CONCLUSIONS AND RECOMMENDATIONS - Modelling Uncertainty in Flood Forecasting Systems - page 133

Chapter 7
CONCLUSIONS AND RECOMMENDATIONS
Summary of Chapter 7
This research has been devoted to providing a contribution to the
development of a framework and tools and techniques for uncertainty
modelling in flood forecasting systems, particularly using probability
and fuzzy set theories. It has also contributed to the exploration of
hybrid techniques for uncertainty modelling and probability-possibility
transformations. Principal conclusions drawn from this research and a
set of recommendations for future research and development in the
field of uncertainty modelling in flood forecasting and warning
systems are presented in this chapter. The first conclusion addresses
the issue of uncertainty in general in flood forecasting. The second
conclusion is about the theories and methods for uncertainty
modelling, which in particular highlights the analogies and differences
between the popular Monte Carlo method and the fuzzy Extension
Principle. The rest of the conclusions are specific to the methods and
methodologies developed and/or applied and explored in this research.
The recommendations emphasise on the need of uncertainty
assessment in flood forecasting and advice that the probabilistic and
possibilistic approaches should be viewed as complementary. The
implementation of risk-based flood warnings is recommended and
research needs for the hybrid techniques of uncertainty modelling and
for the consideration of uncertainty in data-driven models are pointed
out.
7.1 Conclusions
7.1.1 Uncertainty in flood forecasting systems
Flooding, like all natural disasters, is a complex and inherently uncertain phenomenon.
In flood forecasting using mathematical models, the sources of uncertainty have been
classified as (i) model uncertainty, (ii) input uncertainty, (iii) parameter uncertainty, and
(iv) natural and operational uncertainty. In spite of the increasing advancement in the
development of flood forecasting models and techniques, uncertainty in flood forecasts
remains unavoidable. It is therefore important that the existence of uncertainty be
admitted and properly appraised. Hiding uncertainty may create the illusion of certainty,
the consequences of which can be very large (Krzysztowicz, 200 1a). Various benefits of
estimating uncertainty in flood forecasting have been identified, which include the
rational basis for flood warning (risk-based warnings) and potential economic benefits