WP1 – Project Coordination
D1.2 Quality Management Plan
D1.3 Data Management Plan v1
D1.4 Risk Management Plan
D1.5 – Innovation Management
D1.6 Gender and Ethics Plan
D1.7 Data Management Plan v2
D1.2 Quality Management Plan
This document describes the Quality Management Plan (QMP) that will be adopted during the course of RISKADAPT project in order to ensure high quality project results. QMP constitutes the objective of the Task 1.3: “Quality Management” which is part of WP1: “Project Management”. The effective implementation of the procedures described herein will be monitored by the Quality Manager.
The QMP is essential to ensure that the outcomes of the project will be of high quality. To this end, the RISKADAPT’s QMP that is presented in this deliverable defines the quality control and quality assurance processes that will be applied, sets quality rules and Key Performance Indicators (KPIs), and describes the project management, monitoring and internal communications, as well as decisionmaking and conflict resolution mechanisms. Furthermore, the plan provides information about the project’s document management system, along with a detailed presentation for the deliverable review and quality control processes.
Read the full deliverable here.
D1.3 Data Management Plan v1
The purpose of this document is to present the Data Management Plan (DMP) that will be followed during RISKADAPT project to make data FAIR (findable, accessible, interoperable, and reusable). It provides guidance to the RISKADAPT project beneficiaries with regards to the collection, protection, storage, transfer, and analysis of digital and physical personal data subject to European and national legislations, as well as General Data Protection Regulation (GDPR) [2]. This DMP is a living document that will be regularly updated whenever new or additional relevant data is generated or collected. Specifically, this deliverable describes the datasets that will be collected or generated and how they will be managed during the project and beyond its completion. Moreover, the document presents how the “Findable, Accessible, Interoperable, Re-usable” (FAIR) principles, data security, and ethical aspects are addressed in the project.
The DMP is a living document, which will be kept updated during the whole lifetime of the project, since data generation and collection, and therefore data management, will be active in RISKADAP for a considerable time after the submission of its initial version. The datasets may also be altered due to converging factors, such as project maturity, legislative changes, etc.
Read the full deliverable here.
D1.4 Risk Management Plan
This document presents the Risk Management Plan (RMP) that has been developed for the implementation of the RISKADAPT project. The RMP constitutes the output of Task 1.4 “Risk Management” which is part of WP1 “Project Management”. The implementation of the procedures and guidelines described in the RMP will be supervised by the Risk Manager (RM) of the project.
More specifically, the RMP specifies the methodology and procedures for the identification, analysis (in terms of likelihood and impact) and mitigation measures for any potential events/issues (related to technical, cost, schedule or any other aspect), defined as risks, that may rise during the project’s life and have a negative impact on the project’s outcomes. Moreover, a RMP includes the risk registry and mitigation strategies. The RMP is usually developed at the beginning of the project and updated regularly throughout the project’s life.
Herein, the RMP that has been developed for the project RISKADAPT and shall be followed by the consortium partners is presented, including the risk registry of the identified (initial) risks at the beginning of the project along with the corresponding mitigation measures, as well as the roles and responsibilities of the RISKADAPT consortium members regarding the risk management of the project.
Read the full deliverable here.
D1.5 – Innovation Management
T1.5 Project and Innovation Management, which is included in WP1, focuses on the overall Innovation Management Strategy for maximizing the impact of the RISKADAPT project. This deliverable establishes a structured approach and strategy towards innovation and its management, by developing the respective guidelines and procedures for the Innovation Management within the RISKADAPT project. Within this deliverable, the approach, the strategy and the means for evaluation and monitoring the overall innovation are described and explained. Additionally, this deliverable provides the quality assurance plan for any adjustment may need, in order to achieve and optimize the aligning of the RISKADAPT final results with the emerging market needs and the available technologies at the time. By highlighting and strengthening the crucial element of innovation in a structured way, RISKADAPT partners aim to maximise the innovative and exploitable potential of the project’s outcomes.
Among the key findings of this deliverable are the adoption of the Innovation Management Strategy and structure, the innovation indicators for guiding and monitoring the innovation processes and the selection of the RISKADAPT Innovation Manager who is appointed by the consortium and his responsibilities are:
- The collaboration with partners and stakeholders for monitoring the end-user needs, along with the products’ state of the art and the examination of the competition in the market via the services available and offered.
- The co-ordination of the process in which the adjustment of the planned work to the market needs will be completed successfully.
Read the full deliverable here.
D1.6 Gender and Ethics Plan
Deliverable 1.6 “Gender and Ethics Plan” is one of the eight (8) Deliverables of WP1 and is related to T1.7 “GDPR, Gender and Ethical Issues”. In this report, the following information is presented: (a) RISKADAPT’s GDPR and ethical issues management, considering legal instruments and guidelines as well; (b) RISKADAPT’s approach on gender equality concerning aims, actions and measures, resources and expertise that are dedicated for implementation and the method of evaluation for the period 2023-2026. The partners have the general responsibility for ensuring that research is carried out in accordance with these guidelines, and for ensuring that clients and other parties in the research agree to comply with its requirements.
