Meny
 

Flood Hazard Mapping: Uncertainty and its Value in the Decision-making Process

Computers are increasingly used in the simulation of natural phenomena such as floods. However, these simulations are based on numerical approximations of equations formalizing our conceptual understanding of flood flows. Les mer
Vår pris
2279,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Innbundet
Legg i
Innbundet
Legg i
Vår pris: 2279,-

(Innbundet) Fri frakt!
Leveringstid: Sendes innen 21 dager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

Computers are increasingly used in the simulation of natural phenomena such as floods. However, these simulations are based on numerical approximations of equations formalizing our conceptual understanding of flood flows. Thus, model results are intrinsically subject to uncertainty and the use of probabilistic approaches seems more appropriate. Uncertain, probabilistic floodplain maps are widely used in the scientific domain, but still not sufficiently exploited to support the development of flood mitigation strategies.
In this thesis the major sources of uncertainty in flood inundation models are analyzed, resulting in the generation of probabilistic floodplain maps. The utility of probabilistic model output is assessed using value of information and the prospect theory. The use of these maps to support decision making in terms of floodplain development under flood hazard threat is demonstrated.

Fakta

Innholdsfortegnelse

Chapter 1 Introduction


1.1 Background and Motivation
1.2 Research objectives
1.3 Methodology
1.4 Outline of the thesis


Chapter 2 A review of flood inundation modelling
2.1 Introduction
2.2 Flood modelling
2.3 Numerical modelling of floods
2.3.1 Governing flow equations
2.3.2 HEC-RAS and LISFLOOD-FP Models
2.3.3 Why LISFLOOD-FP?
2.4 Conclusions


Chapter 3 Case studies and data availability
3.1 Introduction
3.2 Case study areas
3.2.1 River Ubaye, Ubaye Valle (Barcelonnette)
3.2.2 River Po, Italy
3.3 Topographic data
3.3.1 Model geometry input
3.3.2 Topographic data sources
3.4 Parametric data
3.4.1 Model parameters
3.4.2 Inflow discharge
3.5 Conclusions


Chapter 4 Uncertainty in Flood Modelling
4.1 Introduction
4.2 Uncertainty analysis
4.2.1 Introduction
4.2.2 Methods
4.3 Inflow uncertainty
4.3.1 Rating curve uncertainty
4.3.2 Peak discharge uncertainty
4.4 Model structure
4.5 Communication of Model Uncertainty
4.5.1 Flood Mapping
4.5.2 Probabilistic flood mapping
4.6 Conclusions


Chapter 5 Flood hazard maps and damage
5.1 Introduction
5.2 Flood impact analysis, Ubaye Valley, Barcelonnette
5.2.1 Preliminary analysis
5.2.2 Regional Risk Assessment (RRA)
5.2.3 Economic - Regional Risk Assessment (E-RRA)
5.2.4 Flood damages
5.3 Uncertainty in flood damage assessment
5.4 Conclusion


Chapter 6 Usefulness of Probabilistic flood hazard maps
6.1 Introduction
6.2 Value Of Information (VOI)
6.2.1 Introduction
6.2.2 Application VOI to Ubaye valley (Barcelonnette)
6.3 Prospect Theory
6.3.1 Introduction
6.3.2 Making a decision
6.3.3 Prospect theory application to Ubaye valley (Barcelonnette)
6.3.4 Numerical example
6.3.5 Implementation of prospect theory for Ubaye valley case study
6.4 Conclusion


Chapter 7 Conclusions and recommendations
7.1 Introduction
7.2 Summary of results
7.2.1 Uncertainty in flood modelling: Chapter 2 - Chapter 4
7.2.2 Usefulness of uncertain information: Chapter 5 and Chapter 6
7.3 Limitations of the study
7.4 Conclusions
7.5 Recommendations

Om forfatteren

Micah M. Mukolwe is a trained civil engineer with interests in civil infrastructure design, implementation, project planning and management, and the effect (and mitigation) of natural hazards on floodplain receptors using hydroinformatics tools.