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weakness of this qualitative method is that it can be very approximate and rather holistic.
Another drawback of this approach observed in the present example is that the
evaluations by different experts may differ noticeably. The results would become more
credible if the experts' evaluation could be checked against either measurement or results
from other methods. Besides providing such a check, the joint application of the
quantitative and qualitative methods can also provide additional information regarding
uncertainty.
6.5 Conclusions and discussion
This chapter presented the application of the FOSM, IFOSM and fuzzy set theory and
expert judgement-based qualitative method for the assessment of uncertainty in the
forecasts from Loire River flood forecasting model. Conclusions specific to each of the
methods are presented at the end of each section describing the application of the
methods. The conclusions presented here concern mainly the comparative advantages
and limitations of these methods.
The popular FOSM method proved very useful and worked well in most flow
conditions for the estimation of uncertainty in the forecasts from the Loire River model.
It failed however in some specific flow conditions, where the IFOSM method has been
used successfully. Selection of the appropriate size of the perturbation ratio is an
important issue in the application of both the FOSM and IFOSM methods. In flood
forecasting problems it is advisable to fix beforehand a nominal size of the perturbation
ratio with the aid of a MC-type method for different flow conditions.
The main advantage of the expert judgement-based qualitative method is the
possibility of including all sources of uncertainty without much computational burden.
But the results are only qualitative and rather approximate. Assessments by experts are
also difficult to obtain. In flood forecasting problems, the quantitative methods, such as
MC, FOSM and fuzzy EP should be preferred where practicable. Results of the
qualitative methods can however be used as an additional information.
 
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