WP 2 - Snow and Glacier originated run-off generation

Estimates of future potential effects of climatic warming on runoff from glaciers and glacierised basins requires the application of physically-based models to couple evolving climatic conditions through representation of hydro-glaciological processes with declining glacier area over which meltwater can be generated. How area changes with lowering of the ice surface depends on the three-dimensional geometry of the glacier. A valley glacier occupying a deep trough will largely maintain the same area during glacier thinning whereas a glacier with a wedge-shaped (triangular) cross section will show a reduction in area sooner. How much discharge first increases and when decline starts depends on whether the rate at which energy availability for melting increases can offset the rate at which at which ice area diminishes.

Available hydrological and glaciological data for parameter optimisation are sparse in the Indian Himalaya. Three-dimensional structure and ice volume is known only for the small Dokriani Bamak. Discharge from highly-glacierised basins has been measured at Dokriani and at the much larger Gangotri glacier for about 20 and 5 years respectively.

Four years of mass balance data are available for Chhota Shigri glacier, but discharge is not measured. Long-term climatic observations are not available necessitating use of NCEP/NCAR reanalysis information. Changes in glacier dimensions are best obtained from repeat remotely-sensed imagery, and information is required concerning the Little Ice Age maximum dimensions of glaciers, depletion from which has already augmented runoff.  Measurements of discharge, air temperature and precipitation in highly-glacierised basins are however available for the wetter eastern Himalaya in Nepal. Elevation range and areal extent are known for all glaciers through the Geological Survey of India Inventory of the Himalayan Glaciers. Where at all possible, existing datasets will be acquired. A stream gauging station will be installed at one of the sites as a contribution from HighNoon to maintaining long term hydrological data collection on a river close to a glacier terminus.

The intention in this project is to build on previous model success in quantifying the impact of climate change on river flows in the glacierised north of the subcontinent.  A simple-temperature index-based model was developed by Rees & Collins (2006) in the UK DfID SAGAMATHA programme on snow and glacier aspects of water resources management in the Himalayas. Hypothetical glaciers with prescribed geometry located in hypothetical basins were subjected to a uniform rise in temperature to predict future response of flow in Himalayan glacier-fed rivers as glaciers declined in area. Regional differences in response were indicated even if the absolute quantities of flow depended on assumed geometries of the hypothetical glaciers.  Precipitation was held constant in these estimates.

This model will be used with real and various hypothetical glacier geometries, with output from the climate models in WP1 in order to examine the influence of glacier shapes on future runoff. Precipitation estimates derived from the regional climate models will allow predicted changes in timing and amounts of monsoonal precipitation to be taken into account. Glaciers with real and hypothetical geometries will be modelled for locations across northern India from the arid/monsoon transition at Chhota Shigri through to full monsoonal conditions in the headwaters of the Ganga.  Basins of various percentage glacier cover can be modelled using this approach.

The distributed hydrological model SWAT has already been used for assessing climate change impacts on the hydrology of Indian river basins (Gosain and others 2006), using HadRM2 output. Snow and ice were not represented in these simulations. A snow and ice routine will be developed for this model, and the improved model applied to the entire Ganga basin. The river flow data availability for the Ganga River is problematical, but gridded precipitation data (50 km x 50 km) are available for the period  1950s -2000s. Land-use and snowcover will be derived from the National Remote Sensing Agency. Model calibration and validation can be achieved by using the data available for tributary streams within Nepal. Validation for the entire Ganga system will only be possible at the annual timescale, using the published long-term flow data.

The third approach will use the intrinsic glacier scheme of the Max Planck Institute RCM to forecast runoff changes in glacierised catchments from a generalised 'icesheet' to develop an independent estimate of climate change effects on snow cover, glacier area, volume and runoff conditions. Parameterisation will be achieved by comparison with observation-based mass balance and glacier area datasets. Basins will consist of grid cells from the regional model assembled into plausible drainage areas. The UK Meteorological Office will develop the JULES hydrological model to include glaciers as in the HadRGM1 model. With glaciers included, along with vegetation and surface hydrology, the JULES model will be used to predict future river flow from the Himalaya.  Inter-comparison of future runoff predicted by the three approaches will be undertaken. This will enable at least some estimate of uncertainty in modelled future runoff from Himalayan basins.

