E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||12|
|Section||Policy appraisal, investment planning and decision making tools|
|Published online||20 October 2016|
Toward generalized decision support systems for flood risk management
1 Research Engineer and Adjunct Professor, IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa 52242, USA
2 Postdoctoral Research Scholar, IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa 52242, USA
a Corresponding author: email@example.com
Despite the emergence of a large number of specialized decision-support systems (DSS) in the last decades, currently there are fewer efforts made for integrating the flood risk management relevant sciences with information and communication technologies into generalized DSS. Such systems are expected to formulate decision options for prevention, mitigation, preparation, response, and recovery from flood impacts with consideration of climate change, socio-economic evolution, and stakeholders’ input. Currently, there is no unified vision on the architecture, components, and the needed computer and communications technologies for attaining generic DSS for flood mitigation and resilience. Moreover, there is no guidance of what components should be developed first and in what order and how to efficiently include human-computer interfaces for efficient stakeholder engagement and consensus. This paper calls for the formation of a strategic global partnership for framing and subsequently assisting in the development of a generalized flood DSS (FLOODSS) that can overcome the current flood DSS limitations. The call is preceded by a review of the flood decision-support terminology and context. Subsequently, an initial vision on the FLOODSS is outlined and the steps for transitioning such a system from vision to practice are proposed.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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