Project Details
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Modelling of melt and runoff in a basin with debris covered glacier parts in the upper Aksu catchment, northwest China

Subject Area Physical Geography
Term from 2010 to 2015
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 100348997
 
Final Report Year 2018

Final Report Abstract

Glacier changes caused by climate change have a high impact on runoff generation, especially in arid regions, which tend to have high contributions of glacier melt to total runoff. Hydrological models are suitable tools to quantify these impacts and to create future projections of water availability. The debris covers on the ablation areas of glaciers in many regions, e.g. Central Asia, complicates their application. This debris cover has high influence on the melt rates of the ice below and needs to be considered in the modeling of melt and runoff. In the AKSU-TARIM-MELT project, a conceptual hydrological model for melt and runoff simulation in catchments with debris covered glaciers was developed and applied. Based on the conceptual, semi-distributed runoff model HBV-ETH, a fully distributed accumulation and ablation routine was set up. Snowfall was redistributed using a morphological-statistical approach based on curvature and slope angle, while ablation is calculated using potential clear-sky solar radiation additionally to air temperature. To test its reliability, the model was applied at Vernagtferner, Austria, a catchment with a large set of observational data. The model was able to simulate both, glacier mass balance and runoff, in a satisfactory way. The numerous point measurements of annual and winter mass balance were used to validate the spatial pattern of simulated accumulation and ablation. This analysis revealed a good representation of the measured data by the model. Also on Vernagtferner, the influence of lithology and grain size on sub-debris melt rates was investigated using artificial debris layers. The thermal conductivity was found to be the most suitable parameter to represent the thermal properties of the debris. Moreover, it could be shown that for the estimation of debris cover thickness from remote sensing data, field measurements are needed to derive an empirical relationship between surface temperature and debris thickness. A model for sub-debris ablation using field data input and remote sensing information was developed at Koxkar glacier, China and on the Inylchek glaciers, Kyrgyzstan. It could be shown that ice cliffs play a significant role but not as substantial as stated by other authors. The ablation model for debris covered glacier parts was implemented into the melt routine of the newly developed runoff model. Because this melt routine is based on empirical degree-day factors, it was necessary to develop an approach to preserve the calibration ability of the model. The model was applied at the Inylchek glaciers in the Tian Shan, Kyrgyzstan. Due to the particular runoff situation concerning the periodic filling and outburst of Lake Merzbacher, further model modifications were necessary. For the analysis of the runoff situation, the model itself could be used. The existence of a permanent leakage of Lake Merzbacher could be confirmed by the simulation results. For automatic model calibration, the evolutionary calibration algorithm AMALGAM was applied. To improve the simulation quality of the glacier mass balance, the mass balance gradient of nearby glaciers was used as objective function additional to runoff. The parameter sets obtained by the algorithms achieved good simulation results. To examine the influence of climate change on melt and runoff in the catchment of the Inylchek glaciers, the model was driven by climate scenarios of a baseline and a future scenario (19771 to 2000 and 2071 to 2100). The future scenario is based on the SRES A1B scenario. The simulation revealed a considerable increase of runoff of 112%. This increase is primarily caused by the enlargement of the ablation area and intensified melt rates due to the expected temperature increase. The presented results prove that runoff from debris covered glaciers can be successfully simulated using the newly developed conceptual hydrological model.

Publications

  • 2013. Abflussmodellierung am Vernagtferner – warum auch einfache Modelle von detaillierten Beobachtungsdaten profitieren. Zeitschrift für Glaziologie und Glazialmorphologie 45/46: 169-183
    Mayr, E. and W. Hagg
  • 2013. Einsatz einer Thermalkamera und von Strahlungssensoren zur Oberflächenklassifizierung am Vernagtferner. Surface debris classification at Vernagtferner using temperature observations from a thermal camera and radiation sensors. Zeitschrift für Gletscherkunde und Glazialgeologie, 45/46, 185-201
    Juen, M., Mayer, C., Lambrecht, A., Eder, K., Stilla, U. and Wirbel, A.
  • 2013. Glacier and runoff changes in the Rukhk catchment, upper Amu-Darya basin until 2050. Global and Planetary Change 110: 62-73
    Hagg, W., Hoelzle, M., Wagner, S., Mayr, E., Klose, Z.
    (See online at https://doi.org/10.1016/j.gloplacha.2013.05.005)
  • 2013. Impact of varying debris cover thickness on catchment scale ablation: A case study for Koxkar glacier in the Tien Shan. The Cryosphere Discuss., 7, 5307-5332
    Juen, M., Mayer, C., Lambrecht, A., Haidong, H. and Shiyin, L.
    (See online at https://doi.org/10.5194/tcd-7-5307-2013)
  • 2013. Influence of annual and winter mass balance on the calibration results of a spatially distributed conceptual hydrological model. Journal of Hydrology 478, 40–49
    Mayr, E., Hagg, W., Mayer, C., and L. Braun
    (See online at https://doi.org/10.1016/j.jhydrol.2012.11.035)
  • 2013. Thermal properties of a supraglacial debris layer with respect to lithology and grain size. Geografiska Annaler: Series A, Physical Geography, 95, 197-209
    Juen, M., Mayer, C., Lambrecht, A., Wirbel, A. and Kueppers, U.
    (See online at https://doi.org/10.1111/geoa.12011)
  • 2014. Modeling Runoff from the Inylchek glaciers and Filling of Ice-Dammed Lake Merzbacher, Central Tian Shan. Geografiska Annaler A
    Mayr, E., Juen, M., Mayer, C., Usubaliev, R. and W. Hagg
    (See online at https://doi.org/10.1111/geoa.12061)
 
 

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