by Simrin Sirur
The Western Indian Himalayan Region is more prone to risks from climate change compared to the Eastern Himalayan ranges, a new climate risk index, designed by researchers from the Indian Institute of Technology, Madras (IIT-M), shows.
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The index is the first to use the latest framework from the Intergovernmental Panel on Climate Change (IPCC) to assess climate risk in the Himalayas, by combining both physical and socio-economic indicators, the researchers have said.
The Himalayas considered the “third pole” for the amount of ice and water they hold, are particularly vulnerable to the effects of climate change. Some parts of the Himalayas, like the Hindu Kush Himalayan Range, are warming at a faster rate than the global average. Both snow cover and glacier mass in the Himalayas have been on the decline in recent decades.
Though the likely effects of climate change over the Himalayas are well known, few studies have tried to map how these risks could manifest at a district level in the region. A 2020 study by researchers from the Forest Research Institute and others, aimed to carry out a similar risk assessment in the Himalayan region and found that the Eastern ranges were more risk-prone. The IIT-M study uses an updated technique and publicly available data to find that, while both the Western and Eastern regions are vulnerable, the Western region is more prone to risks arising from climate change.
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Shimla, Dhalai and Imphal West at risk
The IIT Madras researchers determined district-level risk by analysing three of its components: hazard (the likelihood or trend of an event occurring), vulnerability (the tendency to be negatively impacted) and exposure (the extent to which a system may face adverse consequences due to a hazard).
The study considered a wide range of hazards, including earthquakes, cold wave days, flood events, drought, rainfall and lightning days, among others, and used data from publicly available sources, like the India Meteorological Department and Census. To determine vulnerability, it looked at disadvantaged populations that were likely to be harmed as well as the adaptive capacity of households to cope with changing circumstances. Exposure was measured through factors such as population growth rate, population density, percentage of built-up area, percentage of area under agriculture and percentage of grazing land.
“Each of these elements contributes crucial information that helps to understand and mitigate potential threats,” Aayush Shah, co-author of the paper, told Mongabay-India, adding, “Ignoring any of these factors can lead to incomplete or inaccurate risk assessments, resulting in inadequate preparedness and response measures.”
The index was calculated using a method called TOPSIS, or Technique for Order of Preference by Similarity to Ideal Solution. It uses existing data to compare alternatives based on several different criteria and presents the best option by assessing the factors that negatively and positively affect the risk. This method was used to produce separate indices for each risk component – hazard, vulnerability and exposure – as well as an overall risk index, which multiplied all three variables.
In terms of hazard occurrence, the study found Shimla district in Himachal Pradesh to be the most hazard-prone. Shimla experienced the most flood events among all Himalayan districts from 1969 to 2019 and it also received the fourth-highest number of annual snowfall days from 1981 to 2010, the study says. Shimla was followed by East Sikkim, which is drought-prone and “has by far the highest average number of fog days,” and Solan in Himachal Pradesh, which experienced the third-highest number of hailstorm days between 1981 and 2010. Districts in Nagaland and Mizoram were found to be the least hazard-prone compared to other Himalayan districts.
The Eastern Indian Himalayan Region was found to be more vulnerable, with 43 out of 62 districts classified as the “highest and highly vulnerable” districts. Dhalai district of Tripura emerged as the most vulnerable because it scored poorly in adaptive capacity indicators. Indicators for adaptive capacity considered by the study included households with access to electricity as the main source of lighting, hospital beds available per lakh of population, households with access to clean drinking water within house premises, and per capita expenditure, among others.
In terms of exposure, Imphal West in Manipur was found to be the most exposed district, because it has “one of the highest population density in the Indian Himalayan Region and the highest percentage of built-up area,” said the study. Kurung Kumey district from Arunachal Pradesh ranked second, for its population growth rate, and two districts from Uttarakhand – Hardwar and Udham Singh Nagar – ranked third because they have the highest percentage of agricultural land.
“Looking at each aspect of risk is important because it can help form more targeted policies for mitigation,” said Krishna Malakar, Assistant Professor at IIT-M and co-author of the study.
When the hazard, vulnerability, and exposure indices were combined to get an overall risk profile, the Darjeeling district of West Bengal emerged as the most “risk-prone” of all Himalayan districts. The study doesn’t, however, elucidate the nature of the risk. Darjeeling is followed by the West and North Tripura districts.
On a regional scale, the Western Himalayan Region proves to be more “risk-prone,” as per the index, “since more than two-thirds of them (32 out of 47) fall in the highest and high-risk districts category.” In contrast, most districts in the Eastern Himalayan Region (93 out of 62) “are categorised as either the lowest or low-risk districts.”
Calculating risk of the Western Himalayas
The interest in such vulnerability indices is growing, especially as cities and districts design their climate action plans. However, the results may vary depending on the methodologies and data used. The 2020 study in the Himalayas, for example, used a Mountain Specific Risk Management Framework and found that the Eastern ranges were more risk-prone, “due to relatively high climatic exposure and occurrence of more hazards…In addition, water-based natural hazards have high intensity in the eastern Himalayas.”
The Council on Energy, Environment, and Water had also done a similar exercise, mapping vulnerability across districts, but limiting its focus to the “risk of hydro-met disasters and their compounded impact on districts’ climate vulnerability.” In its analysis, done in 2021, Assam emerged as the most vulnerable to hydro-met disasters.
According to Abinash Mohanty, sector head for Climate Change and Sustainability at development consulting group IPE-Global, who had worked on the CEEW’s index, such indices are useful to learn more about how risk profiles differ across districts, but they need to be more dynamic to meaningfully guide policy solutions. “What’s missing from the domain is how the risk landscape is changing and will evolve over the next 10 to 20 years,” he said, adding, “It would be useful to do this type of assessment every two years, to track and monitor these risks, but that requires building capacity and using an integrated approach to assess risks, which is a challenge for governments.”
Mohanty is working with the Mumbai Municipality to create a climate risk observatory that can monitor risks from hazards over time – especially in the short term – in an attempt to bridge capacity gaps. “We are going to integrate hazard information into the command-and-control centre at the Mumbai BMC, so they can track, monitor and take actions on a short-term, mid-term and long-term basis.”
This article was originally published in Mongabay. To read the original article tap here.