Looking for universality...

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Presentation transcript:

Looking for universality... Deterministic-stochastic modelling as a potential tool for the assessment of climate change impacts on hydrological regime in polar regions Olga Semenova State Hydrological Institute St. Petersburg, Russia

Objectives The goal of the research is to develop a tool for assessment of the possible changes in the annual, seasonal and extreme runoff characteristics of watersheds of Eastern Siberia on the base of deterministic-stochastic modelling Necessary conditions: Process-oriented deterministic model with physically observable parameters, minimum of calibration and ability to port calibrated parameters to other watersheds Stochastic model providing the meteorological inputs according to climate change projections State Hydrological Institute, St. Petersburg, Russia

Research strategy Deterministic hydrological model Parameters of observed daily meteorological series Physically observable parameters Simulated scenarios of daily meteorological data Deterministic hydrological model Stochastic Model of Weather Runoff generation processes simulations Climate change projections Numerical evaluation of runoff characteristics changes in probabilistic mode State Hydrological Institute, St. Petersburg, Russia

Looking for universality... Study area Looking for universality... State Hydrological Institute, St. Petersburg, Russia 4

Hydrograph model (deterministic modelling) Looking for universality... Hydrograph model (deterministic modelling) Single model structure for watersheds of any scale Adequacy to natural processes while looking for the simplest solutions Minimum of manual calibration R Forcing data: precipitation, temperature, relative humidity Output results: runoff, soil and snow state variables, full water balance State Hydrological Institute, St. Petersburg, Russia

Weather model (stochastic modelling) Looking for universality... Weather model (stochastic modelling) Simulation of daily precipitation, temperature and relative humidity Simulation of annual and intra-seasonal variations Simulation for hexagonal system of representative points Temporal correlation of meteorological elements Spatial correlation of meteorological elements Parameters are estimated from observed series of meteorological data Parameters may be modified according to climate change projections R State Hydrological Institute, St. Petersburg, Russia

Looking for universality... DM: state variables 0.8 m depth 0.4 m depth Soil temperature at different depths Kolyma Water balance station Snow characteristics State Hydrological Institute, St. Petersburg, Russia

Looking for universality... DM: small and middle scale basins ---------- simulated ---------- observed Timpton at Nagorny, basin area 613 km2 Vitim at Bodaybo, basin area 186000 km2 State Hydrological Institute, St. Petersburg, Russia

Looking for universality... DM: Large-scale basin Lena at Kusur basin area 2,4 million km2 ---------- simulated ---------- observed State Hydrological Institute, St. Petersburg, Russia

Looking for universality... SM: annual values Looking for universality... Chara meteorological station. Annual precipitation (mm) • Calc • Obs mm Exceedance probability, % State Hydrological Institute, St. Petersburg, Russia

SM: correlation of annual values Looking for universality... SM: correlation of annual values Spatial correlation of annual temperature, Lena river basin State Hydrological Institute, St. Petersburg, Russia

Looking for universality... SM: seasonal values Looking for universality... Monthly distribution of precipitation Monthly distribution of temperature Bodaybo station Vostochnaya station State Hydrological Institute, St. Petersburg, Russia

Looking for universality... SM: daily values Daily precipitation, Suntar-Hayata station State Hydrological Institute, St. Petersburg, Russia

SM: correlation of daily values Looking for universality... SM: correlation of daily values Spatial correlation of daily temperature, Lena river basin State Hydrological Institute, St. Petersburg, Russia

Looking for universality... DSM: maximum flows Timpton river at Nagorny, 613 km2 State Hydrological Institute, St. Petersburg, Russia

Looking for universality... DSM: daily flows Ebetiem river at Ebetiem, 114 km2 State Hydrological Institute, St. Petersburg, Russia

Looking for universality... Conclusions The deterministic hydrological model Hydrograph performs well in arctic region at different landscapes and scales Most parameters are estimated from physical characteristics and do not require any calibration The stochastic model takes into account annual, seasonal and daily variation of meteorological elements and their spatial and temporal correlation Next step would be generation of ensembles of precipitation and temperature forcings according to IPCC climate change projections to obtain probabilistic estimates of annual, seasonal and daily extreme hydrological variables for large scale basins State Hydrological Institute, St. Petersburg, Russia

Looking for universality... Acknowledgements The research is being conducted within the research grant funded by the German-Russian Otto-Schmidt laboratory for Polar and Marine Research The IPY Oslo Stipend granted by the Research Council of Norway is appreciated State Hydrological Institute, St. Petersburg, Russia