Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …

This paper traces two decades of neural network rainfall-runoff and streamflow modelling,
collectively termed 'river forecasting'. The field is now firmly established and the research …

Time series modeling is necessary for the planning and management of reservoirs. More
recently, the soft computing techniques have been used in hydrological modeling and …

Accurate hydrologic time-series prediction plays an important role in modern water resource
planning, water supply management, environmental protection, and power system …

Combinations of low-frequency components (also known as approximations) resulting from
the wavelet decomposition are tested as inputs to an artificial neural network (ANN) in a …

This paper investigates the skill of 90-day low-flow forecasts using two conceptual
hydrological models and one data-driven model based on Artificial Neural Networks (ANNs) …

Prediction of the sediment generated within a catchment basin is a crucial input in the
management and design of water resources projects. Due to the unavailability and …

Accurate and reliable flood water level prediction is very difficult to achieve as it is often
characterized as chaotic in nature. Prediction using conventional neural network techniques …

针对目前长期径流预报中物理成因考虑较少的问题, 以丹江口水库为例, 在分析影响径流物理
背景的基础上, 研究前期气象因子与水库秋汛期入库径流过程的相关关系, 识别影响径流的大气 …

Streamflow forecasting has an important role in water resource management (eg flood
control, drought management, reservoir design, etc.). In this paper, the application of …