The river flow data availability in the Ganges River has always been a problem, model calibration and validation shall be done by using the data available on the tributary streams in Nepal and India on the series basis. However, the validation for the total Ganges system shall be made using the published long-term flow data at annual interval.
In the recent past, global climatic change has had a tremendous impact on high mountain glacial environments, often accompanied by the formation and rapid growth of glacial lakes. Many of these lakes are in unstable conditions due to the highly dynamic environment and related dam breach risks. Resulting Glacial Lake Outburst Flood (GLOF) events can reach discharge rates of up to 30,000 m3 s−1 and run-out distances in excess of 200 km have been recorded during past events (Richardson and Reynolds, 2000). The occurrence of GLOFs has been increasing in the second half of the 20th century and individual events have resulted in serious death tolls and the massive destruction of mountain villages, water supply and hydropower infrastructure as well as agricultural land in different parts of the Himalaya (e.g., Watanabe and Rothacher, 1996; Yamada, 1998; Richardson and Reynolds, 2000). It has been recognized that the Himalayas are particularly threatened by GLOF events and UNESCO has, in fact, recently issued a strong warning regarding lake outburst hazards in this region.

In the future, glaciers will even more recede in response to climatic warming and the number and volume of potentially hazardous moraine-dammed lakes in the Himalayas will be increasing (Komori, 2008). Despite the severity of the risks, there is only limited knowledge on how, where and when GLOF events have occurred in the past and how and where they could take place in the future.

This task is therefore structured into the analysis of past, current and future glacial lake and GLOF events with the objective to provide crucial information for a cost-effective prevention, appropriate mitigation actions and adaptation. To this aim, we will apply an advanced setting of remote sensing, terrain analysis, glaciological, geomorphic and flood modeling techniques.

Detailed information on the past occurrence and spatial distribution (magnitude, frequency, reach, outbreak locations) of past GLOF events is important for a better understanding of evolution and impacts of hazardous lakes and GLOF events in the Indian Himalaya. Task 2.x will accordingly address the reconstruction of how, where and when GLOFs occurred in the past.

Remote sensing is a key technique for assessment of current and prediction of future glacial lake hazards in extremely remote regions such as the Indian Himalaya. Recent studies have demonstrated the potential of remote sensing for GLOF hazards (Huggel et al., 2002; Quincey et al., 2007). A strong link will also be provided to the recently started ESA project GlobGlacier to exploit synergies in glacier and glacial lake detection and assessment. Current glacial lakes will be assessed on a region-wide scale in terms of impacts from slope instabilities and rock and ice avalanches, and lake dam stability, as well as potential downstream flood paths.

For the assessment of GLOF hazards in the future, a combined approach of climate-linked glacier retreat models, subglacial topography assessment and slope destabilization will be applied (Frey et al., 2008), to allow for timely planning of prevention and mitigation actions.

Flood modelling will be based both on computationally rapid GIS-models (Huggel et al., 2003) and more complex dynamic flood and debris flow models such as FLO-2D (O’Brian, 2003), considering information from reconstructed data of past events (frequency, reach, flow heights) and current and future lake and GLOF characteristics and scenarios.

This combination of most advanced techniques will allow for support and implementation of remediation techniques and mitigation strategies to effectively reduce the massive risks of current and future GLOF events to population and infrastructure in the Indian Himalaya.

Work will be performed in collaboration with the Glaciology, Geomorphodynamics and Geochronology group at the University of Zurich, Switzerland (Dr. Christian Huggel) and the ESA project GlobGlacier (Dr. Frank Paul).