The water sector is facing emerging challenges, as cyber-physical threats target Supervisory Control and Data Acquisition (SCADA) systems of water utilities. A cyber-physical stress-testing platform is presented in this work, named RISKNOUGHT, which is able to model water distribution networks as cyber-physical systems, simulating the information flow of the cyber layer and the feedback interactions with the physical processes under control. RISKNOUGHT utilizes an EPANET-based solver for the physical process and a customizable network model for the SCADA system, capable of implementing complex control logic schemes within a simulation. The platform enables the development of composite cyber-physical attacks on various elements of the SCADA, including sensors, actuators, and PLCs, assessing the impact they have on the hydraulic response of the distribution network and the level of service. The platform is tested on a proof-of-concept benchmark network with promising results that demonstrate that the platform can form an innovative cyber-physical tool to support strategic planning and risk management.
While flood risk is evolving as one of the most imminent natural hazards and the shift from a reactive decision environment to a proactive one sets the basis of the latest thinking in flood management, the need to equip decision makers with necessary tools to think about and intelligently select options and strategies for flood management is becoming ever more pressing. Within this context, the Preparing for Extreme and Rare Events in Coastal Regions (PEARL) intelligent knowledge-base (PEARL KB) of resilience strategies is presented here as an environment that allows end-users to navigate from their observed problem to a selection of possible options and interventions worth considering within an intuitive visual web interface assisting advanced interactivity. Incorporation of real case studies within the PEARL KB enables the extraction of (evidence-based) lessons from all over the word, while the KB’s collection of methods and tools directly supports the optimal selection of suitable interventions. The Knowledge-Base also gives access to the PEARL KB Flood Resilience Index (FRI) tool, which is an online tool for resilience assessment at a city level available to authorities and citizens. We argue that the PEARL KB equips authorities with tangible and operational tools that can improve strategic and operational flood risk management by assessing and eventually increasing resilience, while building towards the strengthening of risk governance. The online tools that the PEARL KB gives access to were demonstrated and tested in the city of Rethymno, Greece.
2 August 2025 in International Journal of Disaster Risk Reduction
Cities at risk of extreme hydro-meteorological events need to be prepared to decrease the extent of the impacts. However, sometimes, authorities only react to catastrophes failing to proactively prepare against extremes. This can be a result of both absent structural protection measures and problematic governance. While for the first, models exist that can simulate the effect, the effect of the latter is difficult to quantify. This work aims to explore the effects that typical authorities’ behaviour has on the decisions for preparing and protecting a city against floods. This behaviour includes how the different authorities decide, for example, on whether or not to cooperate with each other, build something, assign funding to something, etc. These decisions affect directly the preparedness against and the protection from flood events. For that matter, the institutional analysis framework was used to conceptualise the decision-making processes of authorities responsible for flood risk management. Based on this, an agent-based modelling tool has been created, enabling the exploration of the system’s behaviour under different scenarios. The tool is used as a case study of the responsible authorities for flood protection in the city of Rethymno on the island of Crete, Greece. The tool has a user-friendly interface enabling the end-users to explore the drivers of decision-making processes under different conditions.