Historical development of rainfall‐runoff modeling
MC Peel, TA McMahon - Wiley Interdisciplinary Reviews: Water, 2020 - Wiley Online Library
Rainfall‐runoff models are used across academia and industry, and the number and type
have proliferated over time. In this primer we briefly introduce the key features of these …
have proliferated over time. In this primer we briefly introduce the key features of these …
Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction
An accurate model for sediment prediction is a priority for all hydrological researchers. Many
conventional methods have shown an inability to achieve an accurate prediction of …
conventional methods have shown an inability to achieve an accurate prediction of …
A rainfall‐runoff model with LSTM‐based sequence‐to‐sequence learning
Rainfall‐runoff modeling is a complex nonlinear time series problem. While there is still
room for improvement, researchers have been developing physical and machine learning …
room for improvement, researchers have been developing physical and machine learning …
[图书][B] Water resource systems planning and management: An introduction to methods, models, and applications
DP Loucks, E Van Beek - 2017 - books.google.com
This book is open access under a CC BY-NC 4.0 license. This revised, updated textbook
presents a systems approach to the planning, management, and operation of water …
presents a systems approach to the planning, management, and operation of water …
A method for predicting long-term municipal water demands under climate change
The accurate forecast of water demand is challenging for water utilities, specifically when
considering the implications of climate change. As such, this is the first study that focuses on …
considering the implications of climate change. As such, this is the first study that focuses on …
Forecasting water quality parameters using artificial neural network for irrigation purposes
This study was aimed at analyzing the water quality of Ele River Nnewi, Anambra State for
irrigation purposes with a view to predicting a one-year water quality index using Artificial …
irrigation purposes with a view to predicting a one-year water quality index using Artificial …
[图书][B] Machine learning for spatial environmental data: theory, applications, and software
M Kanevski, V Timonin, A Pozdnukhov - 2009 - taylorfrancis.com
This book discusses machine learning algorithms, such as artificial neural networks of
different architectures, statistical learning theory, and Support Vector Machines used for the …
different architectures, statistical learning theory, and Support Vector Machines used for the …
Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural network
Data-driven models have been widely developed and achieved impressive results in
streamflow prediction. However, the existing data-driven models mostly focus on the …
streamflow prediction. However, the existing data-driven models mostly focus on the …
A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events
CC Young, WC Liu, MC Wu - Applied Soft Computing, 2017 - Elsevier
Accurate rainfall-runoff modeling during typhoon events is an essential task for natural
disaster reduction. In this study, a novel hybrid model which integrates the outputs of …
disaster reduction. In this study, a novel hybrid model which integrates the outputs of …
Flood estimation at ungauged sites using artificial neural networks
Artificial neural networks (ANNs) have been applied within the field of hydrological
modelling for over a decade but relatively little attention has been paid to the use of these …
modelling for over a decade but relatively little attention has been paid to the use of these …