Several studies have concluded that mountainous countries such as Nepal are more vulnerable to climate change; thus, a changing climate should have a significant impact on crop yields. This work aims to explore the impact of climate change on major crop yields in the mountainous parts of Nepal and to determine their relationships based on a regression model between historical climatic data and yield data for food crops. The study starts with an analysis of the last 30 years of climatic data from Lamjung district. Mann-Kendall and Sen’s Slope methods have been used for the trend analysis and quantification. The results showed an increase in temperature of approximately 0.02 °C to 0.07 °C per year in different seasons and a mixed trend in precipitation. Although there was no significant impact of the climate variables on the yields of all crops, the regression analysis revealed negative relationships between maize yield and summer precipitation and between wheat yield and winter minimum temperature, and a positive relationship between millet yield and summer maximum temperature.

Background: In the last two decades, Nepal has experienced an increase in both forest fire frequency and area, but very little is known about its spatiotemporal dimension. A limited number of studies have researched the extent, timing, causative parameters, and vulnerability factors regarding forest fire in Nepal. Our study analyzed forest fire trends and patterns in Nepal for the last two decades and analyzed forest fire-vulnerability risk based on historical incidents across the country. Results: We analyzed the spatial and temporal patterns of forest fires and the extent of burned area using the Mann-Kendall trend test and two machine-learning approaches maximum entropy (MaxEnt), and deep neural network (DNN). More than 78% of the forest fire burned area was recorded between March and May. The total burned area has increased over the years since 2001 by 0.6% annually. The forest fire-vulnerability risk obtained from both approaches was categorized into four classes—very high, high, low, and very low. Conclusions: Although burned area obtained from both models was comparable, the DNN slightly outperformed the MaxEnt model. DNN uses a complex structure of algorithms modeled on the human brain that enables the processing of the complex relationship between input and output dataset, making DNN-based models recommended over MaxEnt. These findings can be very useful for initiating and implementing the most suitable forest management intervention.

As in many other parts of the world, the urban areas of the South Asian region are increasingly expanding. While cities today are the heart of commercial, technological and social development, they are also vulnerable to a variety of natural and anthropogenic threats. The complex urban infrastructure, and the ever-expanding population in cities, exacerbate the impacts of climate change and increase the risk of natural hazards. Throughout history, various hydrological disasters including floods, tidal surges, and droughts, and non-hydrological disasters such as earthquakes, landslides, and storms have led to catastrophic social, economic and environmental impacts in numerous South Asian cities. Disaster risk reduction is therefore central to ensure sustainability in urban areas. Although Nature-based Solutions (NbS) are identified as a promising strategy to reduce risk and increase resilience, there appears to be a lack of evidence-based approaches. NbS are measures that can be practiced to obtain benefits of nature for the environmental and community development through conserving, managing, and restoring ecosystems. Against this backdrop, the South Asian cities provide opportunities to evaluate capacities for achieving Nature-based Resilience (NbR) through NbS. This study documents insights from five cities of five different countries of the South Asian region which are subjected to a wide array of disasters: Barishal (Bangladesh), Phuentsholing (Bhutan), Gurugram (India), Kathmandu (Nepal), and Colombo (Sri Lanka). The primary objective of this study is to provide evidence on how NbS are being practiced. Thus, some success stories in cities under consideration are highlighted: restoration of natural canals through integrated development plans and community participation (Barishal), concepts of Gross National Happiness (GNH) and minimal nature interventions (Phuentsholing), “Greening cities’’ including eco-corridors, vegetation belts, biodiversity parks (Gurugram), proper land use planning aims at different disasters (Kathmandu), and wetland restoration and management with multiple benefits (Colombo). These cases could therefore, act as a “proxy” for learning from each other to prepare for and recover from future disasters while building NbR.

This study tried to understand the mountainous households’ perception of climate change and its impacts on food security in the Lamjung district of Nepal. The study attempted to find out changes in households food security and daily activities in the face of climate change for the last twenty years. The study started with the 150 household surveys along with participatory rural appraisal to understand the climate change perception of local people and its impact on dimensions of food security. Households expressed different levels of perception in terms of climate change on food security. The result shows that most of the mountainous households experienced increased temperature, less rainfall in winter, an increasing number of natural disasters and the emergence of insects for the last twenty years. They perceived the role of climate change in decreased crop production, decreased dairy products and increased household work. The situation of food security is likely to be more vulnerable to climate change in the future. It was also observed that households have been using different autonomous adaptation measures, such as high yielding crop varieties, enhanced irrigation systems and fertilizers, to cope with the changing climate. Finally, the study recommended policy instruments to enhance food security in the mountainous region amidst changing climate.

The COVID-19 pandemic has exceeded over sixty-five million cases globally. Different approaches are followed to mitigate its impact and reduce its spreading in different countries, but limiting mobility and exposure have been de-facto precautions to reduce transmission. However, a full lockdown cannot be sustained for a prolonged period. An evidence-based, multidisciplinary approach on risk zoning, personal and transmission risk assessment in near real-time, and risk communication would support the optimized decisions to minimize the impact of coronavirus on our lives. This paper presents a framework to assess the individual and regional risk of COVID-19 along with risk communication tools and mechanisms. Relative risk scores on a scale of 100 represent the integrated risk of influential factors. The personal risk model incorporates age, exposure history, symptoms, local risk and existing health condition, whereas regional risk is computed through the actual cases of COVID-19, public health risk factors, socioeconomic condition of the region, and immigration statistics. A web application tool (http://www.covira.info) has been developed, where anyone can assess their risk and find the guided information links primarily for Nepal. This study provides regional risk for Nepal, but the framework is scalable across the world. However, personal risk can be assessed immediately from anywhere.