Spatio-Temporal Dynamics and Drivers of Flood Risk Change. Perspectives of Coupled Component Models

Zischg, Andreas Paul (2018). Spatio-Temporal Dynamics and Drivers of Flood Risk Change. Perspectives of Coupled Component Models (Unpublished). (Habilitation, University of Bern, Faculty of Science)

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Extreme floods are one of the most damaging natural hazards, accounting for the majority of all economic losses from natural hazards worldwide. Several intertwined natural and anthropogenic drivers influence flood risk and its change: global warming, precipitation patterns, flood triggering processes, river morphology, river engineering works, population and values at risk, and flood risk reduction strategies. Sustainable flood risk management requires understanding all aspects of flood risk and its change in space and time. Thus, flood risks must be analyzed from a dynamic rather than a static perspective. However, methods to analyze and quantify environmental and socio-economic changes related to flood risk, both in space and time, are nearly not existent.
Within this cumulative habilitation thesis methods are examined and developed that allow the analysis of past and future changes in both the natural and human environment with a spatially explicit perspective, and methods that allow disentangling the different drivers of change that are mostly interwoven and have opposing effects on flood risk evolution. The habilitation extends the frontiers of research on flood risk changes with three main methodological approaches: (1) data-driven analyses of environmental and socio-economic change, (2) development of models for specific aspects of flood risk, and (3) model coupling.
Coupled component models provide an interesting approach for analyzing flood risk change, for modelling feedback mechanisms between human activities and the natural environment, and for the regionalization of global environmental and socio-economic changes. The habilitation thesis gives an outlook for enabling coupled model frameworks to predict and evaluate the effects of different adaptation strategies on flood risk evolution. Finally a modelling framework that couples specialist models toward whole-system models offers the potential for obtaining an universalist view and unifying several approaches in geography. Such a holistic approach is supporting the search for sustainable solutions for the complex and interconnected problems we are facing today.

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