Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

On 7 February 2021, a massive flood occurred in the river Dhauliganga that damaged two hydroelectric stations, five bridges and trapped 100 to 150 casualties who are feared dead. Some evidence has been indicated that caused by a landslide, an avalanche, or a portion of the Nanda Devi glacier that broke off early in Uttarakhand's Joshimath area Chamoli district. The magnitude of the flood caused by the collapse was so large that it far exceeds the collapse itself. Two potential explanations were proposed to explain: the frictional heating of the avalanche may result in high temperatures in the sliding face, which is sufficient for ice and frozen sediments melting to occur in the path. The high-water content generated debris flows that enhanced the mobility of flowing. Another explanation is that it could be related to a glacial lake outburst flood or a temporary lake that eventually broke through its debris dam and poured down the valley. In any case, the collapse materials hold very high moisture content and fast mobility. In this study, a three-dimensional Smoothed Particle Hydrodynamics (SPH) method is adopted to model the flow-like Uttarakhand slides and to explore the physical processes during this event. The SPH is an adaptive, mesh-free, Lagrangian method that simulates free surfaces, moving interfaces, and large flow deformations. A non-Newtonian debris flow model, the Bingham rheological relationship, was incorporated into the SPH framework to describe source materials' characteristics. Besides, the whole flow processes of the flow-like Uttarakhand slides across the 3D terrain are represented. The time history of the velocity, acceleration, and forces were obtained from modelling to analyze the landslide dynamics.