A review of hybrid deep learning applications for streamflow forecasting

KW Ng, YF Huang, CH Koo, KL Chong, A El-Shafie… - Journal of …, 2023‏ - Elsevier
Deep learning has emerged as a powerful tool for streamflow forecasting and its
applications have garnered significant interest in the hydrological community. Despite the …

Effects of mass balance, energy balance, and storage-discharge constraints on LSTM for streamflow prediction

S Pokharel, T Roy, D Admiraal - Environmental modelling & software, 2023‏ - Elsevier
We investigate the effects of physics-based constraints, added to the loss function of a Long
Short-Term Memory (LSTM) network, on its performance in daily streamflow prediction …

[HTML][HTML] The 2021 heatwave results in simultaneous but different hydrological responses over Canada west of 100° W

PH Whitfield, H Abdelmoaty, S Nerantzaki… - Journal of …, 2024‏ - Elsevier
Abstract The 2021 Western North America heatwave resulted in record high air
temperatures over a large area of Canada west of 100°. The heatwave persisted from mid …

Linking explainable artificial intelligence and soil moisture dynamics in a machine learning streamflow model

A Ley, H Bormann, M Casper - Hydrology Research, 2024‏ - iwaponline.com
Machine learning algorithms are increasingly applied in hydrological studies with promising
results. However, these algorithms generally lack the ability for easy interpretability of the …

Modeling the streamflow response to heatwaves across glacierized basins in southwestern Canada

S Anderson, V Radić - Water Resources Research, 2023‏ - Wiley Online Library
In addition to having far‐reaching impacts on human health, agriculture, wildfires,
ecosystems, and infrastructure, heatwaves control streamflow through the melting of …

[HTML][HTML] A blueprint for coupling a hydrological model with fine-and coarse-scale atmospheric regional climate change models for probabilistic streamflow projections

CR Rajulapati, Z Tesemma, K Shook, SM Papalexiou… - Journal of …, 2024‏ - Elsevier
In cold regions, climate change, including warming and changes in snowmelt dynamics,
have profound impacts on streamflow patterns, often leading to flooding events …

[HTML][HTML] Associations between deep learning runoff predictions and hydrogeological conditions in Australia

SR Clark, JBD Jaffrés - Journal of Hydrology, 2025‏ - Elsevier
To capture the complexity of hydrological systems across regions, multidimensional domain
knowledge (eg climate, soils, geology and topography) can be incorporated into deep …

A hybrid SARIMA-Prophet model for predicting historical streamflow time-series of the Sobat River in South Sudan

MGS Kenyi, K Yamamoto - Discover Applied Sciences, 2024‏ - Springer
Accurate river streamflow forecasting is pivotal for effective water resource planning,
infrastructure design, utilization, optimization, and flood planning and warning. Streamflow …

Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

C Frank, M Rußwurm, J Fluixa-Sanmartin, D Tuia - Frontiers in Water, 2023‏ - frontiersin.org
The governing hydrological processes are expected to shift under climate change in the
alpine regions of Switzerland. This raises the need for more adaptive and accurate methods …

A Machine Learning-Based System for Predicting Peak Flowrates of Nebraska Streams

T Roy, S Pokharel, D Admiraal - 2023‏ - rosap.ntl.bts.gov
Accurate, early flood warnings are invaluable for ensuring transportation safety so that flood-
prone roads can be closed well before they become hazardous. A flood forecasting system …