Edjossan-Sossou, A., Selouane, K., Sayah, M. A., Ouabou, M., Vignote, C., Capitaine, M., et al. (2023). An innovative scenario-based modeling tool for the management of resilient water resources. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 808–821). Omaha, USA: University of Nebraska at Omaha.
Abstract: As freshwater availability for domestic and agro-industrial uses is highly sensitive to climate change, there is an urgent need for the management of this critical resource to be resilient, i.e., to cope with and rapidly recover from climate risks. To achieve this resilient goal, decision-makers need to have a comprehensive understanding of (i) the current and future local water resources, (ii) the ways these resources are and will be impacted by climate change, and (iii) the effects their management decisions can have. In this paper, we present an innovative scenario based modeling tool that help decision-makers make the most appropriate decision towards managing water resources: the Resilience Performance Assessment (RPA). This GIS-based decision support tool illustrates the current and future effects of climate change on local water resources and simulates the outcomes of different water resources management strategies. The RPA helps guide decision-makers towards the implementation of context specific adaptation strategies.
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Stella Polikarpus, Tobias Ley, & Katrin Poom-Valickis. (2021). Collaborative Authoring of Virtual Simulation Scenarios for Assessing Situational Awareness. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 229–237). Blacksburg, VA (USA): Virginia Tech.
Abstract: Situational awareness (SA), the ability to perceive, comprehend and predict situation around you and it is a key in attending any incident as critical foundation for successful decision-making. Because incidents are solitary events, development and assessment of SA presents a significant challenge. In this article we analyze the authoring process of twenty-two scenarios implemented in the XVR on-scene virtual simulation software used to assess rescue incident commanders' (ICs) SA. To allow the scenarios to be used by different assessors, the Collaborative Authoring Process Model for Virtual Simulation Scenarios (CAPM) was developed. In Estonia, 473 assessments were recorded in Effective Command database and analysed by all three levels of SA as recommended by Endsley (2000). Introduction of CAPM resulted in scenarios being re-used by different assessors for authentic SA measuring. In the last sections of this article, we introduce our suggestions to improve virtual scenario design and SA research.
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Victor A. Bañuls, Andrzej M. Skulimowski, & José Antonio Román Begines. (2021). Disaster Resilience Modeling of Municipal Water Supply Infrastructures in the Context of Atmospheric Threats. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 198–207). Blacksburg, VA (USA): Virginia Tech.
Abstract: The resilience of water supply infrastructure (WSI) is of utmost importance as threats to predominantly, although not exclusively, urban WSI may accompany virtually all kinds of natural disasters. In this paper, we present some of the challenges posed by climate change in modeling emergencies in WSIs. Climate change is a global phenomenon that significantly impacts global lifestyle. It is expected that increase in global temperatures causes sea levels to rise, increases the number of extreme weather events such as floods, droughts, and storms while highly impacting WSI. In this respect, the challenge is to be prepared for the unexpended by modeling various complex scenarios. Only with a multidisciplinary approach at the global, regional, national, and local levels, can success be achieved. We discuss some of the specific challenges posed by climate change in modeling emergencies in WSIs with a case study modeled using EMERTIC. EMERTIC is a software based on AI and scenarios, that is aimed at supporting decision making at different stages of the Emergency Management cycle.
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Xiaoyong Ni, Hong Huang, Wenxuan Dong, Chao Chen, Boni Su, & Anying Chen. (2021). Scenario Prediction and Crisis Management for Rain-induced Waterlogging Based on High-precision Simulation. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 159–173). Blacksburg, VA (USA): Virginia Tech.
Abstract: Many cities, especially those in developing countries, are not well prepared for the devastating disaster of exceptional rain-induced waterlogging caused by extreme rainfall. This paper proposes a waterlogging scenario prediction and crisis management method for such kind of extreme rainfall conditions based on high-precision waterlogging simulation. A typical urban region in Beijing, China is selected as the study area in this paper. High-precision and full-scale data in the study area requested for the waterlogging simulation are introduced. The simulation results show that the study area is still vulnerable to extreme rainfall and the subsequent waterlogging. The waterlogging situation is much more severe with the increase of the return period of rainfall. This study offers a good reference for the relevant government departments to make effective policy and take pointed response to the waterlogging problem.
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Dashley Rouwendal van Schijndel, Audun Stolpe, & Jo Erskine Hannay. (2021). Toward an AI-based external scenario event controller for crisis response simulations. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 106–117). Blacksburg, VA (USA): Virginia Tech.
Abstract: There is a need for tool support for structured planning, execution and analysis of simulation-based training for crisisresponse and management. As a central component of an architecture for such tool support, we outline the design ofan AI-based scenario event controller. The event controller is a component that uses machine reasoning to computethe next state in a scenario, given the actions performed in the corresponding simulation (execution of the scenario).Scenarios are specified in Answer Set Programming, which is a logic programming language we use for automatedplanning of training scenarios. A plan encoding in ASP adds expressivity in scenario specification and enablesmachine reasoning. For exercise managers this gives AI-based tool support for before-action and during-actionreviews to optimize learning. In line with Modelling and Simulation as as Service, our approach externalizes eventcontrol from any particular simulation platform. The scenario, and its unfolding in terms of events, is externalizedas a service. This increases interoperability and enables scenarios to be designed and modified readily and rapidlyto adapt to new training requirements.
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