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Liudmila Lebedeva1,3, Olga Semenova2,3 1St.Petersburg State University 2State Hydrological Institute, St. Petersburg, Russia 3Hydrograph Model Research Group www.hydrograph-model.ru Estimation of possible active layer depth changes in North-East of Russia using climate projections and deterministic-stochastic approach Goal and objectives The goal of the research is to develop a tool for assessment of possible climate change impacts in permafrost environment of the North-East Russia using deterministic-stochastic modelling approach Requirements • Process-oriented deterministic model with physically observable parameters, minimum of calibration and ability to port calibrated parameters to similar environment • Downscaled climate change projections in probabilistic mode Objectives • Application and testing of the Deterministic-Stochastic Modelling system • Assessment of possible changes of active layer depth properties on the base of IPCC climate change scenarios Research stages • To simulate soil thawing and freezing processes at different landscapes using observed meteorological data as input • To refine the deterministic model parameters on historical data • To generate continuous series of daily meteorological data (30 years span) according the A1F1 and B1 IPCC climate change scenarios using the stochastic model • To simulate water and energy fluxes in the permafrost sites with randomly generated series of meteorological elements as forcing data using the deterministic model with physical parameters • To assess and compare possible changes in active layer properties within variable conditions and according different climate change scenarios Hydrograph Model • • • • Deterministic distributed model of runoff formation processes Heat and water dynamics simulations in soil profile Use of observable physical properties of landscapes as model parameters Minimum of manual calibration Precipitation Rain Snow R Heat energy Snow cover formation Interception Heat dynamics in soil Heat dynamics in snow Snow melt and water yield Initial surface losses Infiltration and surface flow Water dynamics in soil Slope transformation of surface flow Evaporation Underground flow Transformation of underground flow Channel transformation Runoff at basin outlet Forcing data: precipitation, temperature, relative humidity Output results: runoff, soil and snow state variables, full water balance Applications of the Hydrograph model in permafrost environments (runoff simulations) 0.10 Q 1980 1981 0.08 10000 m3/s 10000 8000 5000 0.06 0.04 6000 0.02 4000 0.00 06.1981 08.1981 2000 I II III IV V VI VII VIII IX X XI XII simulated I II III IV V VI 1982 VII VIII IX X XI XII 10.1981 observed 0.10 1983 0.08 m3/s 15000 0.06 0.04 10000 10000 0.02 0.00 5000 06.1982 5000 I II III IV V VI VII VIII IX X XI XII I II III IV V VI VII VIII IX X XI XII T 10.1982 observed Yuzhny creek, KWBS 0.27 km2 Vitim at Bodaybo, 186000 km2 (Eastern Siberia, continuous permafrost) 1. 1 1. 3 1999 1. 2 1. 1 2000 1. 1 1. 0 0. 9 0. 9 0. 8 1. 0 0. 8 0. 9 0. 7 0. 7 0. 8 0. 6 0. 7 m 3/ s m 3/ s Granger watershed, 8 km2 (Yukon basin, Canada – zone of discontinuous permafrost) 08.1982 simulated 0. 6 0. 6 0. 5 0. 5 0. 4 0. 5 0. 4 0. 3 0. 4 0. 3 0. 3 0. 2 0. 2 0. 2 0. 1 0. 1 0. 1 0. 0 0. 0 0. 0 04.1999 06.1999 08.1999 s imulated 10.1999 obs erved 12.1999 05.2000 07.2000 09.2000 s imulated 11.2000 obs erved 01.2001 Stochastic Model “Weather” (SMW) • Simulation of daily precipitation, temperature and relative humidity • Simulation of annual and intra-seasonal variations • Spatial and temporal correlation of meteorological elements • Initial parameters are estimated from observed series of meteorological data • Parameters may be modified according to climate change projections Applications of SMW (observed and simulated series) Monthly distribution of precipitation, Bodaybo station Чара 30372 500 • Calc • Obs 90 450 Precipitation, mm 80 400 350 300 250 70 60 50 40 30 20 10 0 Jan 200 1 2 3 4 5 6 8 10 15 20 25 35 45 55 P, % р ас с ч 65 75 80 85 90 93 95 97 98 Feb Mar Apr May Jun Jul obs 9 9 .2 Aug Sep Oct Nov Dec calc наб л Annual sums of precipitation, Chara station Monthly distribution of air temperature, Vostochnaya station 80 70 20 60 10 Temperature, degr C 50 40 30 20 0 -10 Jan Feb Mar Apr May Jun Jul Aug -20 -30 10 -40 0 obs 0.01 0.1 0.4 1 2 4 6 9 Exc e e da nc e pro ba bi li t y , % c alc 15 25 40 obs Daily values of precipitation, Suntar-Hayata station 50 calc Sep Oct Nov Dec Research strategy Parameters of observed daily meteorological series Stochastic Model of Weather Climate change projections Simulated ensembles of meteorological data according to IPCC climate change projections Physically