assessment of runoff engineering characteristics in conditions of the shortage of...
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Assessment of Runoff Engineering Characteristics in Assessment of Runoff Engineering Characteristics in Conditions of the Shortage of Hydrometeorological Conditions of the Shortage of Hydrometeorological
Data in North-Eastern RussiaData 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 GroupHydrograph Model Research GroupSt. Petersburg, RussiaSt. Petersburg, Russia
www.hydrograph-model.ru
AgendaAgenda• 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
GoalGoalTo 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 modelRequirements 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
Series of daily meteorological data
Research strategyResearch 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
Bare rocksBush tundra
Larch forest
Riparian vegetation
Deep active layer,Subsurface runoff
Shallow active layer,surface runoff
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Variety of landscapes and complex process interactionsVariety of landscapes and complex process interactions
Common approaches for permafrost hydrology modellingCommon 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
OROR
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 characteristicsBoth not reliable in assessment of runoff characteristics
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The Hydrograph ModelThe 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 Vinogradovinitially developed by Prof. Yury Vinogradov
Typical landscapesTypical landscapes
moss and lichen
peat
bedrock
clay inclusion of rocks
100
90
80
70
60
50
40
30
20
10
cm
Larch forestSparse forest
Bush tundraBare rocks
moss and lichen
peat
bedrock
clay inclusion of rocks
100
90
80
70
60
50
40
30
20
10
cm
Larch forestSparse forest
Bush tundraBare rocks
Soil horizons:
Physical properties of the soils driving Physical properties of the soils driving the processes of active layer formationthe processes of active layer formation
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Moss andlichen
Peat Clay withinclusion of
rocks
Bedrock
Density, kg/m3 500 1720 2610 2610Porosity, % 90 80 55 35Water holding capacity, %
60 20-40 13 7
Infiltration coefficient,mm/min
10 0.0005-0.5
0.0005 0.05-1
Heat capacity, J/kg*0C 1930 1930 840 750Heat conductivity,W/m*0C
0.8 0.8 1.2 1.5
Wilting point, % 8 6-8 4 2-3
Results of mResults of modelling active layer dynamicsodelling active layer dynamics
наблюденная рассчитанная17.5 175
01.198401.198301.198201.1981
м
0
-0.5
-1
-1.5
рассчитанная наблюденная9 9
01.196607.196501.196507.196401.196407.1963
м
0
-0.5
-1
-1.5
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
simulatedobserved
simulatedobserved
Results of runoff modelling Results of runoff modelling at the Kolyma water-balance station watershedsat the Kolyma water-balance station watersheds
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Гидрографы на малых водосборах и картинкиНаблюденный Рассчитанный
10.197809.197808.197807.197806.197805.1978
м3
/с
0.10
0.08
0.06
0.04
0.02
0.00
Наблюденный Рассчитанный
10.197908.197906.1979
м3
/с
0.10
0.08
0.06
0.04
0.02
0.00
Yuzhny Creek, 0.27 km2, 1978, m3/s
Sparse forest
Severny Creek, 0.33 km2, 1979, m3/s
Bush tundra
Наблюденный Рассчитанный
10.197708.197706.197704.1977
м3
/с
0.4
0.3
0.2
0.1
0
Наблюденный Рассчитанный
10.197708.197706.197704.1977
м3
/с
0.4
0.3
0.2
0.1
0
Results of runoff modelling Results of runoff modelling at the Kolyma water-balance station watershedsat the Kolyma water-balance station watersheds
12
Kontaktovy Creek, 21.2 km2, 1978, m3/s
Наблюденный Рассчитанный
10.197808.197806.197804.1978
м3
/с
8
6
4
2
0
Наблюденный Рассчитанный
10.197808.197806.197804.1978
м3
/с
8
6
4
2
0
Morozova Creek, 0.63 km2, 1977, m3/sBare rock
Landscape distribution:
Bare rock – 32 %
Bush tundra – 29 %
Sparse forest – 21 %
Larch forest – 18 %
Verification of the modelling results on poorly studied Verification of the modelling results on poorly studied basinsbasins
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Results of runoff modelling at poorly gauged basinsResults of runoff modelling at poorly gauged basins
www.hydrograph-model.ru
Наблюденный Рассчитанный
11.197809.197807.197805.1978
м3
/с
1200
1000
800
600
400
200
0
Наблюденный Рассчитанный
11.197909.197907.197905.1979
м3
/с
1200
1000
800
600
400
200
0
The Ayan-Yuryakh river, 9560 км2, 1978-1979.
Наблюденный Рассчитанный
11.197809.197807.197805.1978
м3
/с
400
350
300
250
200
150
100
50
0
Наблюденный Рассчитанный
11.197909.197907.197905.1979
м3
/с
400
350
300
250
200
150
100
50
0
Mountainous relief and absence of meteorological stations. Input data were interpolated from stations located outside the basin
The Tenke river, 1820 км2, 1978-1979.
Extrapolation of observed runoff series with simulations Extrapolation of observed runoff series with simulations using historical meteorological datausing historical meteorological data
Наблюденный Рассчитанный
11.197809.197807.197805.1978
м3
/с
1400
1200
1000
800
600
400
200
0
Наблюденный Рассчитанный
11.197909.197907.197905.1979
м3
/с
1400
1200
1000
800
600
400
200
0
рассчитанный наблюденный
P, %99.899.2979488807055402515964210.4
2 . 5 2 1 . 5 1 0 . 5 0 - 0 . 5 - 1 - 1 . 5 - 2 - 2 . 5 - 3
Q,
м3
/с
1200
1100
1000
900
800
700
600
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Detrin river, 5630 км2, 1978-1979Two meteostations within basin
The Ayan-Yuryakh river, 9560 км2. Distribution curves of maximum discharges:Observed 1977-1984Simulated 1957-1984
simulated observed
Estimation of maximum runoff distribution curves using Estimation of maximum runoff distribution curves using stochastic weather generatorstochastic weather generator
The Tenke River basin, 2.2 km from the mouth of the Nilkoba River (1820 km2)
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
ConclusionsConclusions
• 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.ruwww.hydrograph-model.ru
AcknowledgementsAcknowledgements
The authors acknowledge the support of the TICOP’s organizers, sponsors and PYRN for the provided opportunity to attend the Conference.
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Thank you for attention!