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Abstract
We developed a spatially distributed conceptual melt and runoff model able to cope with debris covered glacier parts. Subdebris melt was calculated based on empirical equations derived from field observations. The model was applied at the nylchek glaciers. While runoff from outhern nylchek flows directly into nylchek iver, runoff from orthern nylchek is blocked by outhern nylchek and forms ake erzbacher. This lake is drained frequently by outburst floods. To calibrate the model, a multi‐algorithm, genetically adaptive multi‐objective method () was used. Daily runoff observations from nylchek iver as well as glacier mass balance gradients from other glaciers in the ian han were used as objective functions in three split samples. Runoff simulations yielded ash–utcliffe coefficients mostly higher than 0.9, and the mass balance gradients were simulated in an acceptable range. The results of the different split samples vary considerably. Considering the used objective functions and additional data such as the equilibrium line altitude, we chose the most promising parameter set to calculate the filling of ake erzbacher. This analysis indicated answers to several questions concerning the hydrological system of the lake. Apart from calving at the ice dam formed by outhern nylchek glacier, the lake seemed so be filled predominantly by meltwater from orthern nylchek glacier. The lake has a permanent runoff, also during the filling process. After the outburst, the channels seemed to be closed quickly.
Acknowledgements
The authors thank Jasper Vrugt for kindly providing his AMALGAM algorithm for model calibration. Gleb Glazirin is acknowledged for his help in obtaining data from the Inylchek glaciers. Thanks are also due to the German Research Centre for Geosciences (GFZ) and the Central‐Asian Institute for Applied Geosciences (CAIAG) for organizing the expedition to the Inylchek glaciers in 2011, and to Thomas Fischer for his great help in the field. Hans‐Ulrich Wetzel (GFZ) provided the actual maps of Inylchek used for interpretation. Further, we are thankful to our TU Dresden project partners (Aksu‐Tarim RS, Code BO 3199/2‐1) for the processing of KH‐9 Hexagon images and SRTM3 data. The work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the framework of the AKSU‐TARIM project bundle (project HA 5061/2‐1). Susan Braun‐Clarke edited the English.
Additional information
Notes on contributors
Elisabeth Mayr
Elisabeth Mayr, Department of Geography, Ludwig Maximilians University, Luisenstr. 37, 80333 Munich, Germany
E‐mail: [email protected]
Martin Juen
Martin Juen, Christoph Mayer, Commission for Geodesy and Glaciology, Bavarian Academy of Sciences and Humanities, Alfons‐Goppel‐Str. 11, 80539 Munich, Germany
Ryskul Usubaliev
Ryskul Usubaliev, Department of Climate, Water and Natural Resources, Central‐Asian Institute for Applied Geosciences, Timur Frunze Rd. 73/2, 720027 Bishkek, Kyrgyzstan
Wilfried Hagg
Wilfried Hagg, Department of Earth and Environmental Sciences, Università degli Studi di Milano‐Bicocca, Piazza della Scienza, n. 1, 20126 Milan, Italy
