modeling monthly streamflow. The proposed method is compared with relevance vector machines tuned by particle swarm … of hydroclimatic data (e.g., precipitation, temperature, and streamflow) are used as inputs to the models. The relevance … streamflow prediction. It is found that the integrating metaheuristic algorithms into single relevance vector machine improves …

Scaling behaviors in monthly streamflow and Standardized Streamflow Index (SSI) of 11 gauging stations in Ebro basin … spectrum and the detrended fluctuation analysis (DFA) have shown similar results for all the streamflow and SSI time series …

proposed for intermittent streamflow forecasting and extreme event modelling. This study is carried out in a watershed in semi … intermittent streamflow forecasting even for the data outside the training range and for extreme events. Copyright Springer Science …

streamflow changes have occurred in this river since the introduction of dams. To address these concerns, it is necessary to …-Kendall method was used to assess the trends in hydro-climatic data. The streamflow data were divided into a reference period (1956 … Neural Network (BP-ANN) model was used to reconstruct natural streamflow. The contributions of climatic variations and human …