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Science and technology

This theme adresses how science and technology can contribute to DRR, including approaches and initiatives to bring scientific and technical knowledge into practice and policy, approaches for multidisciplinary engagement, good practice in scientific and technical aspects of DRR, and citizen science.

Latest Science & technology additions in the Knowledge Base

Rocks block a road in Tejeros, Gran Canaria, Spain after heavy rains trigger landslides and rockfalls
Update

Rock boccia on the slope

SLF researchers are investigating how artificial stones move on rough ground in order to improve hazard indication maps.
WSL Institute for Snow and Avalanche Research SLF
Research briefs

Discovery about ice layer formation in ice sheets can improve sea level rise predictions

A newly discovered mechanism for the flow and freezing of ice sheet meltwater could improve estimates of sea level rise around the globe.
The University of Texas at Austin
Update

More intense Indian summer monsoons

Satellite data from 1991 to 2020 show heavier summer rainfall that is likely to continue
European Organization for the Exploitation of Meteorological Satellites
Update

New USGS map shows where landslides are most likely to occur

Landslides are a common hazard in the US. In fact, nearly 44% of the country could experience one, potentially catastrophically. Our new national landslide susceptibility map shows where they’re most likely to happen.
United States Geological Survey
Update

South Asia: Collaborating for climate resilience through hydromet and early warning systems

The South Asia Hydromet Forum, supported by the World Bank, brings together representatives from meteorological and hydrological services for technical training, data sharing, and knowledge exchange to strengthen forecasting and early warning systems.
World Bank, the
Hand on a keyboard with images of an AI-powered programme
Update

Cultivating trust in AI for disaster management

Artificial intelligence applied in disaster management must be reliable, accurate, and, above all, transparent. But what does transparency in AI mean, why do we need it, and how is it achieved?
Eos - AGU
Research briefs

Rolling in the deep: Norfolk street flooding predicted in seconds with machine learning models

Getting around on a rainy day often involves dodging puddles – or sloshing through them. But during downpours, shallow pools can quickly become roadway ponds that cripple transportation, threaten safety and undermine emergency response.
Thomas Jefferson National Accelerator Facility (JLAB)
speakers
Update

Five ways AI can strengthen early warning systems

Explore how AI can boost early warning systems to protect vulnerable communities.
United Nations University (UNU)
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