Understanding ice loss and glacial lake expansion in the Bhutanese Himalaya

“从1990年到2010年，冰川湖面积平均增长了20.8%。冰前湖的发展是一个特别重要的加重因素，在质量损失，这个变量还没有包括在目前的冰损失预测，并可能导致在“风险地区”的突发洪水危险增加。喜马拉雅山脉的冰前湖可能会通过产犊和海底融化导致锋面冰损失的快速加速。在不丹，对冰川对冰前湖发育的反应的观测有限，对该地区湖泊造成的质量损失的长期影响受到很大的限制，而且变化很大。研究表明，对于加拿大的湖泊终止冰川，崩解损失占总质量损失的10 - 25%，在特殊的夏季增加49%。该研究将利用开放全球冰川模型（OGGM），这是一个基于Python的开源冰川模型，可以模拟任何大小冰川的历史和未来质量平衡。该模型已被证明是有效的，在喜马拉雅山，也可以将正面消融参数，使湖泊的发展和崩解的意义被理解。Yang等人（2022年）使用OGGM对不丹四个冰期的历史冰川退缩进行了建模，在一系列不同的历史气候情景下校准了模型的温度敏感性和非气候参数的剩余偏差，以实现模型准确性，但该研究没有测试产犊参数。在这项研究中，必须考虑到碎片覆盖;不丹64%的冰川面积被归类为“碎片覆盖”，此外，许多这些冰川的坡度很低，增加了冰前湖退缩后发展的可能性。重要的是将碎片覆盖纳入我们的质量平衡模型，以进一步了解气候变化将如何影响Lunana地区和/或更广泛地区的冰川。研究还发现，量化碎片覆盖对冰的温度敏感性的影响一直是精确模拟冰川退缩的最大挑战之一;因此，应通过实地观察校准这一参数。碎片对产犊过程的影响也很少有研究，这对于了解亚洲高山地区变薄率与向浮力产犊过渡之间的关系可能很重要。"

"Glacial lake area grew on average by 20.8% from 1990 - 2010. Proglacial lake development is a particularly important aggravating factor in mass loss; this variable has not been included in current ice loss projections and may result in increasing outburst flood hazard in 'at risk regions'. Proglacial lakes in the Himalayas can lead to the rapid acceleration of frontal ice loss through calving and sub-marine melt. In Bhutan, observations of the glacial response to proglacial lake development have been limited, and the long-term implications for lake driven mass loss in the region are poorly constrained and have been shown to be highly variable. Calving loss was shown to account for 10 - 25% of total mass loss for a lake terminating glacier in Canada, with an increase of 49% during exceptional summers.The study will utilise the Open Global Glacier Model (OGGM), an open source glacier model based in Python that can simulate historical and future mass-balance of glaciers of any size. The model has been shown to be effective in the Himalaya and can also incorporate frontal ablation parameters to allow the significance of lake development and calving to be understood. Yang et al. (2022) used the OGGM to model historical glacier retreat in Bhutan from four glacial stages under a suite of different historical climate scenarios calibrating the models temperature sensitivity and the residual bias for non-climatic parameters to achieve model accuracy, however this study did not test calving parameters. Debris cover must be considered in this study; 64% of glacier area in Bhutan is classified as 'debris covered', furthermore, many of these glaciers are low gradient, increasing the likelihood of proglacial lake development following retreat. It is important to incorporate debris cover into our mass balance models, to further understand how climate change will affect the glaciers in the Lunana region and/or wider region. Studies have also found that quantifying the effect of debris cover on the temperature sensitivity of ice has been one of the biggest challenges for accurately modelling glacial retreat; this parameter should therefore be calibrated through field observations. The effect of debris on calving processes has also seen little research and may be important in understanding the relationship between thinning rates and the transition to buoyant calving in High Mountain Asia."