Forecasting a time series became one of the most challenging tasks to variety of data sets. The existence of large number of parameters to be estimated and the effect of uncertainty and outliers in the measurements makes the time series modeling too complicated. Recently, Artificial Neural Network (ANN) became quite successful tool to handle time series modeling problem. This paper provides a s...

Successful river flow time series forecasting is a primary goal and an essential procedure required in the planning and water resources management. River flow data are important for engineers to design, build and operate various water projects and development. The monthly river flow data taken from Department of Irrigation and Drainage, Malaysia are used in this study. This study aims to develo...

“Hydromax” is the river flow forecasting system for the early warning of extreme hydrological events (floods as well as low waters) in the Meuse river basin and its tributaries. Hydromax provides in real-time short-term predictions of river flows based on past rainfall and river flow measurements, and long-term flood forecasting based on meteorological forecasts. It is now successfully in routi...

watershed outflow has influenced by different factors such as climatic, human and physical aspects and this variability of effective factors can cause complex conditions, difficulty of flow forecasting and it mainly originates by different local and temporal scales of these factors. also, some remote meteorological signals can cause changes in meteorological conditions in different regions. hab...

analyses and investigations on river flow behavior are major issues in design, operation and studies related to water engineering. thus, recently the application of chaos theory and new techniques, such as chaos theory, has been considered in hydrology and water resources due to relevant innovations and ability. this paper compares the performance of chaos theory with anfis model and discusses ...

Each winter and early spring, the Northeast River Forecast Center (NERFC) faces the challenge of forecasting river stage and flow for ice affected rivers. “Stage versus flow” relationships tend to be in error and there is a lack of real-time information about the nature of the ice cover. The NERFC is investigating methods to forecast river stage and flow for ice-affected rivers because in times...

The merits of the modelling philosophy of Box & Jenkins (1970) are illustrated with a summary of our recent work on seasonal river flow forecasting. Specifically, this work demonstrates that the principle of parsi-mony, which has been questioned by several authors recently, is helpful in selecting the best model for forecasting seasonal river flow. Our work also demonstrates the importance of m...

Analyses and investigations on river flow behavior are major issues in design, operation and studies related to water engineering. Thus, recently the application of chaos theory and new techniques, such as chaos theory, has been considered in hydrology and water resources due to relevant innovations and ability. This paper compares the performance of chaos theory with Anfis model and discusses ...

This paper discusses the modelling of rainfall-flow (rainfall-run-off) and flow-routeing processes in river systems within the context of real-time flood forecasting. It is argued that deterministic, reductionist (or 'bottom-up') models are inappropriate for real-time forecasting because of the inherent uncertainty that characterizes river-catchment dynamics and the problems of model over-param...