MODELLING FUTURE CHANGES IN CRYOSPHERE OF INDUS BASIN

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1 MODELLING FUTURE CHANGES IN CRYOSPHERE OF INDUS BASIN ANIL V. KULKARNI DISTINGUISHED VISITING SCIENTIST DIVECHA CENTRE FOR CLIMATE CHANGE INDIAN INSTITUTE OF SCIENCE BANGALORE INDIA Presented at workshop on Climate and Environment Changeon the Indus basin waters, ICIMOD, Kathmandu, February 2016

2 INDUS BASIN GLACIERS: What we know - don t know

3 GLACIER EXTENT HIMALAYA GLACIER INVENTORY IS AVAILBALE FROM ICIMOD, GLIMS AND RGI, ISRO and GSI Sq km 0 INDIA Tobias et al, 2012; Kulkarni and Buch, 1991; Bajracharya and Shrestha, 2011

4 GLACIER RETREAT (Kulkarni A. V. and Yogesh Karyakarte,2014) NUMBER OF GLACIERS: Himalaya: 81; Indus : 35 PERIOD OF INVESTIGATION: MEAN RETREAT: INDUS BASIN: 178 ±138 m/ decade EXCEPT THREE, ALL OTHER GLACIERS ARE RETREATING NO FIELD DATA IN KARAKORAM, ARUNACHAL PRADESH

5 LOSS IN GLACIER AREA (Kulkarni A. V. and Yogesh Karyakarte,2014) GLACIAL AREA LOSS OBSERVED FROM 1960 TO TOTAL GLACIER AREA: HIMALAYA-KARAKORAM: ~ 40,000 sq km GLACIATED AREA MAPPED: 11,000 SQ KM, LOSS IN GLACIER AREA: INDUS BASIN : 3.7 % / Decade

6 MASS LOSS: DIFFERENT SCALES: INDUS BASIN Glaciological Geodetic Gravimetric Chhota Shigri glacier mwe/ yr from 2002 to 2014 (Azam et al., 2014) Lahual Spiti, Western Himalaya ± 0.18 mwe/ yr from 1999 to 2011 (Gardelle et al., 2013) High Mountain Asia -4 ± 20 Gt/ yr from 2003 to 2009 (Jacob et al, 2012)

7 VOLUME OF GLACIER STORED WATER (From: Tobias et al, 2012) 3 Slope, basal shear stress and elevation range 2 Scaling method Range: Gt Glacier volume in HKH region (Gt)

8 VELOCITY USING SUBPIXEL CORRELATION SAMUDRA TAPU GLACIER, INDUS BASIN Cuffy and Paterson, The Physics of Glaciers, 2010 Prateek G., A.V. Kulkarni, and J.Srinivasan, 2014, Estimation of ice thickness using surface velocities and slope at the Gangotri glacier, India, Journal of Glaciology, 60(220),

9 SPATIAL DISTRIBUTION OF DEPTH AND LAKE PREDICTION: SAMUDRA TAPU, CHENAB BASIN

10 BC AND ALBEDO OF ACCUMULATION AREA A.V. Kulkarni,et al 2013

11 Fate of Himalayan Glaciers Chaturvedi et al, 2014, Glacial Mass Balance Changes in the Karakoram and Himalaya based on CMIP5 Multi-Model Climate Projections, climatic Change

12 Schematic of the methodology Chaturvedi et al, 2014, Glacial Mass Balance Changes in the Karakoram and Himalaya based on CMIP5 Multi-Model Climate Projections, climatic Change

