A multicriteria fuzzy pattern recognition approach for assessing the vulnerability to drought: Mediterranean region

The first objective of this paper is to explore a new integrated approach to estimate drought vulnerability taking into account the characteristics of a system that make it prone to be affected by an external hazard. The second objective is to investigate the link between fuzzy pattern recognition and distance based multi-criteria categorization oriented to the assessment of the vulnerability to drought. Firstly, relevant information is grouped into drought sensitivity and adaptive capacity criteria. Instead of the estimation of a unique score for the vulnerability, we propose a classification of the vulnerability to drought into several, in general, non ordered categories. Initially, only the ideal and the anti-ideal points are considered. The link with the multicriteria technique for order preference by similarity to ideal solution (TOPSIS) is investigated. Next, many non-ordered categories are considered which are modulated from all the combinations of the extreme points. Finally, the original fuzzy pattern recognition is considered where the centres are not selected a priori but based on the sample itself. A choice that strengthens the meta-multicriteria character of the proposed approaches is that the categories are not ordered, but they are modulated from all the combinations of the extreme points.

Automated summary

This paper aims to explore a new integrated approach to estimate drought vulnerability, considering system characteristics and fuzzy pattern recognition, categorizing vulnerability into multiple unordered categories. The study shows that by using different combination modulation, the multi-criteria nature of the method can be enhanced.