Read the full deliverable here.
D1.7 Data Management Plan v2
The purpose of this document is to present the updated version of the Data Management Plan (DMP) that will be followed during RISKADAPT project to make data “Findable, Accessible, Interoperable, Re-usable” (FAIR). It provides guidance to the RISKADAPT project beneficiaries with regards to the collection, protection, storage, transfer, and analysis of digital and physical personal data subject to European and national legislations, as well as General Data Protection Regulation (GDPR) [2].
Specifically, this deliverable describes the datasets that will be collected or generated and how they will be managed during the project and beyond its completion. Moreover, the document presents how the FAIR principles, data security, and ethical aspects are addressed in the project. The DMP is a living document, which will be kept updated during the whole lifetime of the project, since data generation and collection, and therefore data management, will be active in RISKADAPT for a considerable time after the submission of its initial version. The datasets may also be altered due to converging factors, such as project maturity, legislative changes, etc.
Read the full deliverable here.
WP2 – User Requirements, Architecture
D2.1 – CoPs, Co-designed User Requirements
D2.2 - Specifications, Architecture
D2.1 – CoPs, Co-designed User Requirements
The aim of this report is to: (a) identify and engage relevant stakeholders and form Communities of practice (CoPs); (b) collect and identify the social impacts and user needs; as well as (c) specify the user requirements, that will be translated into technical specification in Task 2.2. In three pilots an explorative study incorporating a literature review, content analysis, interviews, questionnaires and focus groups etc. was conducted to gather information on social impacts, user needs, and user requirements. The three pilots encompass the Polyfytos Bridge in North Western Macedonia in Greece, the energy transmission grids in Finland and the Cattinara hospital in Trieste in Italy. After the identification of the stakeholders for each pilot an approach was developed to engage them in stakeholder groups, e.g. Communities of Practice (CoPs).
The findings of data collection in Pilot 1, 2 and 3 show that social impacts and user needs differ, but in general access to services, and timely information after a climate induced disaster are needed. For Pilot 1 (the Polyfytos Bridge in North Western Macedonia in Greece) this means information on alternative routes, continuous access to public services, the state of the art of the bridge and the opening of the bridge. Concerning Pilot 2 (energy transmission grids in Finland) the consequences of a power failure have a huge impact on society and economy and information on future climatological developments, particularly on icing, are important. With regard to Pilot 3 (Cattinara Hospital in Trieste in Italy) access to health services are needed as well as information on public services, transportation and infrastructure. In addition, the user requirements resulting from the pilots have been identified and analysed. The requirements have many similarities, such as addressing risks, access to the data base, user-friendly interface and reliable information. These requirements will be used as the main input in T2.2.
Stakeholder engagement is relevant for the project because end-users of the RISKADAPT platform have valuable feedback on the platform that will be developed contributing to the rebuilding or renovating of infrastructure after a severe weather event and users of the infrastructure – bridge, energy grids and hospital – give insight into their needs.
The Communities of Practice organized as meetings, workshops and sessions are meant to engage stakeholders, particularly end users, in the development of the RISKADAPT platform. At the same time, the developers of the RISKADAPT platform learn from the input of stakeholders in terms of performance of the platform. Additional information based on secondary data for pilot 1 and pilot 2 shows that social impacts as result of a bridge closure may lead to cascade effects, varying from significant disruptions to mobility, emergency response, and the transportation of essential goods to isolation of communities that, in turn, lead to life-threatening delays in accessing healthcare and emergency services. Disaster preparedness contributes to less social impacts. Therefore, citizens need to be aware of the situation – in this case the energy situation – and learn how to deal with a situation of energy outrage.
The key finding of this deliverable is that user requirements, user needs and social impacts are not always easy to identify due to the type of infrastructure. Generally, health services are organized locally, e.g. a hospital with a regional function, while energy infrastructure is organized nationally and a bridge may have a regional as well as an international function. In addition, there are many users of the infrastructure. Therefore, we decided to identify the main stakeholders for each pilot and worked on their active involvement in the development of the RISKADAPT platform.
Read the full deliverable here.
D2.2 - Specifications, Architecture
RISKADAPT will provide, in close cooperation with the end-users/other stakeholders, a novel, integrated, modular, interoperable, public and free-of-charge, customisable user-friendly platform (PRISKADAPT), to support systemic, risk-informed decisions regarding adaptation to Climate Change (CC) induced compound events at the asset level, focusing on the structural system. PRISKADAPT will explicitly model dependencies between infrastructures, which, inter alia, will provide a better understanding of the nexus between climate hazards and social vulnerabilities and resilience. Moreover, this project will identify gaps in data and propose ways to fill them, so as to advance the state-of-the-art in asset level modelling by means of utilizing advanced climate science to predict CC forcing on the structure of interest and structural analyses that are customised to the specific structure of interest. The proposed approach considers all major CC induced load effects in tandem with material deterioration, novel probabilistic environmental Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) of structural adaptation measures as well as a new model to assess climate risk that will combine technical with social risk assessments. PRISKADAPT will provide values to a set of indicators for each asset of interest, quantifying primary parameters and impacts, and will deliver all the required information for adaptation decisions in the form of a Model Information System (MIS). PRISKADAPT will be implemented in the case studies of the project pilots that involve specific assets, however, it will permit customisation with local parameters and data, so it can be applied across Europe for CC adaptation decisions involving assets of similar function, that are exposed to multiple climate hazards.