13 Poster: C13B-0810 Session Title: Glacier Monitoring from In Situ and Remotely Sensed Observations Estimation of glacier mass balance: An approach based on satellite-derived transient snowlines and a temperature index model driven by meteorological observations Sayli A. Tawde, Anil V. Kulkarni, G. Bala Centre for Atmospheric and Oceanic Sciences, Divecha Center for Climate Change, Indian Institute of Science, Bangalore, India sayli@caos.iisc.ernet.in I. Background & Motivation An area of 22,800 km 2 is under glacier coverage in the Himalaya, impacting the hydrological and socio-economic status of the downstream population Glaciers and seasonal snow extents vary according to climate conditions. Glacier evolutions in response to changing climate can be monitored using glacier mass budget measurements. Present field mass balance measurements are limited to few small glaciers, but we need basin-wide estimates toanticipate availability ofwater resources in this region. There are different remote sensing based techniques to compute basin-wide mass balance. One ofthe technique is Area Accumulation Ratio (AAR) method, which relies onthe regression between mass balance and AAR. Calculation of AAR requires an accurate estimate of Equilibrium Line Altitude (ELA) i.e. Transient Snowline (TSL) at the end of ablation season. Identification of ELA using remote sensing is difficult because of temporal gaps, cloud covers and intermediate snowfall events. Therefore, an improved approach is proposed to monitor the location of ELA in ablation season by combining satellite-derived TSL & meteorological data. II. Study area Chandra Basin, Lahual Spiti, Himachal Pradesh, Western Himalaya. 72% precipitation falls in winter season Fig. 1 Map of Chandra basin, meteorological station near the basin III. Methodology Fig. 2 A flowchart of the methodology Uncertainty analysis: Satellite data In-situ data IV. Results A. Precipitation gradient of basin Estimated precipitation gradient = 0.19 ± 0.18%/m Precipitation gradient is high for South-west facing glaciers i.e. glaciers on the windward side to the flow of Westerlies B. Satellite versus model transient snowlines Fig. 4 Correlation between satellite-derived and model transient snowlines C. Modification of mass balance-aar regression Modified regression between field mass balance and model AAR on Chhota Shigri glacier Reduces RSME in model mass balance Converges to regression between available field mass balance-aar for the Western Himalayan glaciers. Fig. 3 Variation of precipitation gradient with orientation of the glaciers Fig.5 Comparison between trends of satellite-derived (blue) and model (red) transient snowlines Fig.6 Old and modified AAR-mass balance regression developed on Chhota Shigri ( , ) D. Modelled mass balance over a decade Decadal ( ) mass loss from 12 glaciers in the Chandra basin is 1.67 ± 0.64 Gt Uncertainty in model mass balance = 0.3 m w.e. E. Comparison of model mass balance 1) Annual specific mass balance (m w.e.) of Chhota Shigri glacier 2003 to 2009 using field (F), model (M) and conventional AAR method (A) Corr (F-A)=0.68 RMSE(F-A)= 0.81 m w.e. Corr (F-M)= 0.94 RMSE(F-M)= 0.26 m w.e. 2) Avg. winter mass balance on Chhota shigri by glaciological method, ( )= 1.02 m w.e. by Azam et al. (2014), ( )= 0.94 m w.e. by our model, ( ) = 1.17 m w.e. 3) Glaciers Chhota Shigri Fig. 8 Annual specific mass balance for Chhota Shigri glacier. Table 1 Comparison of model mass balance (m w.e./yr) in the Chandra basin with mass balance estimates using different methods. Model and the conventional AAR method mass balance is up to 2009 Study Glaciological Geodetic Present Convention period study al AAR ± ± ± ± 0.07² ± ± , ± Hamtah ± ± ± Selected ± Conclusions The new method improves mass balance estimates over the conventional AAR method by reducing mean absolute percentage bias by 50.44% on Chhota Shigri. Total mass loss from 1999 to 2009 for 12 glaciers in Chandra basin is: 1.67 ± 0.67 Gt (with mass balance of ± 0.30 m w.e./yr). The model mass loss rate is comparable with geodetic estimates on regional scale. However, variations in modelled mass balance compared to geodetic estimates are observed on individual glaciers. Model is found useful to estimate mass balance of glaciers, where field observations are unavailable. Using temperature and precipitation data which is normally available for a long period, we can reconstruct mass loss for past as well as predict for future. Fig.7 Model mass loss (Gt) from 1999 to 2009 References: 1. Gardelle et al. (2013) 3. Kulkarni (1992) 5. Vincent et al. (2013) 2. Kaab et al. (2012) 4. Kulkarni et al. (2004) 6. Wagnon et al. (2007)

14 Temperature and Precipitation change (Chaturvedi et al, 2014)

15 Temperature and Precipitation change (Chaturvedi et al, 2014)

16 GLACIER MASS BALANCE IN HIMALAYA DUE TO TEMPERATURE AND PRECIPITATION CHANGE (Chaturvedi et al, 2014)

17 THANKS