4.2.5.2. Household `s perception
of communities role in flood management
A part from the role of government and NGOs in flood management,
the interviewed households recognized the role of communities in managing flood
disasters. 33.94% reported they should adopt early harvest option in order to
reduce impact of flood on their livelihood; 22.63% said the importance of
planting trees in reducing flood extent, while 13.57% reported they should
install collective food storage in order to assist affected
people with food items. Others suggested diversification of economic activities
(11.31%), group farming (7.24%); building of strong house (3.16%), avoiding
cultivation close to the river (2.26%), flood management committee (2.26%),
collective saving (3.62%).
To sum up, besides the extreme variability in terms of flood
magnitude and frequency in the Mono River in the study area, which may be due
to the increasing in the precipitation and the river discharge patterns, the
proximity of the villages and the closeness of households' farmlands to the
river body, the type of construction and the position of settlements, the
structure of the populations (high number of children; high household size),
low level education of household, the lack of the diversification of livelihood
strategies, the lack of adequate flood warning system and lack of willingness
and ability to take responsive actions coupled with inadequate emergency
services during and after flood, may increase the communities' vulnerability to
flood disasters.
The low level education coupled with the limited livelihood
strategies and the low incomes have resulted in poor agricultural practices. In
addition, since the crop production is the main source of income and food added
to the high number household member, increased exposure to floods will
exacerbate the population vulnerabilities to flood hazards by compromising
their food security. This situation proves that the research hypothesis is
verified.
4.3 Computation of Flood
Vulnerability Index
The Flood Vulnerability Index (FVI), in the present study,
aimed to identify the most vulnerable village related to flood events in the
three selected counties in the downstream area of the Mono River basin in the
Yoto district.
4.3.1 Identifying key indicators of developed FVI
Thirty (30) indicators were used in the present study. Those
indicators were categorised under the three factors of vulnerability and were
included in the FVI computation.
4.3.2. Normalised Scores and Weight Values of Indicators
A system at risk is more vulnerable when it is more exposed to a
hazard. However, it will be less vulnerable the more resilient it is. From the
vulnerability equation, high exposure and high susceptibility lead to
increases in vulnerability. On the other hand, high resilience levels
decreases vulnerability. To this end, the normalization method takes into
account the functional relationship between the variable and vulnerability in
order to avoid misleading issue in the construction of the indices. The
normalised values of each indicator is given in annexe (6). Iyengar and
Sudarshan (1982) method were used to calculate weight of each indicator. The
calculated weights for each of the flood vulnerability indicators are given in
"annexe "7.
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