Random forests (RF) is a supervised machine learning algorithm, which has recently started
to gain prominence in water resources applications. However, existing applications are …

The recent dry and warm years in Europe are often assessed as extreme in terms of socio-
economic and environmental losses. However, the impact of a drought is a function of its …

To seek stochastic analogies in key processes related to the hydrological cycle, an extended
collection of several billions of data values from hundred thousands of worldwide stations is …

What elements should a parsimonious model reproduce at a single scale to precisely
simulate rainfall at many scales? We posit these elements are:(a) the probability of dry and …

Many studies have analyzed historical trends in annual peak flows in the United States
because of the importance of flooding to bridges and other structures, and the concern that …

Hydroclimatic processes come in all “shapes and sizes”. They are characterized by different
spatiotemporal correlation structures and probability distributions that can be continuous …

Predicting runoff, one of the fundamental operations in hydrology, is crucial for directing the
complete exploitation and use of local water resources. However, influenced by factors such …

Despite its far-reaching implications for conservation and natural resource management,
little is known about the color of environmental noise, or the structure of temporal …

Nature manifests itself in space and time. The spatiotemporal complexity of processes such
as precipitation, temperature, and wind, does not allow purely deterministic modeling …

Hydroclimatic time series analysis focuses on a few feature types (eg, autocorrelations,
trends, extremes), which describe a small portion of the entire information content of the …