Deliverable 2.2 “Specifications, Architecture” aims to: (a) develop the baseline specification of the system functionalities, to meet the needs identified in T2.1 taking into account existing national and international regulations; (b) describe the modules of the RISKADAPT platform; (c) present the RISKADAPT system architectural specification; (d) identify the interfaces of the internal components and the foreseen interactions between the components, as well as the interfaces for interoperability of the system with RISKADAPT applications, in order to guide the development in a way that will later on enable their integration into the system.
This deliverable plays a pivotal role in the development of RISKADAPT by serving as the foundation for subsequent technical work in WP3, WP4, and WP5. It ensures a structured approach to implementing the platform, thereby enhancing resilience through improved climate risk assessment and adaptation strategies at the asset level.
The primary beneficiaries of this work include RISKADAPT technical partners, public authorities, infrastructure owners and operators, researchers, technology providers, and policymakers involved in climate adaptation planning. By providing an openly accessible framework, the deliverable enables these stakeholders to adopt and customize PRISKADAPT for diverse infrastructure types across Europe, ensuring broad applicability. By establishing clear system specifications and architecture, this deliverable ensures the successful development and deployment of PRISKADAPT, ultimately contributing to stronger, data-driven climate adaptation strategies across Europe.
Read the full deliverable here.
WP3 – Climate Data, CC Forcing, Multi-Hazard Modelling
D3.1 – Access to EO data
D3.2 – Extreme value distributions for Europe – present climate
D3.3 – Extreme value distributions-future climate
D3.4 – Hydrologic/hydraulic modelling regarding floods
D3.5 – Model of high wind loading on a high rise building
D3.1 – Access to EO data
This deliverable describes the Earth Observation (EO) data sources used in the RISKADAPT project. The most important data source is the Copernicus Climate Store. The data types include in-situ, remote sensed, and model-based data. Model-based data can be divided between historical reanalyses based on observations and climate model runs that simulate the climate system’s response to a scenario for future emissions. Local observational data from national data providers can be used to complement the Copernicus data. This deliverable will give an overview of the EO data directly available for the partners. The use of open data sources through API interfaces is encouraged and demonstrated.
Read the full deliverable here.
D3.2 – Extreme value distributions for Europe – present climate
RISKADAPT will provide, in close cooperation with the end-users/other stakeholders, a novel, integrated, modular, interoperable, public and free, customisable user-friendly platform (PRISKADAPT), to support systemic, risk-informed decisions regarding adaptation to Climate Change (CC) induced compound events at the asset level, focusing on the structural system. PRISKADAPT will explicitly model dependencies between infrastructures, which, inter alia, will provide a better understanding of the nexus between climate hazards and social vulnerabilities and resilience.
Moreover, this project will identify gaps in data and propose ways to overcome them and advance the state of the art of asset level modelling through advanced climate science to predict CC forcing on the structure of interest, structural analyses, customised to the specific structure of interest, that consider all major CC induced load effects in tandem with material deterioration, novel probabilistic environmental Life Cycle Assessment (LCA) and Life Cycle Cost (LCC) of structural adaptation measures and a new model to assess climate risk that will combine technical risk assessment with assessment of social risks. PRISKADAPT will provide values to a set of indicators for each asset of interest, quantifying primary parameters and impacts, in the form of a Model Information System (MIS) that will provide all required information for adaptation decisions. PRISKADAPT will be implemented in the case studies in the pilots that involve specific assets, however, it will permit customisation with local values of parameters and data, so it can be applicable throughout Europe for CC adaptation decisions involving assets of similar function, exposed to multiple climate hazards.
This report is one of the three deliverables of WP3 “Climate Data, CC Forcing, Multi-Hazard Modelling” and corresponds T3.1 “Climate data for hydrological analyses, wind and rain forcing and material degradation. Extreme Value Analyses” of the RISKADAPT project. To meet the aim of this Task, in this report the terminology, methods, and tools that can be used to perform statistical extreme value analysis on climate data are presented. Input data can mainly come from reanalysis data (like ERA5) or from in-situ time series measurements. In addition, and as the focus of this report is on the analysis of present climate, i.e., approximate for years 1970-2020, pointers to Copernicus Climate Data Store (CDS) data sets and tools are provided that can be used to evaluate risks caused by extreme events for infrastructure, especially those that are related to project’s pilots.
