Ms. Marianthi Malioka, Prof. Nikolaos Kalyviotis (p), Prof. Vana Tsimopoulou, Prof. Nikitas Mylopoulos

Climate variability and the increasing frequency of extreme rainfall events are intensifying flood risks and exposing structural vulnerabilities in infrastructure systems. Drainage constitutes a fundamental component of the design of engineering works, as it is directly linked to flood‑risk management, highlighting its central role in resilient regional development. Yet, persistent discrepancies between preliminary drainage planning and final design—driven by incomplete topographic data, evolving project geometries, and regulatory inconsistencies—undermine the reliability of infrastructure delivery. These challenges become even more acute during construction, a phase described as one of particular vulnerability, where temporary drainage solutions often fail, leading to erosion, flooding, and costly delays.
This research proposes an integrated methodological framework that combines hydrological and hydraulic modelling with Building Information Modelling (BIM) to enhance the accuracy, adaptability, and resilience of drainage system design. By systematically comparing planning‑phase assumptions with final design outcomes across multiple case studies, the study identifies the key drivers of redesign and quantifies their impact on project performance. BIM is evaluated as a digital environment capable of unifying geometric, hydrological, and construction‑phase data, enabling dynamic updates, clash detection, and scenario‑based simulations under climate‑stress conditions.
The expected contribution lies in bridging the gap between theoretical and applied drainage design, improving infrastructure resilience to climate‑induced hydrological extremes, and providing evidence‑based guidelines for the institutional adoption of BIM in regional infrastructure planning. The findings aim to support regions in transitioning toward more adaptive, data‑rich, and climate‑responsive engineering practices—fully aligned with the focus on regional responses to global challenges.

Ms Paulin Zahn (p), Prof. Dr. Miriam Rehm

Urban heat intensification increases climate-related health risks, particularly in densely populated urban areas, while access to effective adaptation measures remains uneven across socio-economic groups. At the same time, many municipalities face financial constraints that limit their capacity to expand green infrastructure, and growing urban populations create development pressures that can lead to additional land sealing. Most studies concentrate on the distribution of existing green spaces or the consequences of elevated temperatures for socio-economic groups. The present study seeks to analyze the recent urban greening dynamics and their spatial distribution in 153 German cities between 2018 and 2023. Greening and sealing are measured using CORINE Land Cover Plus Backbone data at both city and 1 km grid levels, and compared with spatial indicators of heat exposure, socio-economic disadvantage, demographic structure, fiscal capacity, and local political characteristics to assess their spatial alignment. The descriptive analysis finds that, overall, German cities have experienced more sealing than greening between 2018 and 2023, with only seven cities showing a net increase in green space. Patterns at the city level further suggest that fiscal conditions are associated with greening dynamics, as municipalities characterized by higher debt levels, greater recourse to liquidity-alleviating loans, and lower net trade tax revenue per capita tend to exhibit stronger declines in green space. We do not find evidence that a city adopting a heat action or climate adaptation plan is linked to increased greening. We also do not find greening efforts to be concentrated in areas with higher heat exposure or greater socio-economic disadvantage at the spatial grid level, and thus cannot discern an alignment between observed greening patterns and indicators of vulnerability in our data.

Prof. Jen-Te Pai (p)

Conducted for the purposes of disaster prevention and mitigation, this study focuses on Taiwan’s industrial sector, specifically targeting industrial parks under the jurisdiction of manufacturing authorities. The research clarifies existing autonomous adaptation plans implemented by individual enterprises or parks as a whole. By integrating indicators established in previous disaster resilience research, this study develops a feasible set of Eco-DRR (Ecosystem-based Disaster Risk Reduction) indicators for Taiwan’s industrial parks to achieve the goals of environmental, social, and economic sustainability.

The research establishes an evaluation framework comprising five major dimensions: Economic Feasibility, Ecological Benefits, Disaster Risk, Human Well-being, and Social Participation. The Fuzzy Delphi method was employed to select suitable Eco-DRR indicators for industrial parks, while the Fuzzy AHP method was applied to determine the evaluation weights. Based on these methods, the study evaluates the climate change adaptation actions and infrastructure resources of various industrial parks in Taiwan. Finally, based on the evaluation results, a portfolio of disaster mitigation strategies using Nature-based Solutions (NbS) is proposed. These research findings serve as a reference for adaptation strategies rooted in ecological disaster mitigation for future industrial land development."