Debris from a large landslide is heaped amid a damaged community in western Nepal
A July 2020 landslide damaged a community in the Bajhang District in western Nepal. Small, remote communities like this one need accurate information, effective communications, and advance planning to prepare for and recover from natural disasters. Credit: Biplob Rakhal

In recent decades, Nepal’s communities, infrastructure, ecosystems, and public health have faced increasing risks from natural hazards like landslides and floods. Layering climate change effects onto existing climate variability, seismically active geology, and expansive human activities increases the impacts of these hazards.

For Nepal’s local authorities and residents to assess risk and prepare accordingly, they need credible resources to help translate risk information from the national scale to the local scale. Here we focus on efforts to derive a multihazard risk index that is relevant to stakeholders at the local level. We also outline steps necessary to help communities move beyond merely recovering from disasters and to build infrastructure that improves their resilience and adaptability. Such measures will help communities prepare to avoid, mitigate, and adapt to the effects of natural hazards in the coming decades.

Diversity and Danger

The central Himalayan nation of Nepal is home to an abundance of natural resources and biological diversity, with climates and physical environments ranging from tropical in the country’s southern low plains to temperate in the Middle Hills to alpine amid the northern high mountain peaks.

Effective and efficient implementation of risk management strategies requires local planning as well as coordinated efforts among federal, provincial, and local stakeholders to share resources.

However, this region is also home to a diversity of natural hazards. Avalanches, floods, landslides, and torrential monsoon rainfall often occur at the same time, amplifying adverse consequences. For example, prolonged rainfall in August 2014 induced a catastrophic landslide in northern Nepal. Debris from the landslide formed an earthen dam 55 meters tall that blocked the Sunkoshi River [Van der Geest, 2018]. The combination of the landslide and the ensuing flooding killed 156 people, submerged dozens of houses, and destroyed sections of the highway linking Nepal and China, disrupting cross-border trade revenue. These events also damaged hydropower infrastructure, reducing Nepal’s electric energy generation by about 10% and causing electrical power outages in the capital and elsewhere in the country.

The effects of the 2014 landslide were felt through much of Nepal, but most natural hazards are highly local in their impacts. For instance, damages from the 2008 Koshi flood, 2012 Manaslu avalanche, 2013 Boje landslide, 2016 Dharka landslide, and 2017 Saptari flood were more localized. Effective and efficient implementation of risk management strategies, therefore, requires local planning. Further, implementing these strategies demands coordinated efforts among federal, provincial, and local stakeholders to share resources that are appropriate on the basis of individual communities’ characteristics. Nepal’s national policy for disaster risk reduction and its strategic action plan for 2018–2030 are a step toward this direction.

Understanding Risk Drivers

The terms risk, hazard, exposure, and vulnerability are often used interchangeably, but they refer to different concepts. Hazard refers to the nature, magnitude, and probability of harmful events. Exposure refers to the population and value of assets potentially affected by hazardous events. Vulnerability characterizes how sensitive exposed people and assets are to a given hazard. Risk represents interactions among hazards, exposures, and vulnerabilities.

Sound understanding of these risk drivers is important in implementing policy measures for risk reduction. Policymakers, for example, use risk indexes—which distill detailed assessments of hazard likelihoods and impacts into easier-to-digest outputs—to identify where risk hot spots are and where priority funding is needed. They then make decisions on the basis of existing capacities to combat likely hazards and varying vulnerabilities of different communities.

Computing risk indexes at local scales requires historical records of weather-related disasters and exposure. But the challenges of acquiring accurate, complete, and comparable records are multifold, especially in a developing country.

Whereas in developed countries, like the United States, most disaster data are collected and organized through official channels—with only limited integration of highly localized reports—in developing countries like Nepal, databases compiling information on weather-related disasters typically rely on information from many sources apart from official sources. A central database usually acquires data at the community level through interpersonal connections, local news portals, and information shared by acquainted individuals. Because these information sources are remote and sometimes lack the ability to communicate beyond their immediate communities, these reports are heterogeneous, and some incidents, casualties, and damage to properties go unreported or underreported.

Typically, investments and investment strategies related to natural hazards in developing countries focus more on disaster recovery than on building adaptive capacity in communities.

If the local-level information collected in Nepal could be formalized, however, it could be very helpful for assessing local risks. But data sets collected from informal and local reporting are not sorted into categories on the basis of, for example, demographics, economic status, the magnitude of weather events, or damage scales. This lack of sorting makes it more difficult to synthesize data and to develop the robust risk indexes needed to devise locally targeted resilience strategies.

The most important challenge is the lack of system architecture at the local level. System architecture refers to digital and computing infrastructure; standards and regulations; and the means to coordinate groups of decisionmakers, stakeholders, governing units, and members of the public. A well-functioning system architecture supports database maintenance, dissemination of information, and the development of adaptation strategies.

