O.M. Semenova State Hydrological Institute; Gidrotehproekt Ltd, St. Petersburg, Russia

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


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


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


Bare rocksBush tundra

Larch forest

Riparian vegetation

Deep active layer,Subsurface runoff

Shallow active layer,surface runoff


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


The Hydrograph ModelThe Hydrograph Model


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


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


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


10.197708.197706.197704.1977

м3

/с

0.4

0.3

0.2

0.1

0


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


10.197808.197806.197804.1978

м3

/с

8

6

4

2

0


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


Results of runoff modelling at poorly gauged basinsResults of runoff modelling at poorly gauged basins



11.197809.197807.197805.1978

м3

/с

1200

1000

800

600

400

200

0


11.197909.197907.197905.1979

м3

/с

1200

1000

800

600

400

200

0

The Ayan-Yuryakh river, 9560 км2, 1978-1979.


11.197809.197807.197805.1978

м3

/с

400

350

300

250

200

150

100

50

0


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


11.197809.197807.197805.1978

м3

/с

1400

1200

1000

800

600

400

200

0


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


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


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.

www.hydrograph-model.ruwww.hydrograph-model.ru

Thank you for attention!

O.M. Semenova State Hydrological Institute; Gidrotehproekt Ltd, St. Petersburg, Russia

Documents

Transcript of O.M. Semenova State Hydrological Institute; Gidrotehproekt Ltd, St. Petersburg, Russia