Quantifying climate risks to infrastructure systems: a comparative review of developments across infrastructure sectors

Infrastructure systems are particularly vulnerable to climate hazards, such as flooding, wildfires, cyclones and temperature fluctuations. Responding to these threats in a proportionate and targeted way requires quantitative analysis of climate risks, which underpins infrastructure resilience and adaptation strategies. The aim of this paper is to review the recent developments in quantitative climate risk analysis for key infrastructure sectors, including water and wastewater, telecommunications, health and education, transport (seaports, airports, road, rail and inland waterways), and energy (generation, transmission and distribution). We identify several overarching research gaps, which include the (i) limited consideration of multi-hazard and multi-infrastructure interactions within a single modelling framework, (ii) scarcity of studies focusing on certain combinations of climate hazards and infrastructure types, (iii) difficulties in scaling-up climate risk analysis across geographies, (iv) increasing challenge of validating models, (v) untapped potential of further knowledge spillovers across sectors, (vi) need to embed equity considerations into modelling frameworks, and (vii) quantifying a wider set of impact metrics. We argue that a cross-sectoral systems approach enables knowledge sharing and a better integration of infrastructure interdependencies between multiple sectors

Climate Impact Storylines for Assessing Socio-Economic Responses to Remote Events

Complex interactions involving climatic features, socio-economic vulnerability or responses, and long impact transmissions are associated with substantial uncertainty. Physical climate storylines are proposed as approach to explore complex impact transmission pathways and possible alternative unfolding of event cascades under future climate conditions. These storylines are particularly useful for climate risk assessment for complex domains, including event cascades crossing multiple disciplinary or geographical borders. For an effective role in climate risks assessments, practical guidelines are needed to consistently develop and interpret the storyline event analyses.This paper elaborates on the suitability of physical climate storyline approaches involving climate event induced shocks propagating into societal impacts. It proposes a set of common elements to construct the event storylines. In addition, criteria for their application for climate risk assessment are given, referring to the need for storylines to be physically plausible, relevant for the specific context, and risk-informative.Six examples of varying scope and complexity are presented, all involving the potential climate change impact on European socio-economic sectors induced by remote climate change features occurring far outside the geographical domain of the European mainland. The storyline examples illustrate the application of the proposed storyline components and evaluates the suitability criteria defined in this paper. It thereby contributes to the standardization of the design and application of event-based climate storyline approaches

Framework for rainfall-triggered landslide-prone critical infrastructure zonation

Rainfall-induced landslides cause frequent disruptions to critical infrastructure in mountainous countries. Climate change is altering rainfall patterns and localizing extreme rainfall events, increasing the occurrence of landslides. For planning climate-resilient critical infrastructure in landslide-prone regions, it is urgent to understand the changing landslide susceptibility in relation to changing rainfall extremes and spatially overlay them with critical infrastructure to determine risk zones. As such, areas requiring financial reinforcements can be prioritized. In this paper, we develop a framework linking changing rainfall extremes to landslide susceptibility and intensity of critical infrastructure — exemplified on a national scale using Nepal as a case study. First, we define a set of 21 different unique rainfall indices that describe extreme and localized rainfall. Second, we prepare a new annual (2016–2020) inventory of 107,900 landslides in Nepal mapped on PlanetScope satellite imagery. Next, we prepare a landslide susceptibility map by training a random forest model using the collected extreme rainfall indices and landslide locations in combination with spatial data on topography. Fourth, we construct a gridded critical infrastructure spatial density map that quantifies the intensity of infrastructure (i.e., transportation, energy, telecommunication, waste, water, health, and education) at each grid location using OpenStreetMap. The landslide susceptibility map classified Nepal's topography into low (36 %), medium (33 %), and (32 %) high rainfall-triggered landslide susceptibility zones. The landslide susceptibility map had an average area under the receiver characteristic curve value of 0.94. Finally, we overlay the landslide susceptibility map with the critical infrastructure intensity to identify areas needing financial reinforcement. Our framework reasonably mapped critical infrastructure hotspots in Nepal prone to landslides on a 1 km grid. The hotspots are mainly concentrated along major national highways and in provinces 4, 3, and 1, highlighting the need for improved land management practices. These hotspots need spatial prioritization regarding climate-resilient critical infrastructure financing and slope conservation policies. The research data, output maps, and code are publicly released via an ArcGIS WebApp and GitHub repository. The framework is scalable and can be used for developing infrastructure financing strategies for landslide mountain regions and countries

