Landslides and debris flows have long posed significant challenges in the Himalayan region, especially during severe weather conditions.
The institute said that to address these issues, professionals from meteorology, hydrology, geomorphology, remote sensing and geotechnical engineering collaborated to develop a unique approach that integrates meteorological modeling with debris flow. Integrates with numerical simulation.
"At the core of our framework is to integrate meteorological data generated by the WRF model with numerical simulations of debris flows. This approach allows us to better understand the complex interactions between precipitation patterns and landslide dynamics," Pro. S. Srikrishnan, principal researcher on the project, SAI said in a statement.
This framework significantly enhances landslide prediction in the Himalaya.
Key features include the use of high-resolution WRF models to analyze rainfall patterns important for landslide prediction, integrating an updated debris flow numerical model and establishing specific rainfall intensity-duration thresholds through simulations. According to the researchers, this comprehensive approach improves accuracy by considering factors such as soil moisture and past events such as floods.
Director of IIT Roorkee, Prof. K.K. "This groundbreaking framework holds immense potential to strengthen disaster preparedness efforts not only in the Himalayan region but potentially across India," it said. Pant.
According to the researchers, the innovative framework aims to contribute to better regional disaster preparedness by providing more refined thresholds that can predict landslide events.
The institute said that to address these issues, professionals from meteorology, hydrology, geomorphology, remote sensing and geotechnical engineering collaborated to develop a unique approach that integrates meteorological modeling with debris flow. Integrates with numerical simulation.
"At the core of our framework is to integrate meteorological data generated by the WRF model with numerical simulations of debris flows. This approach allows us to better understand the complex interactions between precipitation patterns and landslide dynamics," Pro. S. Srikrishnan, principal researcher on the project, SAI said in a statement.
This framework significantly enhances landslide prediction in the Himalaya.
Key features include the use of high-resolution WRF models to analyze rainfall patterns important for landslide prediction, integrating an updated debris flow numerical model and establishing specific rainfall intensity-duration thresholds through simulations. According to the researchers, this comprehensive approach improves accuracy by considering factors such as soil moisture and past events such as floods.
Director of IIT Roorkee, Prof. K.K. "This groundbreaking framework holds immense potential to strengthen disaster preparedness efforts not only in the Himalayan region but potentially across India," it said. Pant.
According to the researchers, the innovative framework aims to contribute to better regional disaster preparedness by providing more refined thresholds that can predict landslide events.
