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Projection of glacier runoff in Yarkant River basin and Beida River basin, Western China

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Hagemann,  S.
The Land in the Earth System, MPI for Meteorology, Max Planck Society;
Terrestrial Hydrology, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Citation

Zhang, S., Gao, X., Zhang, X., & Hagemann, S. (2012). Projection of glacier runoff in Yarkant River basin and Beida River basin, Western China. Hydrological Processes, 26, 2773-2781. doi:10.1002/hyp.8373.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-E95A-D
Abstract
The retreat of mountain glaciers and ice caps has dominated the rise in global sea level and is likely to remain an import component of eustatic sea-level rise in the 21st century. Mountain glaciers are critical in supplying freshwater to populations inhabiting the valleys downstream who heavily rely on glacier runoff, such as arid and semi-arid regions of western China. Owing to recent climate warming and the consequent rapid retreat of many glaciers, it is essential to evaluate the long-term change in glacier melt water production, especially when considering the glacier area change. This paper describes the structure, principles and parameters of a modified monthly degree-day model considering glacier area variation. Water balances in different elevation bands are calculated with full consideration of the monthly precipitation gradient and air temperature lapse rate. The degree-day factors for ice and snow are tuned by comparing simulated variables to observation data for the same period, such as mass balance, equilibrium line altitude and glacier runoff depth. The glacier area-volume scaling factor is calibrated with the observed glacier area change monitored by remote sensing data of seven sub-basins of the Tarim interior basin. Based on meteorological data, the glacier area, mass balance and runoff are estimated. The model can be used to evaluate the long-term changes of melt water in all glacierized basins of western China, especially for those with limited observation data. © 2011 John Wiley & Sons, Ltd.