Daily Streamflow Forecasting Using Networks of Real-Time Monitoring Stations and Hybrid Machine Learning Methods

Water, Год журнала: 2024, Номер 16(9), С. 1284 - 1284

Опубликована: Апрель 30, 2024

Considering the increased risk of urban flooding and drought due to global climate change rapid urbanization, imperative for more accurate methods streamflow forecasting has intensified. This study introduces a pioneering approach leveraging available network real-time monitoring stations advanced machine learning algorithms that can accurately simulate spatial–temporal problems. The Spatio-Temporal Attention Gated Recurrent Unit (STA-GRU) model is renowned its computational efficacy in events with forecast horizon 7 days. novel integration groundwater level, precipitation, river discharge as predictive variables offers holistic view hydrological cycle, enhancing model’s accuracy. Our findings reveal 7-day period, STA-GRU demonstrates superior performance, notable improvement mean absolute percentage error (MAPE) values R-square (R2) alongside reductions root squared (RMSE) (MAE) metrics, underscoring generalizability reliability. Comparative analysis seven conventional deep models, including Long Short-Term Memory (LSTM), Convolutional Neural Network LSTM (CNNLSTM), (ConvLSTM), (STA-LSTM), (GRU), GRU (CNNGRU), STA-GRU, confirms power STA-LSTM models when faced long-term prediction. research marks significant shift towards an integrated deep-learning forecasting, emphasizing importance spatially temporally encompassing variability within watershed’s stream network.

Язык: Английский

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Impacts of sea-level rise on groundwater inundation and river floods under changing climate

Journal of Hydrology, Год журнала: 2022, Номер 614, С. 128554 - 128554

Опубликована: Окт. 26, 2022

Язык: Английский

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Particle swarm and grey wolf optimization: enhancing groundwater quality models through artificial neural networks

Stochastic Environmental Research and Risk Assessment, Год журнала: 2023, Номер 38(3), С. 993 - 1007

Опубликована: Ноя. 18, 2023

Язык: Английский

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Global groundwater in the Anthropocene

Elsevier eBooks, Год журнала: 2023, Номер unknown, С. 483 - 500

Опубликована: Янв. 1, 2023

Язык: Английский

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Contribution of standardized indexes to understand groundwater level fluctuations in response to meteorological conditions in cold and humid climates

Journal of Hydrology, Год журнала: 2024, Номер 634, С. 131105 - 131105

Опубликована: Март 24, 2024

Understanding the fluctuations in groundwater levels response to meteorological conditions is challenging, especially given slow transit time associated with reservoirs and short duration of series for levels. Nevertheless, this knowledge crucial water resource management, that global warming will drastically impact hydrological dynamics cold humid climates. The objective work was quantify how standardized indexes contribute understanding level climates (10 23 years). relationships between precipitation index (SPI), temperature (STI), climate indexes, (SGI) were analyzed. reactivity examined 2000 2022 using measurements from 152 wells located 46°N 52°N province Quebec (Canada). results showed available sufficient provide new insights into role on fluctuations, demonstrating usefulness indexes. One main contributions study hydrogeological systems go through an annual reset due prolonged freezing period. This one drivers isolating year-to-year conditions, contributing short-duration droughts.

Язык: Английский

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