A comprehensive survey of machine learning methodologies with emphasis in water resources management
M Drogkoula, K Kokkinos, N Samaras - Applied Sciences, 2023 - mdpi.com
This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …
algorithms, highlighting their practical applications in the critical domain of water resource …
A hybrid hydrologic modelling framework with data-driven and conceptual reservoir operation schemes for reservoir impact assessment and predictions
Reservoirs have been built worldwide to address the water-related issues. To fully
understand their potential impacts on the hydrologic regime, explicitly parameterizing …
understand their potential impacts on the hydrologic regime, explicitly parameterizing …
Explainable machine learning model for multi-step forecasting of reservoir inflow with uncertainty quantification
We propose an explainable machine learning (ML) model with uncertainty quantification
(UQ) to improve multi-step reservoir inflow forecasting. Traditional ML methods have …
(UQ) to improve multi-step reservoir inflow forecasting. Traditional ML methods have …
[HTML][HTML] Enhancing surface water monitoring through multi-satellite data-fusion of Landsat-8/9, Sentinel-2, and Sentinel-1 SAR
Long revisit intervals and cloud susceptibility have restricted the applicability of earth
observation satellites in surface water studies. Integrating multiple satellites offers potential …
observation satellites in surface water studies. Integrating multiple satellites offers potential …
Insights from Dayflow: A historical streamflow reanalysis dataset for the conterminous United States
Reconstructed historical streamflow time series can supplement limited streamflow gauge
observations. However, there are common challenges of typical modeling approaches …
observations. However, there are common challenges of typical modeling approaches …
National estimation of regulated water storage of reservoirs in China
The need for man-made reservoirs has increased with the growing population and changing
climate. One of the most intensive human-induced alterations of the hydrological cycle is the …
climate. One of the most intensive human-induced alterations of the hydrological cycle is the …
Estimation of water storage capacity of Chinese reservoirs by statistical and machine learning models
Reservoir is essential for water resources management and utilization, and its storage
capacity is the key information for the scientific and engineering community. Over 95% of …
capacity is the key information for the scientific and engineering community. Over 95% of …
[PDF][PDF] Data-driven modeling of municipal water system responses to hydroclimate extremes
Sustainable western US municipal water system (MWS) management depends on
quantifying the impacts of supply and demand dynamics on system infrastructure reliability …
quantifying the impacts of supply and demand dynamics on system infrastructure reliability …
A Hierarchical Temporal Scale Framework for Data‐Driven Reservoir Release Modeling
Q Longyang, R Zeng - Water Resources Research, 2023 - Wiley Online Library
As an important anthropogenic interference in the hydrologic cycle, reservoir operation
behavior remains challenging to be properly represented in hydrologic models, thus limiting …
behavior remains challenging to be properly represented in hydrologic models, thus limiting …
Analysis of reservoir outflow using deep learning model
SS Choudhary, SK Ghosh - Modeling Earth Systems and Environment, 2024 - Springer
Predicting reservoir outflow is crucial for managing water resources in under extreme flood
and drought conditions. Time series study of reservoir outflow relies heavily on previous …
and drought conditions. Time series study of reservoir outflow relies heavily on previous …