nland Flood Mitigation Model

Mitigation Model for
Inland Flood Disaster
AMR DAGHISTANI
03/10/2020
1
First Paper Outlines
• Introduction
• Problem statement
• Literature review
• Objectives
• Proposed methodology
• Collect the data
• Do the analysis
• Conclusions and recommendations
2
First Paper Outlines
• Introduction
• Natural Disaster Worldwide
• Inland Flood in the USA
• Washington (AR) as a case study
• Hazus-MH
• Thesis statement (uncertainty)
3
First Paper Outlines
• Problem statement
• Uncertainties are inherent in any loss estimation methodology
• The Flood Model performs its analysis at the census block level
with small numbers of buildings. Damage analysis of these small
numbers makes the Flood Model more sensitive to rounding
errors.
• In the uncertainty analysis in flood damage assessment two
types of uncertainty are distinguished: aleatory and epistemic
uncertainty (Merz and Thieken, 2009).
4
First Paper Outlines
• Problem statement
• Aleatory uncertainty is related to the variability or
heterogeneity within a population which can be expressed
by statistic parameters such as the mean, variance and
skewness.
• Epistemic uncertainty is the lack of understanding of a
system and can in theory be reduced by further study or by
collecting more or better data.
5
Literature review
• Literature review for the last five years
Systematic Literature Review (SLR) guideline.
1. Scoping study: The scoping study involved the identification of the
natural disaster keywords.
2. Identification of search strategy: The research will focus on the
preparedness models for inland flood disaster only.
3. Application of extension criteria: Titles and abstracts will be
reviewed in accordance with the identified search strategy after
removing duplicates.
6
Literature review
• Literature review for the last five years
Systematic Literature Review (SLR) guideline.
4. Data extraction: This step will extract the important information for
further study.
5. Analysis of data: The extracted data will be analyzed to categorize the
research area of the inland flood preparedness models.
6. Dissemination of information: The analysis will highlight the distribution
of information that has interest in the inland flood preparedness
research field.
7
Objectives
• Reduce the uncertainty for the number of the displaced
people by using five flood year plains ( 10,25,50,100, and
500).
• Find the optimal buffer value to maximize the number of
displaced people.
• Maximize the number of the save people.
8
Proposed methodology
• Finding the distribution of different flood plains
• Finding the matching distribution for different buffer values.
• Optimize the number of displaced people to be equivalent to
80% of the total population at the hazard zones (Pareto
analysis).
9
Collect the data
• Get the data from Hazus-MH for five different flood plains
with a buffer value increased uniformity from 0 to 50.
10
Do the analysis
• Using MATLAB and Minitab to perform the analysis
11
Conclusions and recommendations
• Writing the conclusions and recommendations