Drought risk analysis for forested landscapes: Project PRAFOR

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• Mark Brewer (Biomathematics & Statistics Scotland (BioSS))
• Tuesday 08 September 2020, 13:30-13:50
• Seminar Room 1, Newton Institute.

If you have a question about this talk, please contact info@newton.ac.uk.

EBDW03 - Integrating quantitative social, ecological and mathematical sciences into landscape decision-making

This project aims to extend theory for probabilistic risk
analysis of continuous systems, test its use against forest data, use process
models to predict future risks, and develop decision-support tools.



Risk is commonly defined as the expectation value for
loss. Most risk theory is developed for discrete hazards such as accidents,
disasters and other forms of sudden system failure and not for systems where
the hazard variable is always present and continuously varying, with matching
continuous system response.



Risks from such continuous hazards (levels of water,
pollutants) are not associated with sudden discrete events, but with extended
periods of time during which the hazard variable exceeds a threshold. To manage
such risks, we need to know whether we should aim to reduce the probability of
hazard threshold exceedance or the vulnerability of the system.



In earlier work, we showed that there is only one
possible definition of vulnerability that allows formal decomposition of risk
as the product of hazard probability and system vulnerability. We have used
this approach to analyse risks from summer droughts to the productivity of
vegetation across Europe under current and future climatic conditions; this
showed that climate change will likely lead to greatest drought risks in
southern Europe, primarily because of increased hazard probability rather than
significant changes in vulnerability.



We plan to improve on this earlier work by: adding
exposure to hazard; quantifying uncertainties in our risk estimates for risk;
relaxing assumptions via Bayesian hierarchical modelling; testing our approach
on both observational data from forests in the U.K., Spain and Finland and on
simulated data from process-based modelling of forest response to climate
change; embedding the approach in Bayesian decision theory; and developing an
interactive web application as a tool for preliminary exploration of risk and
its components to support decision-making.

This talk is part of the Isaac Newton Institute Seminar Series series.

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