This report provides methodological guidance on the application of Bayesian hierarchical modelling techniques to improve the reliability of extreme value analysis by incorporating spatial and temporal dependencies. By quantifying return levels and return periods of extremes of key climate variables, these statistical tools provide essential methods in studying climate change induced risks for infrastructure. We evaluate climate data sources relevant to extreme weather and hydrological events, including precipitation, wind speed, and temperature extremes. The report demonstrates statistical techniques using real-world datasets, with a particular focus on case studies relevant to RISKADAPT pilot sites. This deliverable also includes practical examples of extreme value analysis using Python-based computational tools, enabling application in different infrastructure contexts. The extreme value analysis presented here is relevant for climate scientists, engineers, policymakers, and infrastructure managers involved in climate adaptation planning.
However, while reanalysis data sets presented here, such as ERA5 Land, provide valuable insights, limitations in spatial and temporal resolution necessitate careful methodological considerations, including downscaling approaches, which will be dealt in more detail in other deliverables of the RISKADAPT project.
Read the full deliverable here.
D3.3 – Extreme value distributions-future climate
This deliverable will complement the deliverable D3.2. Continuing explaining the methods and tools for statistical extreme value analysis for climate variables, this report focuses on analysis of the future climate, approximately for years 2040-2100. The input data are produced either by climate model simulations or by historical reanalyses. We provide pointers to Copernicus CDS data sets and tools that can be used to evaluate risks caused by extreme events for infrastructure, especially those that are related to RISKADAPT project’s pilots. The deliverable is public and the intended audience includes project partners and anyone interested in extreme value analysis.
Read the full deliverable here.
D3.4 – Hydrologic/hydraulic modelling regarding floods
The primary objective of Deliverable D3.4 is to outline the hydrological and hydraulic modelling processes required to estimate hydrodynamic loads on the piers and abutments of any bridge, with a special focus on the Polyfytos Bridge located at the Polyfytos Lake, Greece (namely the Pilot 1 of the RISKADAPT project). This includes obtaining all the necessary input data (i.e., topography, land use, hydrologic soil group, extreme precipitation data, and lake bathymetry), as well as setting up the hydrological model (to convert extreme precipitation into extreme discharges) and the hydraulic model (to propagate discharges along the river/reservoir and calculate hydrodynamic loads on bridge piers under present and future climate projections).
The Aliakmon River catchment runoff (feeding the Polyfytos Lake) was estimated using the 2D hydrological model based on extreme precipitation and catchment characteristics (i.e., topography, land use and soil type). Extreme events were investigated by considering three return periods of extreme rainfall (i.e., 50, 100 and 1.000 years). Simulations of the Aliakmon River catchment model for the present climate determined that a 72-hour rainfall duration resulted in the highest discharge peaks, with maximum discharges at the inflow to the Polyfytos Lake being 2.400, 3.100 and 6.350 m³/s for the respective return periods. Future climate scenarios showed varying impacts on peak discharges, with some predicting reductions and others increases.
Hydraulic modelling assessed hydrodynamic loads and scour risks on the piers of the Polyfytos road bridge, which spans over the Polyfytos Lake reservoir. The study incorporated geometric and hydrological data to simulate unsteady flow conditions and evaluate the impact on scouring processes around bridge piers using a full-2D numerical hydraulic model. The hydraulic modelling results provided essential time series data for further analysis, including water depths, water surface elevations, depth-averaged flow velocities, and discharges at specified locations. Despite the lack of detailed bathymetry and sediment composition data, the analysis indicated that water flow velocities at the bridge piers remain low during high-water events, suggesting a low risk of scour formation.
Thus, the results presented in this deliverable provide the necessary input information for Task 4.2, dealing with material degradation and structural vulnerability of structures exposed to extreme events. Additionally, the deliverable contributes to Milestone 6, entitled “Assessment of hydrodynamic loads on piers/abutments of bridges.”
Deliverable D3.4 is meant primarily for other partners of the RISKADAPT project, mainly to support the work of Task T4.2, but also for other practitioners who would like to estimate the impact of hydrodynamic loads and scour risks on the bridge piers to learn about the input data and the models needed to support this action, especially in the data-scarce catchments where global data (e.g., precipitation) has to be used.
D3.5 – Model of high wind loading on a high rise building
This report showcases the development and application of a general methodology to estimate the atmospheric load on tall buildings in case of extreme weather events, that shall become more frequent and intense in Europe due to climate change. In particular, the methodology herein presented enables the derivation of a semi-empirical function for an easy, fast and direct estimation of the atmospheric load on tall buildings. Such a methodology is applied to the case study of Cattinara Public Hospital of Trieste (North-East Italy) that is the Pilot 3 of the RISKADAPT project. Such a case study has been selected because of two key features: the region of Trieste is characterised by the Bora wind, which is a high-intensity wind that periodically impacts the city; and the Cattinara Hospital is a relatively tall building located on the top of a hill just outside the city, thus highly exposed to the Bora wind. For these reasons, Pilot 3 is a unique and ideal site for the purposes of the present study.
