scholarly journals Building an Intelligent Hydroinformatics Integration Platform for Regional Flood Inundation Warning Systems

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 9 ◽  
Author(s):  
Li-Chiu Chang ◽  
Fi-John Chang ◽  
Shun-Nien Yang ◽  
I-Feng Kao ◽  
Ying-Yu Ku ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Management ◽  
Flood Risk ◽  
Modular Design ◽  
Data Access ◽  
Flood Risk Management ◽  
Flood Inundation ◽  
Warning Systems ◽  
Integration Platform ◽  
Flood Disasters

Flood disasters have had a great impact on city development. Early flood warning systems (EFWS) are promising countermeasures against flood hazards and losses. Machine learning (ML) is the kernel for building a satisfactory EFWS. This paper first summarizes the ML methods proposed in this special issue for flood forecasts and their significant advantages. Then, it develops an intelligent hydroinformatics integration platform (IHIP) to derive a user-friendly web interface system through the state-of-the-art machine learning, visualization and system developing techniques for improving online forecast capability and flood risk management. The holistic framework of the IHIP includes five layers (data access, data integration, servicer, functional subsystem, and end-user application) and one database for effectively dealing with flood disasters. The IHIP provides real-time flood-related data, such as rainfall and multi-step-ahead regional flood inundation maps. The interface of Google Maps fused into the IHIP significantly removes the obstacles for users to access this system, helps communities in making better-informed decisions about the occurrence of floods, and alerts communities in advance. The IHIP has been implemented in the Tainan City of Taiwan as the study case. The modular design and adaptive structure of the IHIP could be applied with similar efforts to other cities of interest for assisting the authorities in flood risk management.

scholarly journals Flood Risk Management Methodology for Lakes and Adjacent Areas: The Lake Pamvotida Paradigm

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
George Papaioannou ◽  
Athanasios Loukas ◽  
Lampros Vasiliades
Keyword(s):  
Risk Management ◽  
Natural Hazards ◽  
Flood Risk ◽  
Urban Areas ◽  
Hydrologic Modeling ◽  
Flood Risk Management ◽  
Flood Inundation ◽  
Hydrodynamic Simulations ◽  
Flood Inundation Modeling ◽  
Inundation Modeling

In recent decades, natural hazards have caused major disasters in natural and man-made environments. Floods are one of the most devasting natural hazards, with high levels of mortality, destruction of infrastructure, and large financial losses. This study presents a methodological approach for flood risk management at lakes and adjacent areas that is based on the implementation of the EU Floods Directive (2007/60/EC) in Greece. Contemporary engineering approaches have been used for the estimation of the inflow hydrographs. The hydraulic–hydrodynamic simulations were implemented in the following order: (a) hydrologic modeling of lake tributaries and estimation flood flow inflow to the lake, (b) flood inundation modeling of lake tributaries, (c) simulation of the lake as a closed system, (d) simulation of the lake outflows to the adjacent areas, and (e) simulation of flood inundation of rural and urban areas adjacent to the lake. The hydrologic modeling was performed using the HEC-HMS model, and the hydraulic-hydrodynamic simulations were implemented with the use of the two-dimensional HEC-RAS model. The simulations were applied to three soil moisture conditions (dry, medium and wet) and three return periods (T = 50, T = 100 and T = 1000 years) and a methodology was followed for the flood inundation modeling in urban areas. Upper and lower estimates on water depths, flow velocities and inundation areas are estimated for all inflow hydrographs and for varying roughness coefficient values. The proposed methodology presents the necessary steps and the results for the assessment of flood risk management and mapping for lake and adjacent urban and rural areas. The methodology was applied to Lake Pamvotida in Epirus, Greece, Ioannina.

Early Warning for Pre and Post Flood Risk Management by Using IoT and Machine Learning

2021 ◽  
Author(s):  
S. P. M. K. W. Ilukkumbure ◽  
V. Y. Samarasiri ◽  
M. F. Mohamed ◽  
V. Selvaratnam ◽  
U. U. Samantha Rajapaksha
Keyword(s):  
Machine Learning ◽  
Risk Management ◽  
Early Warning ◽  
Flood Risk ◽  
Flood Risk Management

scholarly journals Does Flooding Define the Aquapelago? Constructing Venice’s flood disaster risk personality

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Ilan Kelman
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Flood Risk ◽  
Flood Management ◽  
Disaster Risk ◽  
Flood Risk Management ◽  
Flood Disaster ◽  
Flood Disasters ◽  
The Impact

Part of Venice’s character and appeal is sometimes constructed and construed as being not just about water, but also about the role which flood management plays, especially avoiding floods. A ‘disaster risk personality’ is created regarding water-land interaction, based mainly on avoiding inundation. This paper explores the construction of this approach for Venice’s flood disaster risk personality through a conceptual examination of Venice as an aquapelago to understand water-land links and separations. With this baseline, three decision-making lessons for Venice’s flood disaster risk personality are detailed: (i) the dynamicity of the water-land interface and hence the aquapelago, (ii) the impact of structural approaches on disaster risk personality, and (iii) the implications of submergence. While non-structural approaches to flood risk management tend to have the best long-term successes in averting flood disasters, Venice has chosen the opposite approach of constructing a large barrier, substantively changing its disaster risk personality. This choice is not inherently positive or negative, with the desirability and usefulness being subjective and based on the (flood) disaster risk personality sought for the locale.

Virtually Expert: Modes of Environmental Computer Simulation Modeling

2014 ◽  
Vol 27 (4) ◽  
pp. 579-603 ◽  
Author(s):  
Catharina Landström ◽  
Sarah J. Whatmore
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Simulation Modeling ◽  
Local Communities ◽  
Flood Risk Management ◽  
Flood Inundation ◽  
Research Projects ◽  
Virtual Engineering ◽  
Software Packages ◽  
Institutional Order

ArgumentThis paper challenges three assumptions common in the literature on expertise: that expertise is linearly derived from scientific knowledge; that experts always align with the established institutional order; and that expertise is a property acquired by individuals. We criticize these ideas by juxtaposing three distinct expert practices involved with flood risk management in England. Virtual engineering is associated with commercial consultancy and relies on standardized software packages to assess local flood inundation. Mathematical experimentation refers to academic scientists creating new digital renderings of the physical dynamics of flooding. Participatory modeling denotes research projects that aim to transform the relationships between experts and local communities. Focusing on different modes of modeling we contribute an analysis of how particular models articulate with specific politics of knowledge as experts form relationships with flood risk management actors. Our empirical study also shows how models can contribute to re-distribution of expertise in local flood risk management.

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