Abstract：
Retrieval of glacier ice thickness is extremely important for monitoring water resources and predicting glacier dynamics and changes. The inter-annual glacier ice thickness observations (more than 5 years) exploit the glacier mass changes. Ice thickness is one of the important parameters to predict the future sea-level rise. Without adequate knowledge and precise information of glacier ice thickness distribution, future sea-level changes cannot be accurately assessed. In this study, we use an existing flow model to estimate the ice thickness of the High Mountain Asia (HMA) glaciers, using remote sensing techniques. The glacier ice velocity is one of the significant parameters in the Laminar flow model to retrieve the ice thickness. The glacier ice velocity is derived by utilizing the Differential SAR Interferometry (DInSAR) technique. The most optimum DInSAR data (ALOS-2/PALSAR-2) is used for estimating the ice velocity of the HMA glaciers. The ice thickness is mainly estimated for five different states in the HMA region, namely Himachal Pradesh, Uttarakhand, Sikkim, Bhutan, and Arunachal Pradesh. Most of the states are observed with a mean ice thickness of 100 m. Five benchmark glaciers (Samudra Tapu, Bara Shigri, Chhota Shigri, Sakchum, and Gangotri glaciers) are also selected for validating our results with the existing thickness information. The issues related to velocity-based ice thickness inversion are also emphasized in this study. The high-velocity rate due to the influx of melting water from adjacent glaciers causes an increment in the flow rate. This abnormal velocity derives erroneous ice thickness measurements. This is one of the major problems to be considered in the velocity-based thickness-derived procedures. Finally, the investigation suggests the inclusion of the velocity influencing parameters in the physical-based models for an accurate ice thickness inversion.
摘要：
冰川冰层厚度的反演对于监测水资源和预测冰川动态和变化极为重要。年际冰川冰厚观测（超过5年）利用了冰川质量的变化。冰层厚度是预测未来海平面上升的重要参数之一。如果没有足够的知识和精确的冰川厚度分布信息，未来的海平面变化无法准确评估。在这项研究中,我们使用现有的流动模型来估算亚洲高山（HMA）冰川的冰厚，使用遥感技术。冰川冰速度是层流模型中反演冰厚度的重要参数之一。冰川冰速度是通过利用差分SAR干涉测量（DInSAR）技术得出的。最佳DInSAR数据（ALOS-2/PALSAR-2）用于估算HMA冰川的冰速度。冰层厚度主要是针对HMA地区的五个不同州进行估算的，即喜马al尔邦,北阿坎德邦，锡金,不丹,和阿鲁纳恰尔邦.大多数州的平均冰厚为100m。五个基准冰川（SamudraTapu，BaraShigri,ChotaShigri,Sakchum,和Gangotri冰川）也被选择使用现有的厚度信息来验证我们的结果。本研究还强调了与基于速度的冰厚反演有关的问题。由于来自相邻冰川的融化水的流入，高速速率导致流速增加。这种异常速度导致错误的冰厚度测量。这是基于速度的厚度推导程序中要考虑的主要问题之一。最后,研究建议在基于物理的模型中包含速度影响参数，以进行精确的冰厚反演。