The strong wind and wind-driven rain are the two meteorological variables considered to estimate the atmospheric load on buildings which, in turn, is quantified as pressure load at the building facades. The facade pressures load is the key variable used to assess structural vulnerability of buildings and infrastructures. The present study is carried out through a chain of multiscale numerical simulations, which are strategically linked together to transport and convey information from the climatic timespatial scales, the meteorological mesoscale and the very small, local, building scale in the final result.
To this scope, a downscaling methodology has been adopted and applied for a detailed numerical study of the Cattinara Hospital, which was selected as representative of a tall building in Europe exposed to strong wind, i.e. the Bora wind, due to the peculiar local meteorology. First, the past and future climate in the Trieste region has been studied, scrutinising state-of-the art climatic databases (e.g., EURO-CORDEX and ERA5) which are the results of the most advanced climatic simulations for the European continent (scale 100 km). Second, to further ground the study in the real-world settings, a specific extreme event of strong Bora wind (registered in February 2012) has been selected and reproduced numerically utilising the Weather Forecast and Research (WRF) model, a state-of-the-art meteorological model. Such a simulations reproduce the weather conditions at the regional scale (spatial scale of 1 km) and allow to analyse in detail the meteorological processes and dynamics, providing accurate and realistic atmospheric variables in the neighbourhood of the Cattinara Hospital.
Third, the output from such meteorological simulation is used to setup very-highly resolved numerical simulations that reproduce the wind flow in the building area (spatial scale of 10 m) to gain insight of the local circulation around the buildings. These last simulations have been carried out using highly accurate techniques and turbulence models developed in the field of Computational Fluid Dynamics and using the open-source software OpenFOAM. The result of this numerical downscaling procedure made it possible to investigate the climatology and meteorology of the characterising the Trieste area at different scales, as well as to evaluate the atmospheric load on the Cattinara Hospital in the most realistic way for a typical extreme of wind.
Based on this study, a semi-empirical function for estimating pressure load on buildings is derived as a practical tool for technical and non-technical stakeholders. An extensive parametric study has been performed running several very-high resolved numerical simulations of the Cattinara Hospital case study by estimating the pressure load at the building facades under different wind intensities (from weak to exceptionally strong) and. The results have been synthetised in a set of functions estimating the atmospheric building load knowing the averaged mean wind velocity impacting on the structure.
The functions have been extended to include also the contribution to the load given by the wind-driven rain, by utilising well-established relations available in the literature. Overall, the estimating functions can be directly used in the configuration of single building on a gently slope terrain, as that one of Cattinara Hospital.
It is worth to notice that a universal function estimating the pressure load from the averaged wind speed can be hardly derived, due to the complex interaction between the terrain topography and themorphological elements (other tall buildings in the neighbourhood) that are specific features of each case study. However, the methodology developed and applied in the present study is a general and operational strategy that can be repeated and adapted to a wide variety of case studies, therefore representing a general result of applicative interest for infrastructure builders and for different types of technical and non-technical stakeholders.
Read the full deliverable here.
WP4 – Multi-Hazard Vulnerability and Adaptation, Structural Resistance Integration in Lifecycle Analyses
D4.1 – Material Degradation, Structural Vulnerability
D4.2 – Structural resistance integration in lifecycle analyses
D4.1 – Material Degradation, Structural Vulnerability
The current deliverable presents a methodological approach to assess the present and future structural vulnerability, of selected infrastructures (pilots), in connection to the mechanical properties of the materials and their degradation evolution under adverse weather conditions such as among others, extreme winds, heavy rains, and ice, taking also into account the effects of Climate Change (CC). First, an approach for the estimation of the time-dependent corrosion degradation of structural steel and reinforcing steel bars either in normal or prestressed concrete is presented. Then, the results of the above process are elaborated in the estimation of structural vulnerability to Pilots 1-3 of the project both at present and future times. More specifically, Pilot 1 refers to “the Polyfytos bridge” constructed over the lake Polyfytos near the town of Kozani in Greece, operating in less than full capacity for some period due to important structural problems because of the partial loss of the required prestressed tendons capacity induced by severe corrosion. Pilot 2 considers power transmission towers in Finland. For those towers, the effect of CC on atmospheric icing conditions and high winds to power transmission towers (ice load combined with winds) was evaluated. Pilot 3 refers to Cattinara Hospital which is a major high rise public hospital building in Trieste, Italy, exposed to high winds, suffered in the past, such as in February 2012, where nonstructural damages in fittings and plasters were produced. Pilot 4 of RISKADAPT project is related to the assessment of glass window damage in high rise buildings in Hong Kong due to high wind flows and wind-driven rain. The approach followed for Pilot 4 differs from that in Pilots 1-3. In specific, glass windows are non-structural elements, and they do not affect the structural capacity of the building, but they only contribute to serviceability. Thus, for Pilot 4, to point out the effect of extreme weather on high rise buildings, a description of Hong Kong regulations on glass windows was made followed by a history of failure events attributed to high winds. Moreover, for that pilot, algorithms for the glass window damage were developed and presented in RISKDAPT D3.6. The deliverable ends providing information on possible adaptation options that are applicable to the assets of Pilots 1-3. First, techniques with low carbon precast concrete and their properties are presented. These materials, apart from any novel technical solutions may offer, also aim at shaping policies (decarbonization, circular economy) and standards (precast concrete and sustainability). Besides precast concrete, additional rehabilitation techniques such as the restoration of the structural steel (which could be applicable to Pilot 2) or other refurbishment techniques relevant to the reinforcing steel in concrete structural components (which could be applicable to Pilots 1 and 3) through fiber glass/carbon polymers or steel jacketing are presented.