A spatially-explicit harmonized global dataset of critical infrastructure

Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments

A spatially-explicit harmonized global dataset of critical infrastructure

Critical infrastructure (CI) is fundamental for the functioning of a society and forms the backbone for socio-economic development. Natural and human-made threats, however, pose a major risk to CI. Therefore, geospatial data on the location of CI are fundamental for in-depth risk analyses, which are required to inform policy decisions aiming to reduce risk. We present a first-of-its-kind globally harmonized spatial dataset for the representation of CI. In this study, we: (1) collect and harmonize detailed geospatial data of the world’s main CI systems into a single geospatial database; and (2) develop the Critical Infrastructure Spatial Index (CISI) to express the global spatial intensity of CI. The CISI aggregates high-resolution geospatial OpenStreetMap (OSM) data of 39 CI types that are categorized under seven overarching CI systems. The detailed geospatial data are rasterized into a harmonized and consistent dataset with a resolution of 0.10 × 0.10 and 0.25 × 0.25 degrees. The dataset can be applied to explore the current landscape of CI, identify CI hotspots, and as exposure input for large-scale risk assessments

Improved assessment of rainfall-induced railway infrastructure risk in China using empirical data

Rainfall-induced hazards, such as landslides, debris flows, and floods, cause significant damage to railway infrastructure. However, an accurate assessment of rainfall-induced hazard risk to railway infrastructure is limited by the lack of regional and asset-tailored vulnerability curves. This study aims to use multisource empirical damage data to generate vulnerability curves and assess the risk of rainfall-induced hazards to railway infrastructure. The methodology is exemplified through a case study of the Chinese national railway infrastructure. Regional- and national-level vulnerability curves are derived based on historical railway damage records. These curves are combined with the daily precipitation data and the railway infrastructure market value to estimate regional- and national-level risk. The results show large variations in the shape of the vulnerability curves across the different regions. The railway infrastructure in Northeast and Northwest China is more vulnerable to rainfall-induced hazards due to low protection standards. The expected annual damage (EAD) ranges from 1.88 to 5.98 billion RMB for the Chinese railway infrastructure, with a mean value of 3.91 billion RMB. However, the risk to railway infrastructure in China shows high spatial differences due to the spatially variations of precipitation characteristics, exposure distribution, and vulnerability curves. The South, East, and Central provinces have a high risk of rainfall-induced hazards, resulting in the average EADs of 184 million RMB, 176 million RMB, and 156 million RMB, respectively, whereas the risks in the Northeast and Northwest provinces are estimated to be relatively lower. The usage of multisource empirical data enables risk assessments that include spatial details for each region. These risk assessments are highly necessary for effective decision making to achieve infrastructure resilience

The impacts of coastal flooding and sea level rise on critical infrastructure: a novel storyline approach

2. Constructing a storyline framework 3. Methods: Storyline quantification 4. Storyline foundation: the three events 5. Results 6. Discussion 7. Conclusion Disclosure statement Additional information References Appendixes Full Article Figures & data References Citations Metrics Licensing Reprints & Permissions View PDFView EPUB ABSTRACT This study presents an event-based storyline framework to assess the influence of future climatic and socioeconomic conditions on coastal flood impacts to critical infrastructure. The framework combines well-established quantitative methods of sea level rise, coastal inundation, and critical infrastructure (CI) physical damage assessments into an integrated modelling approach. We apply our approach to re-imagine three historic events: storm Xaver, storm Xynthia , and a storm surge event along the coast of Emilia Romagna (Italy). Our results indicate that northern Germany would benefit mostly from coordinated adaptation action to reduce the flood impact, whereas the southwestern coast of France would find the highest damage reduction through asset-level ‘autonomous’ adaptation action. Our approach helps to improve the scientific understanding of how coastal flood risk are assessed and best managed, and forces a distillation of the science into an accessible narrative to support policymakers and asset owners to make progress towards more climate-resilient coastal communities

