Moraine dams, impounding glacial lakes, are among the weak natural dams because of their slope, freeboard and composition. Glacial lake outburst floods occurring due to the failure of moraine dams are significant hazards for the valley downstream the failure, as they possess huge amount of hydraulic energy that can kill thousands and destroy infrastructures and riverine landscape. Also, the entrainment of debris to the flow from the breaching process and downstream channel may develop the flow into a much bigger disaster or even a series of hazard chain. Ice and rock avalanche or landslide, glacier calving, degradation of ice cores, earthquake and atmospheric events trigger the breaching phenomenon which generates a series of waves overtopping the dam or seepage causing the failure of the dam. Various approaches have been discussed in this review paper to produce an understanding of the failure mechanism of moraine dams: experimental works, empirical relationships, analytical solutions, and numerical modelling. No concrete experimental investigations and parametric solutions pertained to the failure mechanism of moraine dam is found in the review, but various empirical relationships are discussed and suitable approaches for numerical modelling are suggested as per the requirement of the task.

The failure of a natural or an artificial dam often leads to catastrophic flooding downstream. Studies have been conducted to investigate the mechanisms of single dam failure and the propagation of dam-break flood wave. However, little attention has been paid to the cascade failure of two or more sequential dams. In this article, consequences of a dam-break flood wave down a channel exerting pressure load on a downstream dam with different backwater effects were studied experimentally. Three typical flood patterns were observed for different downstream reservoir water depths. High precision pressure sensors were employed to measure the pressure load at different heights on the dam. Changes of the maximum pressure load were measured as the bed slope and the upstream and downstream reservoir water depths varied. An empirical formula was obtained by linear regression to predict the maximum pressure load. Additionally, a sinusoidal attenuation function was introduced to describe the time evolution of pressure load exerted on the downstream dam, and its parameters were determined using the measurement data in different cases.

The China–Pakistan Economic Corridor (CPEC) is one of the flagship projects of the One Belt One Road Initiative, which faces threats from water shortage and mountain disasters in the high-elevation region, such as glacial lake outburst floods (GLOFs). An up-to-date high-quality glacial lake dataset with parameters such as lake area, volume, and type, which is fundamental to water resource and flood risk assessments and prediction of glacier–lake evolutions, is still largely absent for the entire CPEC. This study describes a glacial lake dataset for the CPEC using a threshold-based mapping method associated with rigorous visual inspection workflows. This dataset includes (1) multi-temporal inventories for 1990, 2000, and 2020 produced from 30 m resolution Landsat images and (2) a glacial lake inventory for the year 2020 at 10 m resolution produced from Sentinel-2 images. The results show that, in 2020, 2234 lakes were derived from the Landsat images, covering a total area of 86.31±14.98 km² with a minimum mapping unit (MMU) of 5 pixels (4500 m²), whereas 7560 glacial lakes were derived from the Sentinel-2 images with a total area of 103.70±8.45 km² with an MMU of 5 pixels (500 m²). The discrepancy shows that Sentinel-2 can detect a large quantity of smaller lakes compared to Landsat due to its finer spatial resolution. Glacial lake data in 2020 were validated by Google Earth-derived lake boundaries with a median (± standard deviation) difference of 7.66±4.96 % for the Landsat-derived product and 4.46±4.62 % for the Sentinel-derived product. The total number and area of glacial lakes from consistent 30 m resolution Landsat images remain relatively stable despite a slight increase from 1990 to 2020. A range of critical attributes has been generated in the dataset, including lake types and mapping uncertainty estimated by an improved equation of Hanshaw and Bookhagen (2014). This comprehensive glacial lake dataset has the potential to be widely applied in studies on water resource assessment, glacial lake-related hazards, and glacier–lake interactions and is freely available at https://doi.org/10.12380/Glaci.msdc.000001 (Lesi et al., 2022).