In general, under operating loads, the structural elements of a structure are normally under compressive forces and relatively small values of biaxial bending moments whereas under extreme transversal/horizontal loadings, such as an unexpected high value of wind pressure or flood conditions a threshold approach of limit states, can be followed to categorize system components into safe and unsafe conditions. This uncertainty in structural behavior is considered by modelling the load effects on the structure, the geometrical data, the strength, the toughness and the mechanical characteristics which can change due to the material degradation, as random variables. An appropriate methodological framework is applied in RISKADAPT project for assessing the structural vulnerability of the structures considered in the Pilots 1-3. More specifically, first the methodology follows appropriate standards and models for estimating the material degradation of structural materials (concrete and steel) based on climate and environmental parameters. For the climate parameters such as temperature and relative humidity, data based on the Shared Socioeconomic Pathways (SSPs) were provided by FMI. Then, the aforementioned methodology is applied on Pilots 1-3 to evaluate the
expected material degradation issues and any possible effects on structure’s condition and vulnerability. The vulnerability of the structures of Pilots 1-3 is assessed by performing appropriate structural analyses and estimating the structural risk under various scenarios of the climatic hazards considered in each case (i.e., extreme wind, ice loads) both in present and future times. Results obtained show that the impact of CC on structural performance cannot be generalised. Rather, structural performance should be assessed individually for each structure, considering differences of the above impact in different European regions and the peculiarities of each structure. For instance, in the case of energy transmission towers in Finland (pilot 2), the impact of CC is positive for structural safety as it lowers the weight of the ice on the lines. On the other hand, CC promoting heavy rains can be detrimental for old bridges subjected to scouring. This is even more so in the case of highway bridges subjected to de-icing salts in the winter (pilot 1). In the case of the Italian hospital (pilot 3), even though CC will increase the temperature and, thus, the rate of corrosion, the high safety factors provided by the codes keep adequate structural safety. Finally, regarding glass window damage the past experience of recorded events show that high-rise buildings especially in areas prone to cyclones such as Hong Kong (Pilot 4) may lead to extensive damages affecting the serviceability of the building and sometimes having significant societal impact such as injuries or deaths.
Included in the last part of the document are potential adaptation options that are applicable for rehabilitation or strengthening of the structures considered herein. The evaluation of each adaptation option will be performed in a following stage of the project. The results presented in the deliverable constitute the output of the structural analysis tasks and provide input for the LCA/LCC analyses (under T4.5) and will also be fed in the RISKADAPT platform (under WP5). Moreover, external stakeholders including local and regional authorities that own constructed facilities, business or private owners of facilities, developers, investors, financiers, insurers, as well as the supply side of structural adaptation communities (civil engineers, contractors, material and product suppliers) and civil protection authorities may benefit from the work presented in the current deliverable.
D4.2 – Structural resistance integration in lifecycle analyses
This deliverable, as part of the EU-funded project RISKADAPT (Grant Agreement No. 101093939), addresses the objectives of Task 4.5: Probabilistic LCA/LCC Model Development. It introduces an innovative probabilistic framework for Life Cycle Assessment (LCA) and Life Cycle Costing (LCC), with a focus on structural resistance integration for infrastructures impacted by climate change-induced extreme weather events. The primary purpose is to assess environmental and economic impacts of restoration measures and propose sustainable adaptation strategies by enhancing conventional LCA/LCC methodologies with uncertainties and variabilities arising from extreme weather events. It seeks to enable practitioners and decision-makers to evaluate structural adaptation options, balancing environmental sustainability and economic efficiency.
This deliverable describes and demonstrates a novel probabilistic LCA/LCC framework called the Predictive Risk-Integrated Dynamic Environmental Life Cycle Analyses approach (PRINTED). This methodology integrates uncertainty analysis through probabilistic risk assessment, evaluates potential adaptation options for infrastructure considering both environmental and economic impacts, and uses a Monte Carlo simulation to analyse variability in results and assess decision-making robustness under different climate scenarios. The methodology is illustrated through a case study of a power transmission tower in Finland, which constitutes Pilot 2 of RISKADAPT project. Various structural adaptation options, such as high-strength steel (HSS) and fiber-reinforced polymer (FRP) strengthening, were analysed for their performance under extreme climate conditions.
