Hydrological Modeling and Evaluation for Flood Risk Management
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 15827
Special Issue Editors
Interests: hydrodynamic modeling; flooding; climate change; European continental shelf; extreme events
Interests: urban hydrology; stormwater drainage system; climate change; mathematical modeling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Floods can be considered to be one of the most devastating natural hazards, with severe socioeconomic and environmental impacts on the affected areas. In the future, flood risk will increase as a consequence of several factors including population growth in flood-prone areas, decaying or poorly engineered flood control infrastructure, and climate change that leads to increases in sea level, rainfall, and storm winds. The dynamics of flooding can be very complex, particularly when a flood results from a particular combination of multiple process drivers. Understanding flood mechanisms and predicting extents of inundation and potential damage are important issues in flood risk management. Generation of flood inundation maps for a range of flood scenarios may help us to identify flood-prone areas and as such provide reliable information to the public about the flood risk. This can be achieved by using hydrological modeling methods that incorporate flood dynamics and include multiple drivers in an integrated manner. As such, hydrological modeling is complex and requires an optimal balance between initial/boundary inputs, computational effort, and model efficiency.
Technologies exist for producing and delivering flood assessments, such as LIDAR data and GIS for mapping topography, high-resolution bathymetry data, dense networks of observational data, and a range of modeling frameworks, yet these tools remain rarely integrated in assessment of flood extents. More recently, approaches of varying complexity based on computer models have been used to assess flood inundation and flood risks; they range from the most simplistic static approaches to quite complex dynamic hydraulic models.
This Special Issue welcomes multidisciplinary studies that aim to showcase innovation in numerical techniques for improved prediction of the dynamics and extent of flooding in a reliable and effective manner. In this context, researchers of various disciplines, including coastal and hydraulic engineering, hydrology, meteorology, remote sensing, geography, and geotechnics, are invited to explore advances in analysis of model prediction skill (e.g., uncertainty quantification, sensitivity analysis, data assimilation, machine learning, multi-scale modeling) and/or integration of multiple flood drivers into hydrological modeling.
Dr. Agnieszka Indiana Olbert
Dr. Bartosz Kaźmierczak
Guest Editors
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Keywords
- Hydrological/hydrodynamic modelling
- Coastal and/or fluvial flood mechanisms
- Compounds events
- Extreme event analysis and flood probability
- Model uncertainty, data assimilation, machine learning
- Remote sensing
- Multi-scale and high-resolution modelling
- Flood risk management
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