Water Management

As a result of today’s competitive energy market and increased concerns regarding the environment, hydropower operators must develop business strategies to maximize availability and profitability of their plants to gain competitive advantages.

The scope of the Water Management Interest Group (WMIG) is to focus on the development of methods & tools required to optimize hydraulic processes while maintaining safe and environmentally-friendly operations.

Topics of interest include watershed management and water use planning, meteorological forecasting (water, ice, flow), operational modeling (benchmarking and performance measurement), data acquisition techniques, and impact assessment (flow, environmental requirements).

Topics and Issues:

• Watershed Management/ Water Use Planning

Water Use Management Strategies
Global Flow Management Strategies

• Operational Modeling and Optimization

Benchmarking and Performance Measurement
Modeling and Optimization Techniques
Global Watershed Optimization
Single Reservoir Optimization
Multiple Criteria Optimization
Expert Systems

• Meteorology – Climate

Variability and Forecasting Evaluations
Impacts on Watershed Hydrology
Instrumentation and Communications
Climate Change

• Hydrology

Precipitation Forecasting
Uncontrolled Inflow Forecasting
Stochastic Hydrology
Gap Filling and Data Extension
Regression Techniques
Statistical Techniques

• Data Acquisition & Techniques

Collection, Validation and Diffusion
GIS

• Hydraulics

Dam Break and Flood Routing
Erosion and Sedimentation Transport
Ramping Rates
Fish Habitat Issues
Simulation of Flows and Water Levels
Hydraulics of Dam Failures
Physical and Mathematical Modeling

• Ice on Rivers and Reservoirs

Mathematical Modeling of Ice Conditions
Operating Strategies

• Impact Assessment

Evaluation of the Impact of Flows and Water Levels
Adaptation to Environmental Requirements
Mitigation Techniques

Current Projects

• Risk Informed Decision Making Framework for Hydro Project Operation under High Inflow Conditions: Accounting for Uncertainty and RiskDevelop a Risk Informed Decision Making (DM) framework for responding to unusual and extreme conditions - such as high inflow events that do not normally involve dam safety concerns. This framework would formalize the treatment of uncertainty and reflect the risk taking attitudes, values and trade-off principles of the organization. The framework would allow operation-planners to more quickly respond to such emergency situations and openly and transparently communicate operational decisions made to stakeholders and senior management.
• Integration of Radar & Satellite Participation Estimates into Rain and Snow Gauge NetworksThe objectives of this project are to: a)Identify and document the technologies currently being used or that have the potential to be used to successfully merge precipitation and snow water equivalent estimates from radar and satellite with the raw precipitation and snow measurement data collected from ground networks, with a view to providing more accurate reservoir inflow estimates; b)Evaluate which of these technologies are the most promising or most frequently applied to the integration of radar and satellite data with data from ground truthing networks, taking into consideration that it may be necessary to address precipitation and snow water equivalent measurements separately.
• Impact of Wind, Temperature and Other Environmental Factors on Reservoir Evaporation LossesDocument progress made since the mid‐1990’s, with particular focus on the period 2003 to present, in methods and technologies for monitoring and modelling of reservoir evaporative losses; Identify research results that provide direction, again in a location‐specific context, on reliable yet cost‐effective approaches to meeting the data requirements of a well performing reservoir evaporation forecasting model; Prioritize geographical areas of focus based on available evaporative water losses data;
• Benchmarking Performance OptimizationTo study the current use of hydropower water resource optimization programs, to determine how participants are deriving turbine performance base line data used by the optimization models and to recommend best practices for use in optimization models.

Recently Completed Projects