Reconstruction of glacier mass balances in the Ala

Reconstruction of glacier mass balances in the
Ala-Archa basin
David Kriegel, Doris Duethmann, Sergiy Vorogushyn, Abror Gafurov
CAWA Symposium 2010, 24. – 26.11.2010, Tashkent, Uzbekistan
Overview
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Introduction
Modelling glacier and snow melt runoff
Data
First results
Outlook
Introduction
Introduction – from glacier to runoff
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CA head water catchments highly glaciated
>1,580km³ fresh water storage
melt runoff as significant water sources (40-70% in summer)
climate change causes redistribution of precipitation, temperature
changes and runoff variation
How much does melt contribute to runoff?
How do glaciers change their “face”?
Introduction - Investigation site
Introduction – glacier mass and area change
 Reconstruction of mass balance with hydrological model
Modelling - Hydrological model WASA
Climate forcing
T, P, rh, rad
River basin
water
balance
Model output:
Time series of water
availability variables
Q, MB(z)
Processes represented in WASA:
 Infiltration
 Soil water movement
 Evapotranspiration
 Runoff generation
 Runoff routing in river network
 Retention in reservoirs
Modelling – melt description
• simple approach for snow and ice: temperature index
MELT = RMULT * CMFi * (TM-T0)
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depending on annual variation of min and max melt/d
by now: downwasting
planned: glacier area evolution
problem: distribution of MB by
elevation
 h-parametrization
(typical h(MB) for
different classes)
Data: Ala-Archa
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DEM 90m, Modis Landcover, Soil map
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Temp, Precip , rel. humidity, sun
duration from 7 stations:
1959 – 1973/74,1991
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Discharge data from 4 stations:
monthly mean values 1959-1991
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Mass balances (MB) for Golubina
glacier 1972-1993
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Initial glaciation from Landsat MSS
images from 1970ies (Kutzov and
Shahgedanova, 2009: negligible area changes
between 60ies and 70ies)
First results
• Dzhindizuv: overestimation, too early and too much Q
•Ala-Archa 2: overestimation!
•Adigene: overestimation!
First results – Analysis
• Adigene: no precipitation data!
• Interpolation and lapse rates according to Baitik and AlaArcha  problem: not suitable
• According to local scientists, precipitation strongly variable in
Ala-Archa catchment
Further development needed!
First results – Dzhindisuv
Outlook
• Next step: further development and calibration of model
WASA
– Refine input (precipitation, soil and vegetation parameters)
– Include ice evolution
• Implementation for other small catchments
• Run forward with climate data up to the year 2100