This paper deals with the application of fuzzy logic in a relational database environment with the objective of capturing more meaning of the data. It is shown that with suitable interpretations for the fuzzy membership functions, a fuzzy relational data model can be used to represent ambiguities in data values as well as impreciseness in the association among them. Relational operators for fuzzy relations have been studied, and applicability of fuzzy logic in capturing integrity constraints has been investigated. By introducing a fuzzy resemblance measure EQUAL for comparing domain values, the definition of classical functional dependency has been generalized to fuzzy functional dependency (ffd). The implication problem of ffds has been examined and a set of sound and complete inference axioms has been proposed. Next, the problem of lossless join decomposition of fuzzy relations for a given set of fuzzy functional dependencies is investigated. It is proved that with a suitable restriction on EQUAL, the design theory of a classical relational database with functional dependencies can be extended to fuzzy relations satisfying fuzzy functional dependencies.

Integrated application of cluster analysis and Multicriterion Decision-Making (MCDM) is employed for the case study of the Flumen Monegros irrigation area in the Huesca province of Spain. Economic, environmental and social criteria are used to rank alternative strategies. Alternative strategies are formulated by mixing factors such as irrigation systems, water pricing, water allocation, crop distribution, fertiliser use and subsidies received. Cluster analysis is employed to reduce the large size payoff matrix to a manageable subset for further use of the MCDM technique. ELECTRE-3, an MCDM technique of outranking nature, is employed to rank the alternative strategies. The Kendall rank correlation coefficient is employed here to analyse the correlation between the ranking patterns obtained from various scenarios. Results indicate that three representative strategies are to be preferred based on this analysis.

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Global climate models (GCMs) are developed to simulate past climate and produce projections of climate in future. Their roles in ascertaining regional issues and possible solutions in water resources planning/management are appreciated across the world. However, there is substantial uncertainty in the future projections of GCM(s) for practical and regional implementation which has attracted criticism by the water resources planners. The present paper aims at reviewing the selection of GCMs and focusing on performance indicators, ranking of GCMs and ensembling of GCMs and covering different geographical regions. In addition, this paper also proposes future research directions.

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