Integrated metaheuristic algorithms with extreme learning machine models for river streamflow prediction
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-63908-w
Abstract: Accurate river streamflow prediction is pivotal for effective resource planning and flood risk management. Traditional river streamflow forecasting models encounter challenges such as nonlinearity, stochastic behavior, and convergence reliability. To overcome these, we introduce novel… read more here.
Keywords: extreme learning; metaheuristic algorithms; streamflow prediction; integrated metaheuristic ... See more keywords
Streamflow prediction using Long Short-Term Memory networks: a case study at the Kratie Hydrological Station, Mekong River Basin
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Hydroinformatics"
DOI: 10.2166/hydro.2025.276
Abstract: Accurate streamflow prediction is vital for hydropower operations, agricultural planning, and water resource management. This study assesses the effectiveness of Long Short-Term Memory (LSTM) networks in daily streamflow prediction at the Kratie station, investigate different… read more here.
Keywords: term memory; long short; prediction; streamflow prediction ... See more keywords
Enhancing streamflow prediction in the Wujiang River basin: a two-stage decomposition approach with deep learning integration
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Water and Climate Change"
DOI: 10.2166/wcc.2024.599
Abstract: Global climate change and human activities have profoundly impacted the geological and hydrological processes in watersheds, increasing the challenges in streamflow prediction. In this study, we propose a streamflow prediction model based on deep learning… read more here.
Keywords: deep learning; mode decomposition; wujiang river; prediction ... See more keywords
Utilizing Bivariate Climate Forecasts to Update the Probabilities of Ensemble Streamflow Prediction
Sign Up to like & getrecommendations! Published in 2020 at "Sustainability"
DOI: 10.3390/su12072905
Abstract: In order to enhance the streamflow forecast skill, seasonal/sub-seasonal streamflow forecasts can be post-processed by incorporating new information, such as climate signals. This study proposed a simple yet efficient approach, the “Bivar_update” model that utilizes… read more here.
Keywords: streamflow prediction; climate; model; ensemble streamflow ... See more keywords
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Sign Up to like & getrecommendations! Published in 2024 at "Hydrology and Earth System Sciences"
DOI: 10.5194/hess-28-2107-2024
Abstract: Abstract. Deep learning (DL) algorithms have previously demonstrated their effectiveness in streamflow prediction. However, in hydrological time series modelling, the performance of existing DL methods is often bound by limited spatial information, as these data-driven… read more here.
Keywords: long short; lstm; model; lumped lstm ... See more keywords