This deliverable contributes to RISKADAPT by offering a scalable framework to incorporate probabilistic assessments in infrastructure lifecycle analyses, enabling informed decision-making for infrastructure resilience against climate risks, and promoting sustainable construction practices by identifying eco-friendly and cost-effective adaptation solutions.
The primary beneficiaries of this work include LCA practitioners and experts interested in applying probabilistic approaches to lifecycle assessments, decision-makers and market players in green construction seeking sustainable and resilient solutions for infrastructure adaptation, and environmental NGOs and policymakers focused on mitigating climate change impacts through evidence-based strategies.
The probabilistic LCA/LCC framework addresses the gap in current methodologies by accounting for uncertainties in climate scenarios and adaptation impacts. HSS adaptation scenarios demonstrated lower environmental impacts due to material optimisation, while FRP strengthening provided a feasible option for corroded structures. Climate scenarios significantly influenced failure probabilities, with results highlighting the importance of region-specific assessments. The methodology, demonstrated with publicly available datasets, ensures broader applicability and cost-effectiveness for stakeholders.
This deliverable advances the understanding of sustainable infrastructure adaptation, providing a robust, probabilistic approach that aligns with the overarching goals of the RISKADAPT project to mitigate climate risks effectively.
WP5 – PRISKADAPT, MIS and Data Gaps
D5.1 – Data Management System
D5.4 – PRISKADAPT/MIS v1
D5.1 – Data Management System
This document, Deliverable 5.1 (D5.1), presents the development and implementation of the Data Management System (DMS) within the RISKADAPT project. The DMS, developed as part of Task 5.5, is a comprehensive framework for collecting, storing, managing, and distributing diverse datasets and analytical tool results essential for climate risk assessment and adaptation planning. By ensuring seamless data integration, scalability, and security, the DMS serves as the backbone of the RISKADAPT platform, enabling robust decision-making in climate resilience initiatives.
The DMS is designed with several key objectives in mind. It establishes a modular and scalable architecture that supports efficient data handling and adaptation to emerging project needs. It facilitates interoperability across diverse systems through open standards, universal APIs, and GIS compliance, while also incorporating advanced security measures. Additionally, the DMS integrates an Open Geospatial Consortium (OGC)-compliant GIS platform to enable sophisticated spatial analysis and visualization, critical for effective climate adaptation planning. The development of the DMS follows an Evolutionary Prototyping (EP) methodology, which emphasizes iterative refinement and responsiveness to stakeholder feedback. This approach ensures that the system evolves dynamically to meet changing project requirements and aligns closely with the needs of technical partners and end-users. By incorporating insights from early prototypes and user evaluations, the DMS has been progressively enhanced to support comprehensive data management and integration.
The architecture of the DMS is organized into six modular layers, each serving distinct purposes in the data management workflow. The Ingestion Layer can collect and preprocess data from diverse sources (existing and potential), including climate models, sensors, and project modules. The Storage Layer provides robust solutions for both structured and unstructured data, enabling efficient retrieval and ensuring resilience through data archiving and backup mechanisms. The Processing Layer transforms raw data into actionable insights through analytical workflows, while the Assimilation Layer harmonizes and integrates data outputs, ensuring compatibility with open standards and facilitating API-based sharing. The Observability Layer monitors system health and performance, and the Security Layer enforces access control and ensures data encryption, safeguarding information throughout the system. Key capabilities of the DMS include its OGC-compliant GIS platform, which supports geospatial data integration and analysis, and its universal API, which enables seamless communication between diverse system modules. Additionally, the DMS offers critical business services such as data search and retrieval, secure data sharing, and subscription/notification services that streamline workflows and ensure real-time access to updates and critical insights.
The development and implementation of the DMS provide substantial benefits to the RISKADAPT project by enabling efficient workflows, improving the integration of diverse data sources, and supporting critical functionalities such as climate risk analysis and adaptation planning. It is expected to enhance collaboration among technical partners and stakeholders while setting a benchmark for secure, scalable, and interoperable data management solutions in climate adaptation contexts. The deliverable primarily serves RISKADAPT project partners, particularly technical teams engaged in data integration, storage, and GIS development. It also provides valuable insights for external stakeholders, such as researchers and practitioners working on climate adaptation platforms or similar data-intensive applications.
Looking ahead, the DMS will continue to evolve as a robust and adaptive framework, supporting the RISKADAPT platform’s goal of building climate resilience. Future efforts will focus on the integration of new data, expansion of its functionalities, refinement of the integration processes, and incorporation of insights from future demonstrations and user feedback. The DMS provides a strong foundation for managing complex data interactions, enabling informed and proactive decision-making in the face of changing climate risks.
