It has been customary in the last few decades to employ stochastic models to represent
complex data sets encountered in geophysics, particularly in hydrology. This article reviews …

The end users of hydrological models may be justified for being tired of the excessive
uncertainty of these models, not to mention their simplistic approximations and crude …

A deterministic geometric approach, the fractal–multifractal (FM) method, already found
useful in modeling storm events, is adapted here in order to encode, for the first time, highly …

A deterministic geometric approach, the fractal-multifractal (FM) method, is proposed to
temporally downscale (disaggregate) rainfall and streamflow records. The applicability of the …

In this study, we attempt to offer a solid physical basis for the deterministic fractal–multifractal
(FM) approach in geophysics (Puente, Phys Let A 161: 441–447, 1992; J Hydrol 187: 65–80 …

With the advent of data acquisition techniques and data processing capabilities (computers+
algorithms), evolutionary computing (EC) has found its way into a wide range of applications …

A deterministic geometric procedure, yielding a multitude of interesting patterns as
projections of simple multifractal measures supported by the graphs of fractal interpolating …

Complex geometries often present in hydrologic data sets such as precipitation records
have been difficult to model in their totality using classical stochastic methods. In recent …

Hydrologic data sets such as precipitation records typically feature complex geometries that
are difficult to represent as a whole using classical stochastic methods. In recent years, we …

Usage of a deterministic fractal-multifractal (FM) procedure to model high-resolution rainfall
time series, as derived distributions of multifractal measures via fractal interpolating …