Shallow geohazards

The BGS is home to the National Landslide Database, the National Karst Database and a National Sinkhole Database. Data is collected using methods that range from Earth observation to literature searches, social media and crowd science. We draw from our researchers’ skills to respond to geohazard events, e.g. landslides induced by the Nepal earthquake of 2015 and sinkholes (for example, Solotvyno, Ukraine), and we can assess data quality and representation in terms of size frequency distributions.

Conceptual classifications of shallow geohazards underpin geohazard communication, such landslide, sinkhole and shrink–swell potential, which is based on the Atterberg limits of the soil and its position on the Casagrande plasticity chart.

Modelling commonly requires more specific, field-based information, fo example dimensions, soil types and details of the triggering process. A number of techniques are used to collect this information, including Earth observation, ground based geomatics, geological and geomorphological mapping and  ground investigation techniques such as probing, drilling and shallow geophysics. Examples of this activity include responsive visit case studies and specific research projects, as at Aldbrough and Barton on Sea.

Algorithms, based on process understanding, are developed to identify areas where the ground conditions are more susceptible to geohazards for our  BGS GeoSure  products. By adopting a domains approach, we are recognising that regions of common geology and geomorphology give rise to similar styles of geohazard. Perturbations (triggers) that initiate geohazards may be meteorological, tectonic (such as earthquakes) or anthropogenic.

Our shallow geohazard trigger threshold value research takes a number of approaches to identify hazard tipping points. Input data includes the monitoring data from geohazard observatories. By combining the concepts of susceptibility with MetOffice weather forecasting, we contribute to the Natural Hazards Partnership daily hazard assessment.  This is being advanced by domain-scale, real-time modelling.

By integrating susceptibility with hazard characterisation, we can better understand the potential impact of geohazards. Our research on this topic relies on both the development of impact libraries and modelling, which enable risk assessment and the provision of information for early warning systems to protect vulnerable communities and modelling for multi-hazard research.