observable parameters Deterministic hydrological model Deterministic simulation of processes using stochastic data Numerical evaluation of hydrological changes Study area Kolyma water-balance station (KWBS) – small research watershed (22 km2) in the upper Kolyma river. Watershed boundaries Meteorological Station Rain gauge Recording rain gauge Pit gauge Snow survey line Cryopedometer Evaporation plot Pan evaporation plot Snow evaporation plot Water balance plot Sketch of the KWBS • Mean annual temperature – -11,60C • Precipitation – 314 mm/year • Open wood, bare rocks • Continuous permafrost • High-mountain relief • Representative for the North-East of Russia Active layer depth in different landscapes Site 1 Upper part of the slope: • • rock debris absence of vegetation Site 2 Lower part of the slope: • • clay slate peaty ground swamp larch forest Soil physical properties The main parameters for simulation soil thawing and freezing processes in the Hydrograph model are physical soil properties Porosity, % Field capacity, % Heat capacity, J/m3*K Heat conductivity, W/m*K Peat 80 50 1920 0.8 Clay slate 50 40 750 2.3 55 30 810 1.7 55 13 790 2 Crushed stone Crumbling rock m Deterministic modelling of active layer depth Site 1: Site 2: • 850 m • North-facing slope • Sphagnum, shrubs • Soil profile – peat, clay loam, clay slate • Active layer depth up to 0.7 m • 1100 m • South-facing slope • Absence of vegetation • Rock debris • Active layer depth up to 1.7 m 0 0 0.2 0.2 0.4 0.4 0.6 0.6 0.8 0.8 m 1 1 1.2 1.2 1.4 1.4 1.6 1.6 1.8 03.77 1.8 06.77 09.77 12.77 03.78 Calculated 06.78 09.78 Observed 12.78 03.79 03.82 m 06.82 09.82 12.82 03.83 Calculated Observed and calculated active layer depth in two landscapes, KWBS 06.83 09.83 Observed 12.83 03.84 IPCC emission scenarios Implications of emission scenarios for global Tº by 2100 relative to 1990 (chosen scenarios and the model marked as red) Scenario A1F1 A1B A1T A2 B1 B2 Global ΔT(0C) 4.5 2.9 2.5 3.8 2.0 2.7 Atmospheric-Ocean General Circulation Models Model CCSR/NIES CGCM2 CSIRO Mk2 ECHAM4/OPYC3 GFDL R30 HadCM3 NCAR DOE PCM Country Japan Canada Australia Germany U.S.A. United Kingdom U.S.A. ΔTglob 4.4 3.5 3.4 3.3 3.1 3.2 2.4 ECHAM4/OPYC3 model projection according to A1F1 and B1 scenarios for 2010-2039 Soil thawing – depth projections Maximum active layer depth: projected according to B1 and A1F1 scenarios and historically observed in different landscape Mean active layer depth: projected according to B1 and A1F1 scenarios and historically observed in different landscapes Duration of thawing period (B1, A1F1 and historical) Bare rocks Swamp forest Results • Both mean and maximum annual active layer depths are projected to increase by 2039. • Mean soil thawing is expected to be 40 and 50 cm deeper than historically observed reaching 195 and 205 cm in the bare rock site according to B1 and A1F1 scenario • Mean soil thawing is expected to be 70 cm deeper than historically observed reaching 130 cm in the swamp forest site for both scenarios • The starting date of soil thawing in bare rocks is projected to be almost one month earlier due to strong effect of south-facing slope and solar radiation income • The starting dates of soil thawing in swamp forest landscape are projected to be only one week earlier in comparison with historical data • Total duration of thawing period is projected to extend by 1 – 1.5 months for bare rocks and about 1 month for forest landscape General conclusions • The deterministic hydrological model Hydrograph is able to simulate adequately the processes of soil thawing and freezing in permafrost environment • Observable physical properties of landscapes are used as the model parameters; the model requires minimum of calibration • To assess the possible effect of climate change on active layer depth the processes-based deterministic models are required. The Hydrograph model may be considered to be one of those models • The stochastic model of Weather was used here to downscale climate change projections for specific sites and generate numerous continuous series of meteorological data with assigned parameters. In general, it can be replaced with some more advanced models and was used here as an example of the approach Acknowledgements • This study was conducted within the research grant provided by the Russian-German Otto-Schmidt Laboratory for Polar and Marine research in 2010 • The conference attendance was made possible with the support of APECS which is highly appreciated Thank you for attention! More results on applications of the Hydrograph model in assessment of climate change impacts on runoff in permafrost environment… Poster 124 Evaluation of climate change impact on river runoff in Eastern Siberia by Semenova et al.