Co-constructing a tool for assessing the risk of climate change impacts on water: integration of multi-model ensemble and expert knowledge

11:15 Tuesday 28 May


Room S10


Laura Woltersdorf (Germany) 1; Fabian Kneier (Germany) 1; Carina Zang (Germany) 2

1 - Goethe University Frankfurt; 2 - International Centre for Water Resources and Global Change (UNESCO)

For successful climate change adaptation, decision makers need to have appropriate knowledge on climate change risks at hand. However, it is challenging to take into account the complex information of climate change projections and uncertainties in participatory risk assessments of climate change impacts on water. To integrate the significant uncertainties of both climate and impact modeling, it is state-of-the-art to rely on multi-model ensembles that quantify potential future changes in variables relevant for climate change risk assessments. Therefore, the aim of this study is to co-construct a tool for assessing the risk of climate change impacts on water by integration of multi-model ensemble data as well as expert knowledge.

We use a participatory and transdisciplinary research approach in the frame of the CO-MICC project in the Maghreb region (Morocco, Algeria, Tunisia). We involve scientists from different disciplines (hydrological modelers, sociologists, scientists working on transdisciplinary methods and communication) as well as Maghrebin experts from national administrations (water supply, irrigation, basin management) and meteorological services. Our multi-model ensemble consists of 4 global climate models that serve as input to 4 global hydrological models, simulating hydrological variables under 4 RCPs for 3 future time slices until 2100. In order to co-construct a tool for climate change risk assessment, first, semi-structured expert interviews helped to elicit the experts’ perception of problems, factors and links concerning climate change impacts on water on the country scale. After the interview, the scientist assisted the expert in constructing a causal map visualizing the impacts of climate change on water. Incorporating the scientific literature, the causal maps were translated into one exemplary Bayesian network (BN) structure.

This BN was subsequently discussed in an expert workshop in break-out groups and in the plenary with scientists and local experts. As a result, scientists and stakeholders co-constructed a BN containing the most relevant variables for local climate change risk assessment (i.e. groundwater recharge, streamflow, soil moisture) that are provided by the multi-model ensemble. In addition, local experts defined (1) the objective of the BN, i.e. the most important risk of climate change impacts on water, and (2) the critical state for that risk. Therefore, such BNs can be suitable tools to integrate the quantitative data of the multi-model ensemble, qualitative experts’ knowledge as well as different adaptation options, and allow a stochastic analysis of potential cascading impacts induced by climatic and non-climatic stressors (i.e. water abstractions) on the risk of water availability.