D5.4 – PRISKADAPT/MIS v1
Climate change (CC) is increasingly exacerbating the frequency and intensity of natural hazards, posing a significant threat to the resilience of our built environments. Disruptions to these critical assets can have far-reaching consequences, hindering the movement of people, goods, and services, and ultimately impacting economic growth and societal well-being. To realize these objectives, a platform (PRISKADAPT) is designed to benefit a wide range of stakeholders involved in climate risk assessment and adaptation. Typical stakeholders may be asset owners, infrastructure managers, climatologists, engineers and researchers.
The PRISKADAPT platform incorporates a suite of modules and datasets designed to address various aspects of CC impact assessment and adaptation:
- TPRISKADAPT: A versatile module combining CC loadings, structural data, risk and LCA/LCC assessments, as well as adaptation solutions. A key feature of the module is its authoring tools, which allow users to design and customize workflows through functional flow block diagrams, ensuring modular and dynamic configurations (presented in D5.2).
- Social impacts: Social impact is evaluated by quantifying changes in social welfare (potential gains or losses) based on the asset’s condition or damage level. (the outcomes of this module are presented in D5.3)
- Total Risk Assessment (TRA): The Total Risk Assessment provides a comprehensive evaluation of both technical and social risks, allowing for the analysis of combined social and technological measures to determine the best risk adaptation solution strategies. This methodology’s modular, interoperable, and adaptable design facilitates the integration of new data and the incorporation of emerging social impacts.
- Model Information System (MIS): The module provides the data necessary to evaluate and compare various adaptation measures. These indicators span environmental, social, economic and technical factors, enabling a detailed assessment of each adaptation strategy’s effectiveness, feasibility, and impact.
This document is related to the PRISKADAPT description defined in Task 5.4, Total Risk Assessment framework defined in Task 5.3 and a Model Information System developed in Task 5.7. Leveraging these comprehensive methodologies, a suite of modules has been developed to achieve the framework’s objectives and address identified gaps.
This comprehensive approach enhances the risk of both existing and newly added assets, enabling them to better withstand the impacts of CC. By integrating climate risk assessments and adaptation strategies, the approach provides a clear framework for identifying vulnerabilities and opportunities for improvement.
WP6 – Demonstration and Validation Activities in Pilot Cases. Third Party Use of TPRISKADAPT/MIS
D6.1 – Dissemination and Communication Plan v2
D6.3 - Evaluation Pilot 1
D6.1 – Dissemination and Communication Plan v2
Read the full deliverable here.
D6.3 - Evaluation Pilot 1
This document, Deliverable 6.3 (D6.3), presents the outcomes of Task 6.1.1 (T6.1.1) within the RISKADAPT project. The primary goal of this task is to evaluate the PRISKADAPT/MIS platform during its demonstration at Pilot 1, focusing on a Road Bridge in Greece. The overarching objective is to assess the technical performance, operational feasibility, and potential for adoption of the platform among end users and stakeholders, while also gathering feedback to inform future enhancements. As part of T6.1.1, a workshop and demonstration event was organized (on February 13th, 2025) to present the current status of the platform for Pilot 1 and initiate the evaluation process. The methodology followed is in line with ISO 22398:2013 guidelines for exercises and testing, ensuring a systematic approach to planning, conducting, and improving the activities. Through iterative cycles of feedback, the platform is expected to evolve into a tool that meets the dynamic needs of engineers and scientists beyond the project consortium.
The workshop included a presentation of the technical analysis conducted in Pilot 1 and its implementation within the platform. The demonstration session involved a detailed description and training on the platform, followed by a hands-on session, where all attendees had the opportunity to use the platform under the guidance of the training team. At the end of the event, the evaluation process conducted through a technical questionnaire. The platform is accessible online, allowing all project partners and users from the Region of Western Macedonia (RWM) to continue testing and evaluating it.
The results of the questionnaire demonstrated overall positive feedback from participants. Most attendees found the workshop, training activities, and provided materials to be clear and relevant. The majority were able to achieve the specified goals across the various modules with minimal errors and reported that the system was generally easy to use. However, a smaller percentage experienced difficulties, particularly with navigating the map and exploring assets. While many participants believed the platform could enhance task efficiency, some suggested improvements to better meet their expectations. Key recommendations for future enhancements included resolving login and font formatting issues, refining 3D modelling and mapping features, and providing more information on climatological models. Additionally, some participants requested further explanations of graphs and data, easier uploading of multiple infrastructures, and more comprehensive datasets to support expert analysis and 3D representation.
D6.3 represents the first evaluation of the PRISKADAPT platform and contributes to the achievements of the RISKADAPT project by initiating the iterative testing and feedback process. This process will enhance the platform’s robustness and relevance. Specifically, the demonstration activities and evaluation feedback provide valuable recommendations to ensure the platform aligns with the
practical needs of end-users, including stakeholders from Pilot 1, engineers, policymakers, and researchers involved in environmental management, climate risk adaptation, and data-driven decision-making. These improvements will support the development of more effective resilience strategies for critical infrastructures.