The absence of a generic modeling framework in hydrology has long been recognized. With
our current practice of developing more and more complex models for specific individual …

River discharge predictions often show errors that degrade the quality of forecasts. Three
different methods of error correction are compared, namely, an autoregressive model with …

The existence of chaotic behaviour in the river stage and discharge time series observed at
the Sogutluhan hydrometric station, Turkey, is investigated. Five nonlinear dynamic methods …

This study introduces the concepts of complex networks, especially community structure, to
classify catchments in large-scale river basins. The Mississippi River basin (MRB) is …

During the last two decades or so, studies on the applications of the concepts of nonlinear
dynamics and chaos to hydrologic systems and processes have been on the rise. Earlier …

Technological advances, by facilitating extensive data collection, better data sharing,
formulation of sophisticated methods, and development of complex models, have brought …

This study presents a new approach for complex networks-based analysis of temporal
streamflow dynamics. The novelty comes in the form of using nonlinear dynamic concepts to …

Complexity–entropy causality plane (CECP) is a diagnostic diagram plotting normalized
Shannon entropy\cal H _S HS versus Jensen–Shannon complexity\cal C _ JS CJS that has …

Global climate change is one of the most serious issues we are facing today. While its exact
impacts on our water resources are hard to predict, there is a general consensus among …

We present a nonparametric approach based on local polynomial regression for ensemble
forecast of time series. The state space is first reconstructed by embedding the univariate …