ABSTRACT
This chapter focuses on the application of such a notion in the context of geosciences research, especially in hydrology. The evaluation of the resulting Fractal-Multifractal (FM) models is made using various statistics not included in the objective function. For this purpose, various statistical attributes, such as autocorrelation, histogram, and Renyi entropy functions, are evaluated in terms of Nash-Sutcliffe efficiencies. The present downscaling technique may supplement others based on stochastic methods and may clearly be used to disaggregate outputs from global circulation models (GCMs) in order to assess climate change impacts. The chapter encapsulates the application of the deterministic fractal-multifractal FM approach to the encoding, simulation, disaggregation/downscaling, classification, and prediction of geoscience records. Clearly, the scope of the FM approach is not limited to the study of geoscience records only, as, in a rather natural way, it may also be used to enhance other disciplines, such as physics, engineering, pattern recognition, general statistics, medical sciences and finance.
