Here, you will find information about the provisioning and utilization of the multi-model-based quantitative estimates of freshwater-related hazards of climate change that are freely available in the data portal. The associated methods are referred to as PUNI (Providing and Utilizing eNsemble Information) methods. They were co-developed by scientists and stakeholders from the water sector by iteratively testing alternative ways of presenting and utilizing multi-model ensemble (MME) data in support of exemplary climate change risk assessments. All PUNI methods can be consulted in our PUNI Handbook, which can be downloaded below.
Regarding the provisioning of MME data, the handbook gives a detailed account of (1) the MME generation, (2) the selection of relevant freshwater hazard indicators and (3) the co-designed data portal functionalities, in particular in relation to the quantitative representation of uncertainty information.
From a usage perspective, the handbook provides guidance as to how to deal with uncertain and spatially coarse (0.5° grid cells) MME data for different kinds of climate change risk assessment. Concretely, it introduces diverse methods to integrate MME data into, on the one hand, small regional to local risk assessments and, on the other hand, global-scale hazard and risk assessments. The methods are described through examples taken from stakeholder dialogues that were conducted during the research project (2017-2021). Concerning the methods for small regional to local scale risk assessments, particular attention is given to Bayesian Networks. This cutting-edge integrated modelling approach has great potential for participatory processes, as it combines quantitative multi-model output data with quantitative and qualitative local expert knowledge.