[HTML][HTML] Model predictive control of water resources systems: A review and research agenda
Abstract Model Predictive Control (MPC) has recently gained increasing interest in the
adaptive management of water resources systems due to its capability of incorporating …
adaptive management of water resources systems due to its capability of incorporating …
Optimization methods in water system operation
BPJ Becker, CJ Jagtenberg, K Horváth… - Wiley …, 2024 - Wiley Online Library
Operational water management is a critical global challenge, and decision making can be
improved by using mathematical optimization. This paper provides an overview of …
improved by using mathematical optimization. This paper provides an overview of …
A stochastic data‐driven ensemble forecasting framework for water resources: A case study using ensemble members derived from a database of deterministic …
J Quilty, J Adamowski… - Water Resources Research, 2019 - Wiley Online Library
In water resources applications (eg, streamflow, rainfall‐runoff, urban water demand [UWD],
etc.), ensemble member selection and ensemble member weighting are two difficult yet …
etc.), ensemble member selection and ensemble member weighting are two difficult yet …
Multi-objective ensembles of echo state networks and extreme learning machines for streamflow series forecasting
Streamflow series forecasting composes a fundamental step in planning electric energy
production for hydroelectric plants. In Brazil, such plants produce almost 70% of the total …
production for hydroelectric plants. In Brazil, such plants produce almost 70% of the total …
A generic data-driven technique for forecasting of reservoir inflow: Application for hydropower maximization
A generic and scalable scheme is proposed for forecasting reservoir inflow to optimize
reservoir operations for hydropower maximization. Short-term weather forecasts and …
reservoir operations for hydropower maximization. Short-term weather forecasts and …
Bayesian extreme learning machines for hydrological prediction uncertainty
In recent years, extreme learning machines (ELM) have been used to accurately predict a
variety of hydrological variables (eg, streamflow, precipitation, river water quality). Using the …
variety of hydrological variables (eg, streamflow, precipitation, river water quality). Using the …
Neural-based ensembles and unorganized machines to predict streamflow series from hydroelectric plants
Estimating future streamflows is a key step in producing electricity for countries with
hydroelectric plants. Accurate predictions are particularly important due to environmental …
hydroelectric plants. Accurate predictions are particularly important due to environmental …
Modeling the role of reservoirs versus floodplains on large-scale river hydrodynamics
Large-scale hydrologic–hydrodynamic models are powerful tools for integrated water
resources evaluation at the basin scale, especially in the context of flood hazard …
resources evaluation at the basin scale, especially in the context of flood hazard …
Conditioning ensemble streamflow prediction with the North Atlantic Oscillation improves skill at longer lead times
S Donegan, C Murphy, S Harrigan… - Hydrology and Earth …, 2021 - hess.copernicus.org
Skilful hydrological forecasts can benefit decision-making in water resources management
and other water-related sectors that require long-term planning. In Ireland, no such service …
and other water-related sectors that require long-term planning. In Ireland, no such service …
A stacking ensemble model for hydrological post-processing to improve streamflow forecasts at medium-range timescales over South Korea
DG Lee, KH Ahn - Journal of Hydrology, 2021 - Elsevier
This study presents the potential of hydrological ensemble forecasts over South Korea for
medium-range forecast lead times (1–7 days). To generate hydrological forecasts, this study …
medium-range forecast lead times (1–7 days). To generate hydrological forecasts, this study …