Using fuzzy set theory to address the uncertainty of susceptibility to drought |
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Authors: | Frank Eierdanz Joseph Alcamo Lilibeth Acosta-Michlik Dörthe Krömker Dennis Tänzler |
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Affiliation: | 1.Faculty of Psychology,University of Kassel,Kassel,Germany;2.Center for Environmental Systems Research at the University of Kassel,Kassel,Germany;3.Département de Géologie et de Géographie,Université Catholique de Louvain,Louvain,Belgium;4.Adelphi Research,Berlin,Germany |
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Abstract: | This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The
methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model
input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population
or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership
functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4)
defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy
membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment
of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the
subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology
are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility,
in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the
inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through
the procedures of ‘fuzzification’ and ‘defuzzification’. |
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Keywords: | Susceptibility to drought Vulnerability to climate extremes Fuzzy set applications Climate change impacts |
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