Efforts to overcome these challenges are necessary to prepare for disasters in advance. Typically, though, investments and investment strategies related to natural hazards in developing countries focus more on disaster recovery than on building adaptive capacity in communities. The Nepal government, for instance, allocated more than $11 million in 2020 for disaster risk management in its federal budget (under “Rescue, Relief and Rehabilitation Expense”). However, there is no specific guideline in the budget to distinguish expenses for recovery from disaster preparedness. Considering the trends of climate and disasters affecting the country, this focus must shift.

An Increasingly Urgent Need

The number of weather-related disasters affecting Nepal is growing, with increasing trends in floods and landslides being especially notable (Figure 1). Amid these trends, there is also an increasing number of disaster-related fatalities, underscoring the urgent need for adaptation strategies to cope with growing risk at community levels.

Fig. 1. Numbers of disaster events and associated fatalities (deaths and missing people) in Nepal each year from 1970 to 2019 are shown here.

Whereas upper Himalayan regions of the country are more prone to snow or glacier avalanches, the mid-Himalayas are mostly affected by landslides, and the southern region is more susceptible to floods (Figure 2). However, a lot of communities across Nepal are exposed to risk from multiple hazards, including many in upper Himalayan districts, which are typically of lower socioeconomic status than those in the southern region and are thus more vulnerable to risks from extreme events. A future of more frequent extreme events will likely affect these districts disproportionately if policymakers do not immediately prioritize them for short-term disaster recovery support as well as long-term adaptation benefits.

Fig. 2. Mapping numbers of reported incidents of avalanches, floods, heavy rainfall events, and landslides from 2011 to 2019 shows differences in natural disaster risks faced by communities in various regions of Nepal.

To help assess climate risks, prioritize responses, and create adaptation strategies for more frequent or severe events in the future, we have computed a climate risk index (CRI) for Nepal, following the computational approach taken by Eckstein et al. [2019]. Our CRI encapsulates regional levels of exposure and vulnerability to natural, weather-related hazards. The index is based on analyses of reported past events that caused either economic losses or fatalities and does not include weather events without associated reported economic losses or fatalities. As seen in Figure 3, districts most at risk (lower CRI values in dark red) are mainly concentrated in the western part of the country, though several high-risk districts are located in the east of the country as well.

We considered various indicators in the computation of the CRI, weighting them as indicated in Eckstein et al. [2019]: the number of fatalities (determined on the basis of death and missing persons records), number of fatalities per 100,000 population, losses in millions of U.S. dollars, and losses as a proportion of gross domestic product per capita. Data came from the Nepal Disaster Risk Reduction Portal, the most comprehensive data set currently available in Nepal at the district scale (Figure 3).

Fig. 3. Ranking categories for 74 districts in Nepal according to a recently developed climate risk index (CRI) based on data from 2011 to 2019 are shown here (no data were available for Jumla).

CRI values, and hence the rankings of districts with respect to different indicators, change over time as a result of not only the absolute impacts of extreme weather events but also economic and population growth or decline. In Nepal, updates to the CRI could occur after each population census is undertaken, typically every 10 years.

Practical Applications of the CRI

The localized risk assessments that the climate risk index provides represent a useful tool to help plan risk management.

The localized risk assessments that the CRI provides represent a useful tool to help plan risk management, which generally falls into two categories: mitigation and adaptation.

Mitigation mainly consists of actions taken to prevent or reduce risk to life, property, social and economic activities, and natural resources from natural hazards before they happen. Such measures can involve land use practices, flood plain zoning, and engineering design codes for infrastructure. For instance, avoiding development in landslide- and flood-prone areas through planning and zoning ordinances can save money in construction and reduce loss of life and damage to property.

Adaptation involves strategies to reduce negative impacts of extreme events when they do occur by reducing the associated hazards, exposures, and vulnerabilities. Communities’ adaptation to natural hazards often requires both physical protection and relocation, with particular attention to preserving evacuation routes, as well as regulating risk through structural remedies (e.g., reservoirs and levees) and nonstructural means (e.g., insurance, buyouts, and resettlement).

The CRI distills large volumes of data into a straightforward tool for comparing varying types and levels of risk across Nepal, thus assisting policymakers in prioritizing and allocating resources equitably to enhance adaptation and mitigation plans. It can also alert emergency managers to update emergency operation plans and encourage communities to adopt enhanced property and land management standards.

Risk Communication Challenges in Developing Countries

Effective risk communication with and among decisionmakers and stakeholders is essential to making informed decisions. Several factors make effective risk communication to vulnerable communities in Nepal particularly challenging. Communication and transportation infrastructure are underdeveloped, and well-trained communications specialists on the ground are scarce. Furthermore, literacy rates are low, and there is inadequate information flow among residents, local governments, and federal authorities.