Quantifying climate risks to infrastructure systems: A comparative review of developments across infrastructure sectors

Funder: Climate Compatible Growth Programme funded by the UK FCDOFunder: Swiss Federal Office of Energy (SFOE)Infrastructure systems are particularly vulnerable to climate hazards, such as flooding, wildfires, cyclones and temperature fluctuations. Responding to these threats in a proportionate and targeted way requires quantitative analysis of climate risks, which underpins infrastructure resilience and adaptation strategies. The aim of this paper is to review the recent developments in quantitative climate risk analysis for key infrastructure sectors, including water and wastewater, telecommunications, health and education, transport (seaports, airports, road, rail and inland waterways), and energy (generation, transmission and distribution). We identify several overarching research gaps, which include the (i) limited consideration of multi-hazard and multi-infrastructure interactions within a single modelling framework, (ii) scarcity of studies focusing on certain combinations of climate hazards and infrastructure types, (iii) difficulties in scaling-up climate risk analysis across geographies, (iv) increasing challenge of validating models, (v) untapped potential of further knowledge spillovers across sectors, (vi) need to embed equity considerations into modelling frameworks, and (vii) quantifying a wider set of impact metrics. We argue that a cross-sectoral systems approach enables knowledge sharing and a better integration of infrastructure interdependencies between multiple sectors.</jats:p

Quantifying climate risks to infrastructure systems: A comparative review of developments across infrastructure sectors

Infrastructure systems are particularly vulnerable to climate hazards, such as flooding, wildfires, cyclones and temperature fluctuations. Responding to these threats in a proportionate and targeted way requires quantitative analysis of climate risks, which underpins infrastructure resilience and adaptation strategies. The aim of this paper is to review the recent developments in quantitative climate risk analysis for key infrastructure sectors, including water and wastewater, telecommunications, health and education, transport (seaports, airports, road, rail and inland waterways), and energy (generation, transmission and distribution). We identify several overarching research gaps, which include the (i) limited consideration of multi-hazard and multi-infrastructure interactions within a single modelling framework, (ii) scarcity of studies focusing on certain combinations of climate hazards and infrastructure types, (iii) difficulties in scaling-up climate risk analysis across geographies, (iv) increasing challenge of validating models, (v) untapped potential of further knowledge spillovers across sectors, (vi) need to embed equity considerations into modelling frameworks, and (vii) quantifying a wider set of impact metrics. We argue that a cross-sectoral systems approach enables knowledge sharing and a better integration of infrastructure interdependencies between multiple sectors.</jats:p

STUDY ON ADAPTATION MODELLING:Comprehensive Desk Review : Climate Adaptation Models and Tools

This document provides a comprehensive desk review of climate adaptation models and tools for the “Study on Adaptation Modelling” on behalf of the Directorate General for Climate Action (DG CLIMA) (CLIMA/A.3/ETU/2018/0010). This work was undertaken by a consortium led by Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC) and includes Deltares, the Institute for Environmental Studies (IVM) and Paul Watkiss Associates (PWA). This comprehensive desk review aims to address the European Commissions’ requirement to support better-informed decision making on climate adaptation at multiple governance levels: it provides a comprehensive, up-to-date and forward looking overview of the range of technical, financial, economic and non-monetary models and tools for hazards, risks, impacts, vulnerability and adaptation climate assessments. This therefore aims not only to collate current knowledge on climate adaptation assessment methodologies, but to highlight research gaps in each field. This review subsequently informs a recommended approach for adaptation modelling, detailed in further reports