Ensemble machine learning paradigms in hydrology: A review
Recently, there has been a notable tendency towards employing ensemble learning
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
methodologies in assorted areas of engineering, such as hydrology, for simulation and …
Deep learning methods for flood map**: a review of existing applications and future research directions
Deep Learning techniques have been increasingly used in flood management to overcome
the limitations of accurate, yet slow, numerical models, and to improve the results of …
the limitations of accurate, yet slow, numerical models, and to improve the results of …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
[HTML][HTML] A critical review of real-time modelling of flood forecasting in urban drainage systems
There has been a strong tendency in recent decades to develop real-time urban flood
prediction models for early warning to the public due to a large number of worldwide urban …
prediction models for early warning to the public due to a large number of worldwide urban …
Coupling a hybrid CNN-LSTM deep learning model with a boundary corrected maximal overlap discrete wavelet transform for multiscale lake water level forecasting
Develo** accurate lake water level (WL) forecasting models is important for flood control,
shoreline maintenance and sustainable water resources planning and management. In this …
shoreline maintenance and sustainable water resources planning and management. In this …
[HTML][HTML] A critical review of digital technology innovations for early warning of water-related disease outbreaks associated with climatic hazards
Water-related climatic disasters pose a significant threat to human health due to the potential
of disease outbreaks, which are exacerbated by climate change. Therefore, it is crucial to …
of disease outbreaks, which are exacerbated by climate change. Therefore, it is crucial to …
Groundwater level modeling with machine learning: a systematic review and meta-analysis
Groundwater is a vital source of freshwater, supporting the livelihood of over two billion
people worldwide. The quantitative assessment of groundwater resources is critical for …
people worldwide. The quantitative assessment of groundwater resources is critical for …
[HTML][HTML] Global perspectives on groundwater infiltration to sewer networks: A threat to urban sustainability
While existing studies on sewer networks have explored topics such as surface water inflow,
limited research has delved into groundwater infiltration (GWI). This study aims to fill this …
limited research has delved into groundwater infiltration (GWI). This study aims to fill this …
Application of novel binary optimized machine learning models for monthly streamflow prediction
Accurate measurements of available water resources play a key role in achieving a
sustainable environment of a society. Precise river flow estimation is an essential task for …
sustainable environment of a society. Precise river flow estimation is an essential task for …
The determinants of household water consumption: A review and assessment framework for research and practice
Achieving a thorough understanding of the determinants of household water consumption is
crucial to support demand management strategies. Yet, existing research on household …
crucial to support demand management strategies. Yet, existing research on household …