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A review on the applications of machine learning for runoff modeling
B Mohammadi - Sustainable Water Resources Management, 2021 - Springer
The growing menace of global warming and restrictions on access to water in each region is
a huge threat to global hydrological sustainability. Hence, the perspective at which …
a huge threat to global hydrological sustainability. Hence, the perspective at which …
Application of machine learning and emerging remote sensing techniques in hydrology: A state-of-the-art review and current research trends
A Saha, SC Pal - Journal of Hydrology, 2024 - Elsevier
Water, one of the most valuable resources on Earth, is the subject of the study of hydrology,
which is of utmost importance. Satellite remote sensing (RS) has emerged as a critical tool …
which is of utmost importance. Satellite remote sensing (RS) has emerged as a critical tool …
Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study
F Granata, F Di Nunno, G de Marinis - Journal of Hydrology, 2022 - Elsevier
Prediction of river flow rates is an essential task for both flood protection and optimal water
resource management. The high uncertainty associated with basin characteristics …
resource management. The high uncertainty associated with basin characteristics …
Performance comparison of an LSTM-based deep learning model versus conventional machine learning algorithms for streamflow forecasting
M Rahimzad, A Moghaddam Nia, H Zolfonoon… - Water Resources …, 2021 - Springer
Streamflow forecasting plays a key role in improvement of water resource allocation,
management and planning, flood warning and forecasting, and mitigation of flood damages …
management and planning, flood warning and forecasting, and mitigation of flood damages …
An enhanced monthly runoff time series prediction using extreme learning machine optimized by salp swarm algorithm based on time varying filtering based empirical …
Reliable runoff prediction plays a significant role in reservoir scheduling, water resources
management, and efficient utilization of water resources. To effectively enhance the …
management, and efficient utilization of water resources. To effectively enhance the …
Modeling streamflow in non-gauged watersheds with sparse data considering physiographic, dynamic climate, and anthropogenic factors using explainable soft …
C Madhushani, K Dananjaya, IU Ekanayake… - Journal of …, 2024 - Elsevier
Streamflow forecasting is essential for effective water resource planning and early warning
systems. Streamflow and related parameters are often characterized by uncertainties and …
systems. Streamflow and related parameters are often characterized by uncertainties and …
Uncertainty analysis of climate change impacts on flood frequency by using hybrid machine learning methods
MV Anaraki, S Farzin, SF Mousavi, H Karami - Water Resources …, 2021 - Springer
In the present study, for the first time, a new framework is used by combining metaheuristic
algorithms, decomposition and machine learning for flood frequency analysis under climate …
algorithms, decomposition and machine learning for flood frequency analysis under climate …
[HTML][HTML] River stream flow prediction through advanced machine learning models for enhanced accuracy
N Kedam, DK Tiwari, V Kumar, KM Khedher… - Results in …, 2024 - Elsevier
Abstract The Narmada River basin, a significant water resource in central India, plays a
crucial role in supporting agricultural, industrial, and domestic water supply. Effective …
crucial role in supporting agricultural, industrial, and domestic water supply. Effective …
[HTML][HTML] Application of machine learning and process-based models for rainfall-runoff simulation in Dupage River basin, Illinois
A Bhusal, U Parajuli, S Regmi, A Kalra - Hydrology, 2022 - mdpi.com
Rainfall-runoff simulation is vital for planning and controlling flood control events. Hydrology
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …
modeling using Hydrological Engineering Center—Hydrologic Modeling System (HEC …
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …