Training decision-makers in flood response with system dynamics.
Purpose ‚ The purpose of this paper is to present a training model for decision makers that covers the complexity which is inherent in decision-making processes in times of floods. Design/methodology/approach ‚ Through literature review, case study analysis and iterative interviews with decision-makers, the model was established. It enables one to simulate different scenarios depending on selected influencing factors and was implemented with Stella 9.1. Findings ‚ Flood events are highly complex and their development process is significantly influenced by various conditions. The findings show that the most important factor is the water level which determines the time available to respond. The presented System Dynamics (SD) model has the capability to capture such complex settings. Through what-if analysis and the comparison of different scenarios, learning effects are achieved by using the model. Research limitations/implications ‚ The level of abstraction is high. Not all influencing variables can be incorporated due to the variety of flood events. Based on experts‚¬„ recommendations, the most relevant factors were included as areas of focus in the model. Practical implications ‚ The generated model is presented to facilitate holistic comprehension of the modelling process. It offers the possibility to start learning processes through scenario analyses in order to strengthen decision-makers‚¬„ understanding of complexity. Originality/value ‚To the best of our knowledge, there are no comparable studies that focus on the generation process of building an SD-model for educational purposes in flood response. [ABSTRACT FROM AUTHOR]/nCopyright of Disaster Prevention & Management is the property of Emerald Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
A sensitivity analysis was performed by changing the initial number relief units that are available for conducting response activities.
literature review, case study analysis and iterative interviews
Through literature review, case study analysis and iterative interviews with decision-makers, the model was established. It enables one to simulate different scenarios depending on selected influencing factors and was implemented with Stella 9.1. The presented model simulates the development of a major flood by providing decisionmakers the possibility of undertaking two different types of measures: installing mobile flood protection and evacuating people.
case study for the Upper Danube region
The level of abstraction is high. Not all influencing variables can be incorporated due to the variety of flood events. The model is not aimed to be applied during the response phase, but is aimed to enrich training programmes by application during the prevention phase. As crisis managers may not directly use the output data for real-world relief operations, it is important to minimise negative impacts by responding quickly and efficiently as well as by being well-prepared.
Flood events are highly complex and their development process is significantly influenced by various conditions. The findings show that the most important factor is the water level which determines the time available to respond. The presented System Dynamics (SD) model has the capability to capture such complex settings. Through what-if analysis and the comparison of different scenarios, learning effects are achieved by using the model.
The purpose of this paper is to present a training model for decision makers that covers the complexity which is inherent in decision-making processes in times of floods
Serwis internetowy Portfolio of Solutions został początkowo opracowany w ramach projektu DRIVER+. Obecnie serwis jest zarządzany przez AIT Austrian Institute of Technology GmbH, na rzecz Europejskiego Zarządzania Kryzysowego. PoS jest popierany i wspierany przez Disaster Competence Network Austria (DCNA), jak również przez projekty STAMINA i TeamAware H2020. |