Simulations of future snow cover and discharge in Alpine headwater catchments

被引:148
作者
Bavay, Mathias [1 ]
Lehning, Michael [1 ]
Jonas, Tobias [1 ]
Loewe, Henning [1 ]
机构
[1] SLF Davos, WSL Inst Snow & Avalanche Res, CH-7260 Davos, Switzerland
基金
瑞士国家科学基金会;
关键词
climate change; catchment hydrology; water resources; flow regime; flooding; snow melt; ENERGY-BALANCE; CLIMATE-CHANGE; MODEL; SENSITIVITY; TRENDS; VARIABILITY; IMPACTS; RUNOFF;
D O I
10.1002/hyp.7195
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The snow cover in the Alps is heavily affected by climate change. Recent data show that at altitudes below 1200 In a.s.l. a time-continuous winter snow cover is becoming all exception rather than the rule. This would also change the timing and characteristics of river discharge in Alpine catchments. We present an assessment of future snow and runoff in two Alpine catchments, the larger Inn catchment (1945 km(2)) and the smaller Dischma catchment (43 km(2)), based on two common climate change scenario (IPCC A2 and B2 (IPCC, 2007)). [etc]. The changes in snow cover and discharge are predicted using Alpine3D, it model for the high-resolution simulation of Alpine surface processes, in particular snow, soil and vegetation processes. The predicted changes in snow and discharge are extreme. While the current climate still Supports permanent snow and ice on the highest peaks at altitudes above 3000 in a.s.l., this zone Would disappear under the future climate scenarios. The changes in snow cover could be summarized by approximately shifting the elevation zones down by 900 in. The corresponding changes in discharge are also severe: while the current climate scenario shows a significant contribution from snow melt until middle to late summer, the future climate scenarios Would feature it much narrower snow melt discharge peak ill spring. A further observation is that heavy precipitation events in the fall would change from mainly snow to mainly rain and would have a higher probability of producing flooding. Future work is needed to quantify the effect of model uncertainties on such predictions. Copyright (C) 2008 John Wiley & Sons, Ltd.
引用
收藏
页码:95 / 108
页数:14
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