GSI proposes to scale up landslide predictions in Wayanad
Besides rain data, GSI will consider 42 other factors including slope, elevation, and geological specialities for landslide predictions
The Geological Survey of India (GSI) is in the process of upgrading its landslide predictions in Wayanad even as questions are being raised about the efficacy of the weather prediction systems.
The landslide in Wayanad, which claimed over 300 lives, had triggered a political controversy, with Home Minister Amit Shah stating that the Kerala government was forewarned about the possible heavy rain in the district. However, Chief Minister Pinarayi Vijayan countered the statement with the support of rainfall warnings issued by the India Meteorological department (IMD) and argued that no red alerts were issued by the department.
Rainfall is a major factor that triggers landslides, and hence, such warnings mostly depend on rainfall data provided by the IMD. Besides rain data, the GSI would also consider 42 other factors including the slope, elevation, and geological specialities of the land. The landslide forecasting system relies on integrating meteorological (such as rainfall and rainfall forecasts) data with landscape (susceptibility) conditions to generate short-range (two days) and medium-range (seven days) forecasts, according to GSI officials.
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The warnings are issued after putting all these factors together, and the accuracy of the prediction could be improved by obtaining precise weather data, said V. Ambili, Deputy Director General, GSI, Kerala unit.
The GSI headquarters has already initiated steps to obtain weather data from more sources. Efforts are on to obtain real-time rainfall data, which would go a long way in improving the accuracy of landslide predictions, she said.
The GSI has been issuing regional landslide forecast bulletins on experimental mode once a day for Wayanad to the State and the District Disaster Management Authorities for ground testing since June 25. These landslides forecast models are based on rainfall forecasts provided by the National Centre for Medium Range Weather Forecasting and the IMD and the landslide thresholds prepared by the GSI using past rainfall and landslide data, she explained.
The experimental forecast bulletin requires extensive ground testing over four to five monsoon years. The GSI had recently operationalised landslide forecasting in Darjeeling and Kalimpong districts of West Bengal and Nilgiris district of Tamil Nadu from July 19, 2024 for public use after putting the system to test for four years, Dr. Ambili said.
At present, alerts could be issued at the panchayat level, and precise location-specific predictions had not been possible as site-specific rain data was not available, she added.
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