A study was conducted considering extreme floods in Nepal from 1980 to 2015 and showed that most major floods occur during the monsoon season, especially in July and August, with August being the month with the highest number of extreme floods. The research emphasizes that the majority of the largest floods occur from mid-June to early September. This information aids Nepalese authorities in planning dynamic resource allocation, disaster response, and effective flood management.

Climate change is rapidly altering Himalayan glaciers, affecting water resources. This study investigates the impact of changing air temperature, precipitation, and glacier configuration on streamflow in the Langtang River basin using a process-based glacio-hydrological model and bias-corrected reanalysis data. Results show increased runoff with current glacier conditions but decreased total streamflow under future deglaciation scenarios, emphasizing the need for adaptation strategies.

This study explores the potential of integrating data science models to enhance the predictive capacity of a theory-guided glacier hydrological model for improved river discharge simulations in the Himalayan basins. By combining data science and physical process models, the study addresses the limitations inherent in each approach.

The Himalayan river basins have complex terrain and lack detailed hydrological and meteorological information. This has motivated us to develop a fast and distributed model named PyGDM to simulate the hydrology of this region, which is home to both glaciers and snow. PyGDM is good at simulating glacier and snow melt. Hence, the model is suitable for studying different aspects of the Himalayan region, such as the impact of climate change and hydropower scenarios.

Tree rings are important natural archives that provide information about tree age and also reveal past climate and hydrological events. The Nepal tree-ring width chronology network, including multiple tree species, revealed huge potential to reconstruct multi-centennial long hydro-climates in the central Himalayas. Streamflow reconstruction of Sinja Khola, Diware, over the past 300 years revealed interannual- to multi-decadal-scale flow variability, along with some long declining trends. 

During the last decades, a general increase in heavy rainfall events has caused changes in soil erosion rates and strongly affected the human activities in mountain areas. In this context, plot experiments carried out in southern Italy that involve the use of ¹³⁷Cs and ²¹⁰Pb_ex measurements indicated an increase in soil erosion rates during the last 15–20 years and suggest the use of this technique to detect climate change in mountain areas.

The paper proposes riparian tourism as a holistic and sustainable form of tourism that encompasses both consumptive and non-consumptive forms. It delves into creating a conceptual framework for riparian tourism, including cryo-tourism. This model centres around community ownership and stewardship, furthering robust institutional set-ups and active public-policy discourse. 

We have estimated hydropower potential in the two glacierized river basins of the Nepalese Himalayas. The Glacio-hydrological Degree-Day Model (GDM) was used with different geospatial criteria. In order to force the model simulation and to assess potential future hydrological regimes, a variety of climate variables were combined and used. The sensitivity of climate variables and their impact on hydropower potential were investigated with a combination of different climate variables.

Glacial lake outburst flood (GLOF) modeling of Tsho Rolpa showed that, even if the lake breaches by 20 m in 40 years (from 2021), there will be a sufficient lead time of more than 7 h for early warning and human evacuations in the downstream areas. However, precautionary measures such as community-based GLOF early-warning systems and mechanisms allowing close observation in the case of GLOF events should be established in GLOF-prone regions.

Visibility assessment is crucial for informed decision-making and disaster preparedness in mountainous regions due to snow-induced disasters. This paper presents an innovative approach using augmented reality (AR) to address this challenge. The Him-Drishti application harnesses the established correlation between snowfall intensity and visibility to create a predictive visibility simulation model. This study demonstrates the capacity of AR in disaster management and risk reduction.

In order to create a comprehensive map of landslide hazards for each specific location, it is essential to develop and integrate the spatial and temporal probabilities of landslides. This paper proposes a joint-probability framework that uses copula functions to generate a landslide hazard map for Wayanad District of Kerala, India, using multi-site rainfall data taking into account intensity and duration of rainfall.

On a hydropower field visit to Mustang, Nepal, I was surprised by the locals' comments about water scarcity, lack of snowfall and rising temperatures. This news hit me hard as a civil engineer focused on eco-friendly infrastructure. Even if structures are green, climate change severely affects them. Nepal ranked fourth in climate vulnerability and needs climate-resilient infrastructure. This paper highlights the destruction of Nepal's hydropower by climate change.

We show, for the first time, a comprehensive review of permafrost hazard research in High Mountain Asia (HMA) using literature published in Chinese, accessible through the China National Knowledge Infrastructure (CNKI) database.  The proposed review aims to focus only on High Mountain Asia, mainly territories in China. This review article will help to communicate permafrost hazards in the Chinese scientific literature to the English-speaking scientific community.