Reliable dissemination of risk information to diverse populations often requires practice-oriented risk communication guidelines.

Nepal’s Department of Hydrology and Meteorology issues technical information about flood hazards. However, there is a need for more broadly accessible information that avoids statistics-based warnings of risks and instead describes practical and actionable information emphasizing the importance of associated risk. Consider, as an example, the dissemination of short-duration heavy rainfall forecasts to the public. In addition to providing rainfall intensities and frequencies, these forecasts can include location-specific information about potential flash flooding and impacts on flood control structures, homes, and businesses.

Reliable dissemination of risk information to diverse populations also often requires practice-oriented risk communication guidelines, which can be facilitated when officials from national agencies build relationships with community partners, emergency managers, local broadcasting systems, and community outreach and engagement efforts. For instance, using regular practice runs to test and improve communication systems as well as cooperative games among community leaders (i.e., applying mathematical game theory to test scenarios and help various stakeholders formulate mutually beneficial compromises) helps to convey risk information more effectively than issuing lengthy reports filled with statistics and technical terms.

Preparations on Multiple Fronts

Practical, actionable risk communication is often usefully complemented by decision support tools such as early-warning systems. In recent years, the Department of Hydrology and Meteorology has demonstrated its capacity for hydrometeorological forecasting and providing early warning on floods. Still, more research and efforts are necessary to develop and expand early-warning systems for other hazards like landslides and avalanches.

It is important to acknowledge that Nepal’s flood early-warning system, although it contributes to reducing losses of human lives and properties, does little to reduce socioeconomic vulnerabilities. Early-warning systems should thus be complemented by other preparedness and risk mitigation measures, including awareness and education, land use planning, drainage improvements, bioengineering (e.g., brush layering, live check dams, and vegetative stone pitching), response training, and contingency planning, all targeting the communities that are most at risk.

Nepal’s risk management strategy should aim to address socioeconomic vulnerabilities alongside physical vulnerabilities, and it should be framed around a multihazard perspective.

Overall, Nepal’s risk management strategy should aim to address socioeconomic vulnerabilities alongside physical vulnerabilities, and it should be framed around a multihazard perspective rather than around efforts to address individual hazards and contingencies separately.

Multihazard risk management consists of interacting efforts in the natural sciences, engineering, and social science. For example, developing an early-warning system for landslides requires reliable weather prediction (atmospheric science), land surface modeling (Earth science), risk communication (social science), a user-friendly Web-based information portal (computer engineering), and a continuous monitoring network.

Hazard and disaster studies should be viewed as basic science intended to advance knowledge that is easily transferable to the public rather than only as applied science aimed at fixing problems. Developing an adaptive risk management framework also demands substantial commitment and sustained investment over a long period of time and requires collaborative and interdisciplinary research among climate scientists, engineers, economists, policymakers, and decisionmakers. With such efforts and commitment, along with emerging tools like the CRI and early-warning systems, Nepal’s communities—from the most vulnerable to the least—will be better prepared for and more able to respond to growing threats from natural hazards.

Acknowledgments

We thank Krishna H. Pushkar (joint secretary, government of Nepal), Rocky Talchabhadel (Texas A&M AgriLife Research, Texas A&M University, El Paso), and Jeeban Panthi (Department of Geosciences, University of Rhode Island, Kingston) for their contributions. Any opinions, findings, conclusions, and recommendations expressed in this material are those of the authors. B.R., S.S., G.R.G., T.R.A, and R.S. conceptualized the commentary and wrote the paper. The authors are not aware of any competing interests.

References

Eckstein, D., et al. (2019), Global Climate Risk Index 2020, Germanwatch, Bonn, Germany, www.germanwatch.org/sites/germanwatch.org/files/20-2-01e%20Global%20Climate%20Risk%20Index%202020_14.pdf.

Van der Geest, K. (2018), Landslide loss and damage in Sindhupalchok District, Nepal: Comparing income groups with implications for compensation and relief, Int. J. Disaster Risk Sci., 9(2), 157–166, https://doi.org/10.1007/s13753-018-0178-5.

Author Information

Biplob Rakhal, Engineering-GIS, World Food Program, Kathmandu, Nepal; Sanjib Sharma (sanjibsharma66@gmail.com), Earth and Environmental Systems Institute, Pennsylvania State University, University Park; Ganesh R. Ghimire, Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tenn.; Tirtha R. Adhikari, Central Department of Hydrology and Meteorology, Tribhuvan University, Kirtipur, Nepal; and Ramesh Shrestha, Department of Geography, Durham University, U.K.

Citation:

Rakhal, B., S. Sharma, G. R. Ghimire, T. R. Adhikari, and R. Shrestha (2021), Nepal’s communities brace for multihazard risks, Eos, 102, https://doi.org/10.1029/2021EO159039. Published on 01 June 2021.

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