News

Kathmandu, May 26, 2025 — A groundbreaking review exploring the global application of traditional and local knowledge (TLK) in anticipating natural disasters has just been published in a prestigious scientific journal by researchers from the Himavat Institute.  The study offers powerful insights into how indigenous practices can complement and enhance modern disaster risk reduction (DRR) strategies.

The article, titled “Predicting and Forecasting Disasters: A Global Scan of Traditional and Local Knowledge”, was authored by Dr. Prakash Kumar Paudel, Raja Ram Chandra Timilsina, and Dinesh Bhusal (all affiliated with the Himavat Institute), along with Dr. Henry P. Huntington of Huntington Consulting, USA.

Drawing from 53 peer-reviewed research articles, the study underwent a rigorous screening process and compiled 423 predictive cases from 25 countries. It classifies traditional disaster prediction methods into three major categories: biological, meteorological, and astronomical indicators. The research found that animal behaviors—particularly those of insects, birds, and mammals—were the most commonly used indicators, followed by plant responses, water conditions, and cloud patterns.

“Our research highlights that communities around the world have, for centuries, relied on nuanced environmental observations to anticipate events such as floods, droughts, cyclones, and even earthquakes,” said Dr. Paudel, the study's lead author. “This body of knowledge, while largely under-documented, holds immense potential for improving disaster preparedness at the community level.”

The study revealed that meteorological disasters—including storms and typhoons—accounted for the highest share of predictive cases (33%), followed by hydrological disasters such as floods (31%), and climatological disasters like droughts (28%). Although geophysical disasters (e.g., earthquakes, volcanoes) comprised only 7% of cases, they also demonstrated unique predictive patterns through TLK.

Importantly, the study advocates for greater scientific validation, increased funding, and formal integration of TLK into DRR frameworks. This integration is particularly crucial for resource-limited communities, where modern forecasting technologies are often inaccessible.

“Modern technology alone is not enough. Merging it with time-tested traditional knowledge offers a powerful, community-empowering model for disaster resilience,” added Dr. Paudel.

This pioneering research underscores the Himavat Institute’s commitment to bridging scientific inquiry with traditional wisdom—championing more inclusive, culturally rooted approaches to disaster management in South Asia and beyond.

The full article is available at https://doi.org/10.1016/j.ijdrr.2025.105590