Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years

M Troin, R Arsenault, AW Wood, F Brissette, JL Martel - 2021 - Wiley Online Library
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 …

Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting

RJ Abrahart, F Anctil, P Coulibaly… - Progress in …, 2012 - journals.sagepub.com
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 …

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

AK Lohani, R Kumar, RD Singh - Journal of Hydrology, 2012 - Elsevier
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 …

Forecasting daily runoff by extreme learning machine based on quantum-behaved particle swarm optimization

W Niu, Z Feng, C Cheng, J Zhou - Journal of Hydrologic …, 2018 - ascelibrary.org
Accurate hydrologic time-series prediction plays an important role in modern water resource
planning, water supply management, environmental protection, and power system …

Monthly streamflow forecasting using neuro-wavelet techniques and input analysis

AGSM Honorato, GBL Silva… - Hydrological Sciences …, 2018 - Taylor & Francis
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 …

The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models

MC Demirel, MJ Booij… - Hydrology and earth …, 2015 - hess.copernicus.org
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) …

丹江口水库秋汛期长期径流预报

刘勇, 王银堂, 陈元芳, 王宗志, 胡健, 冯小冲 - 水科学进展, 2010 - skxjz.nhri.cn
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 …

Modeling suspended sediment using artificial neural networks and TRMM-3B42 version 7 rainfall dataset

D Kumar, A Pandey, N Sharma… - Journal of Hydrologic …, 2015 - ascelibrary.org
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 …

Flood prediction using NARX neural network and EKF prediction technique: A comparative study

FA Ruslan, ZM Zain, R Adnan - 2013 IEEE 3rd International …, 2013 - ieeexplore.ieee.org
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 …

[PDF][PDF] Long-term Streamflow Forecasting by Adaptive Neuro-Fuzzy Inference System Using K-fold Cross-validation:(Case Study: Taleghan Basin, Iran)

R Esmaeelzadeh, A Borhani Dariane - Journal of Water Sciences …, 2014 - jwsr.stb.iau.ir
Streamflow forecasting has an important role in water resource management (eg flood
control, drought management, reservoir design, etc.). In this paper, the application of …