWBS Developed set of model parameters which are systematized according to main landscapes of the Upper Kolyma River basin may be successfully transferred to other basins without specific observations The Hydrograph model may be applied as a practical tool to estimate runoff characteristics using any source of meteorological data such as historical observations, re- analysis, future climate model projections www.hydrograph-model.ru

18. Acknowledgements The authors acknowledge the support of the TICOP’s organizers, sponsors and PYRN for the provided opportunity to attend the Conference. www.hydrograph-model.ru Thank you for attention!