Probabilistic hazard assessment as a tool for mapping climate risk

By Vidya S and Kritika Adesh Gadpayle.

Over the past few decades, extreme climate events in India (such as floods, cyclones, and heat waves) have caused widespread damage and human suffering. We had the hottest March yet in 2022, with 280 heatwaves across the country — the highest in 12 years. In 2020, cyclone Amphan, one of the most powerful cyclones ever recorded, is estimated to have destroyed 17 lakh hectares of agricultural crops worth ₹ 15,800 crore, while the Kerala floods of 2018 claimed the lives of 104 people; devastated 5,190 settlements; caused property damages worth roughly ₹ 19,000 crore; and resulted in crop losses of ₹ 3,558 crore. The Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) says that such extreme events may be more common in India in the near future. The situation necessitates a reliable climate risk assessment.

According to IPCC, climate risk arises from the interaction of hazard, exposure, and vulnerability. The term ‘hazard’ refers to the potential occurrence of climate-related physical events or trends causing damage and loss. ‘Exposure’ refers to all assets, services, resources, people, and infrastructure present in an area that could be harmed, while ‘vulnerability’ is the propensity or predisposition to be adversely impacted. Assessing climate risk entails considering the various extreme events (hazards) that could occur, quantifying their likelihood of occurrence, and weighing the potential impacts.

Climate risk can be assessed using sophisticated climate models that project the future climate on the basis of physical laws that govern the Earth’s climate in general (such as the conservation of energy and the ideal gas law), or through probabilistic risk assessment.

Probabilistic risk assessment is a group of techniques incorporating variability and uncertainty into the assessment process. It helps provide an estimate of the range and likelihood of a hazard, exposure or risk, and not just a single-point estimate. Here we discuss probabilistic hazard assessment — a method to asses hazard (which is a component of risk) — getting into the details of its concept, calculations, and utility, using extreme rainfall event as an example.

Probabilistic Hazard Assessment

Probabilistic hazard assessment utilises mathematical expressions to arrive at the probability of occurrence of hazard events. For instance, heavy rainfall with a potential to cause a flooding event can be assessed by estimating the probability of occurrence or exceedance of the event compared to a base case, and by calculating the return period. Often, in the news media and among professional organisations, expressions like a “100–year flood” or a “500–year flood” are used. This expression relates to the return period, which is the time period over which an extreme event with a certain magnitude is likely to occur. It means the event is likely to occur once every 100 years on an average. Another way to interpret the 100–year flood is to think of it as a flooding event that has a one–hundredth or one percentage chance of occurring in any given year. This is called the exceedance probability or the probability of occurrence of a certain event, and mathematically, it is 1 divided by the return period.

Although there are several mathematical equations that may be used to compute the probability of occurrence of hazards — one of the simplest is the Weibull’s method. This method considers the highest rainfall received at a particular station as rank (m) and assigns the value 1 to it, and the length of the period (number of years) is represented as n.

For example, in a station recording highest rainfall of 2000 mm in 30 years, the rank (m) is 1 and the number of years (n) is 30.

Using the formula:

Probability (Px)=m ⁄ (n+1)

Probability (Px) =1 /(30+1) = 0.03, and return period = 1 ⁄ Px =1 ⁄ 0.03 = 33 years

Generally, it could be said that extreme events with high magnitude of rainfall have a higher return period with less probability of occurrence, whereas extreme events with lesser magnitude of rainfall have a lower return period with high probability of occurrence.

To Sum Up

Probabilistic hazard assessment can be a tool for making evidence-based decisions. The information obtained from such an assessment can be used by decision makers to weigh the risks of decision alternatives. Additionally, it allows estimating the probability of extreme events that are becoming more likely as a result of climate change, and they can be presented as hazard curves, hazard maps, or probability maps for communicating with stakeholders.

However, this method is resource-intensive, requiring substantial collaboration and cooperation across business, academic, and public institutions for producing reliable outputs that reflect local data and knowledge. If designed well, these assessments can be updated as and when new data become available or as conditions change.

The authors work in the area of Adaptation and Risk Analysis at the Center for Study of Science, Technology and Policy (CSTEP), a research-based think tank.