Evelyn Mühlhofer is a PhD researcher in the Weather & Climate Risks Group at ETH Zurich’s Institute for Environmental Decisions in Switzerland, and is co-supervised by Elco Koks at the Institute for Environmental Studies (IVM) at Vrije Universiteit Amsterdam. Her research revolves around natural hazard impacts on critical infrastructure systems and service disruptions. Using network modelling, open-source geospatial data, and the risk assessment platform CLIMADA, she examines how structural damages to infrastructure assets can lead to systemic failure cascades, and their implications for basic service access to the dependent population.
Beforehand, she completed a Bachelors degree in Interdisciplinary Sciences (Physical Chemistry) from ETH Zurich, during which she gained theoretical knowledge at the intersection of physics and chemistry, and practical laboratory experience in environmental and analytical chemistry during several research projects. She went on to pursue a Masters degree in Management, Technology & Economics, where she transitioned towards a more applied science spectrum. She joined the Weather & Climate Risks group with a master thesis contrasting actual risk exposure and stated adaptation intentions within countries’ Nationally Determined Contributions following the Paris Agreement. After working in project monitoring and evaluation for a Swiss NGO, and a brief stay at the Swiss Meteorological Office (MeteoSwiss), she returned to ETH for her PhD.
Natural hazards pose significant risks to human lives, infrastructure, and ecosystems. Understanding risks along all these dimensions is critical for effective adaptation planning and risk management. However, climate risk assessments mostly focus on population, economic asset values, and road or building infrastructure, because publicly available data on more diverse exposures are scarce. The increasing availability of crowd-sourced geospatial data, notably from OpenStreetMap, opens up a novel means for assessing climate risk to a large range of physical assets. To this end, we present a stand-alone, lightweight, and highly flexible Python-based OpenStreetMap data extraction tool: OSM-flex. To demonstrate the potential and limitations of OpenStreetMap data for risk assessments, we couple OSM-flex to the open-source natural hazard risk assessment platform CLIMADA and compute winter storm risk and event impacts from winter storm Lothar across Switzerland to forests, UNESCO heritage sites, railways, healthcare facilities, and airports. Contrasting spatial patterns of risks on such less conventional exposure layers with more traditional risk metrics (asset damages and affected population) reveals that risk hot-spots are inhomogeneously and distinctly distributed. For instance, impacts on forestry are mostly expected in Western Switzerland in the Jura mountain chain, whereas economic asset damages are concentrated in the urbanized regions around Basel and Zurich and certain train lines may be most often affected in Central Switzerland and alpine valleys. This study aims to highlight the importance of conducting multi-faceted and high-resolution climate risk assessments and provides researchers, practitioners, and decision-makers with potential open-source software tools and data suggestions for doing so.
@article{muhlhofer2024openstreetmap,title={OpenStreetMap for Multi-Faceted Climate Risk Assessments},author={Mühlhofer, Evelyn and Kropf, Chahan and Riedel, Lukas and Bresch, David Niklaus and Koks, Elco},journal={Environmental Research Communications},year={2024},doi={10.1088/2515-7620/ad15ab}}
A Generalized Natural Hazard Risk Modelling Framework for Infrastructure Failure Cascades
Critical infrastructures are more exposed than ever to natural hazards in a changing climate. To understand and manage risk, failure cascades across large, real-world infrastructure networks, and their impact on people, must be captured. Bridging established methods in both infrastructure and risk modelling communities, we develop an open-source modelling framework which integrates a network-based interdependent infrastructure system model into the globally consistent and spatially explicit natural hazard risk assessment platform CLIMADA. The model captures infrastructure damages, triggers failure cascades and estimates resulting basic service disruptions for the dependent population. It flexibly operates on large areas with publicly available hazard, exposure and vulnerability information, for any set of infrastructure networks, hazards and geographies of interest. In a validated case study for 2018’s Hurricane Michael across three US states, the model reproduced important failure dynamics among six infrastructure networks, and provided a novel spatial map where people were likely to experience disruptions in access to healthcare, loss of power and other vital services. Our generalized approach allows for a view on infrastructure risks and their social impacts also in areas where detailed information and risk assessments are traditionally scarce, informing humanitarian activities through hotspot analyses and policy frameworks alike.
@article{muhlhofer2023generalized,title={A Generalized Natural Hazard Risk Modelling Framework for Infrastructure Failure Cascades},author={Mühlhofer, Evelyn and Koks, Elco and Kropf, Chahan M and Sansavini, Giovanni and Bresch, David N},journal={Reliability Engineering \& System Safety},pages={109194},year={2023},publisher={Elsevier},doi={10.1016/j.ress.2023.109194}}
