Managing the Risks, Impacts and Uncertainties of drought and water Scarcity (MaRIUS)

Droughts and water scarcity pose a significant risk to the environment, society and the economy. In 2012 the UK experienced the driest spring in over a century, following two dry winters. However the current scientific understanding of the complex drivers and impacts of droughts is inadequate.

The project “Managing the Risks, Impacts and Uncertainties of drought and water Scarcity” (MaRIUS) will introduce a risk-based approach to drought and water scarcity in order to inform management decisions and prepare households.

Photo of Lake Hume in drought by Tim J Keegan

The project is designed to capture the complexity of the water scarcity by using expertise across the social and natural sciences and with key stakeholder involvement.

MaRIUS will use scenario modelling and case studies across a number of scales, from household to national, in order to understand both the drought impacts at a local level right as well as the institutional decision making by governments and water companies. The modelling will enable testing of drought scenarios and a thorough representation of their impacts on water quality, agriculture, biodiversity and economic losses.

In addition to the modelling component, social science and stakeholder engagement are a key part of the project and will help us to understand the role of institutions, regulation and the markets in drought management.

Weather@home Contribution

The MaRIUS project will make use of the large ensemble of regional climate model runs available from our weather@home experiments. The focus of this work is to develop event sets of droughts and heat waves within the framework of probabilistic event attribution. This will involve setting up a fast-track event set using the existing weather@home modelling set-up and improving the current modelling framework to allow for important feedbacks specifically relevant to droughts. This will in particular involve coupling a so-called slab-ocean (only the uppermost layer of the ocean) to the atmosphere model used under weather@home.

Project Researcher: