A comprehensive review of deep learning applications in hydrology and water resources
The global volume of digital data is expected to reach 175 zettabytes by 2025. The volume,
variety and velocity of water-related data are increasing due to large-scale sensor networks …
variety and velocity of water-related data are increasing due to large-scale sensor networks …
Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
[HTML][HTML] Improving streamflow prediction in the WRF-Hydro model with LSTM networks
Researchers have attempted to use machine learning algorithms to replace physically
based models for streamflow prediction. Although existing studies have contributed to …
based models for streamflow prediction. Although existing studies have contributed to …
An ensemble CNN-LSTM and GRU adaptive weighting model based improved sparrow search algorithm for predicting runoff using historical meteorological and …
Z Yao, Z Wang, D Wang, J Wu, L Chen - Journal of Hydrology, 2023 - Elsevier
Accurate prediction of river runoff is of great significance for water resources management,
flood prevention and mitigation. The causes of runoff are complex and the mechanisms …
flood prevention and mitigation. The causes of runoff are complex and the mechanisms …
Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model
Water quality monitoring is an important component of water resources management. In
order to predict two water quality variables, namely dissolved oxygen (DO; mg/L) and …
order to predict two water quality variables, namely dissolved oxygen (DO; mg/L) and …
A novel hybrid of meta-optimization approach for flash flood-susceptibility assessment in a monsoon-dominated watershed, Eastern India
The exponential growth in the number of flash flood events is a global threat, and detecting a
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
flood-prone area has also become a top priority. The flash flood-susceptibility mapping can …
Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as …
Monthly streamflow prediction is very important for many hydrological applications in
providing information for optimal use of water resources. In this study, the prediction …
providing information for optimal use of water resources. In this study, the prediction …
Runoff forecasting using convolutional neural networks and optimized bi-directional long short-term memory
J Wu, Z Wang, Y Hu, S Tao, J Dong - Water Resources Management, 2023 - Springer
Water resources matters considerably in maintaining the biological survival and sustainable
socio-economic development of a region. Affected by a combination of factors such as …
socio-economic development of a region. Affected by a combination of factors such as …
[HTML][HTML] Water temperature prediction using improved deep learning methods through reptile search algorithm and weighted mean of vectors optimizer
Precise estimation of water temperature plays a key role in environmental impact
assessment, aquatic ecosystems' management and water resources planning and …
assessment, aquatic ecosystems' management and water resources planning and …
A hybrid deep learning algorithm and its application to streamflow prediction
Process-based streamflow prediction is subjected to large uncertainties in model
parameters and parameterizations related to the complex processes involved in streamflow …
parameters and parameterizations related to the complex processes involved in streamflow …