Advance in Flood Risk Management and Assessment Research
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 14375
Special Issue Editor
Interests: systems approach in geosciences; spatial reasoning; GIT applications in crisis management
Special Issue Information
Dear Colleagues,
As a result of ongoing climate change, among other things we can observe a gradual increase in both the frequency and (especially) the intensity of floods, which often threaten populated areas. Recent events in Germany, Belgium, France, the USA, and elsewhere, with significant damage and above all a large number of casualties, highlight the growing need to improve the effectiveness of flood-risk forecasting systems. They should be based on the latest research in this area. This research must be built on traditional numerical models and new approaches like signal processing, computational intelligence, and machine learning, all supported by increasingly available in situ and remote data acquisition tools. These forecasting systems will enable the development of services supporting effective flood risk management, starting with the design of preventive measures in the landscape, preparing emergency response plans, and early warnings of imminent threat, to the operational support of rescue services and returning to normal conditions.
The purpose of this Special Issue is to exchange knowledge in the field of flood and flood-risk modelling and assessment, the design of preventive measures to reduce flood risk in the threatened area, issuing warnings about the current threat of flooding, and the support of the liquidation of the consequences of the flood—all this supported by modern technologies collecting data on areas potentially at risk of floods, climate, and current weather conditions.
We encourage authors to share their knowledge, experience, and achievements regarding the impact of climate change and human activity on flood risk, the use of modern in situ and remote data acquisition tools, the accuracy of measurements, the interaction between floods and populated areas, the assessment of the impact of human activity on flood risk, the modelling of flood risk distribution in space and time using modern approaches like signal processing, computational intelligence and machine learning, and new methods for early warning.
Dr. Petr Rapant
Guest Editor
Manuscript Submission Information
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Keywords
- flood
- flash flood
- flood risk assessment
- flood risk forecasting
- flood risk management
- early warning
- remote sensing
- machine learning
- computational intelligence