WP1 – Project Coordination
D1.2 Quality Management Plan
D1.3 Data Management Plan v1
D1.4 Risk Management Plan
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.
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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.
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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.
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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.
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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
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.
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WP3 – Climate Data, CC Forcing, Multi-Hazard Modelling
D3.1 – Access to EO data
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
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D3.3 – Extreme value distributions-future climate
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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.
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WP4 – Multi-Hazard Vulnerability and Adaptation, Structural Resistance Integration in Lifecycle Analyses
WP5 – PRISKADAPT, MIS and Data Gaps
WP6 – Demonstration and Validation Activities in Pilot Cases. Third Party Use of TPRISKADAPT/MIS
D6.1 – Dissemination and Communication Plan v2
D6.1 – Dissemination and Communication Plan v2
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