Glacial lake outburst floods threaten China-Nepal connectivity: Synergistic study of remote sensing, GIS and hydrodynamic modeling with regional implications.

Holistic study of glacial lakes and glacial lake outburst floods (GLOFs) in the strategically important China-Nepal transportation corridors is imperative for regional connectivity and disaster risk reduction. This study focuses on four China-Nepal transportation corridors, namely Chentang-Kimathanka, Zhangmu-Kodari, Keyrung-Kathmandu and Taklakot-Hilsa from east to west in the Himalayan region. Within a remote integrated framework, we present the latest high-resolution inventory of glacial lakes, assess their decadal spatio-temporal changes (1992-2022), identify potentially dangerous glacial lakes, and apply hydrodynamic model to assess downstream impacts of possible GLOFs along the study area. The results show 2688 glacial lakes (≥0.001 km2) with a total area of 116.10 ± 8.53 km2 over the study area in 2022. Glacial lakes exhibited spatiotemporal heterogeneity in expansion, with overall expansion of 32 % during 30 years. Keyrung-Kathmandu corridor, among others, was assessed with high GLOF susceptibility. Furthermore, hydrodynamic modeling of four highly dangerous lakes in each transportation area reveals that GLOFs have cross-border effects, impacting ∼103 km of China-Nepal highway, 103 bridges, two major dry ports and 3301 buildings in both countries. Based on these findings, we emphasize the joint efforts of both countries for integrated disaster management for smooth connectivity between two countries and saving downstream population through joint cooperation from central to local government levels by initiating artificial lake lowering, developing cross-border early warning systems and cooperation. This study is valuable for presenting a synergistic study of glacial lakes and GLOF for informing decision- and policy-makers of both China and Nepal for a joint approach to disaster mitigation.

Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal.

Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.