Using Decision Support Systems to Improve Water Supply Planning and Operations

Authors:

  • Josh Weiss and Grantley W. Pyke - Hazen and Sawyer

For the New York City Department of Environmental Protection, we developed the Operations Support Tool (OST), a coupled water supply and quality model, to more accurately monitor and predict reservoir levels and turbidity conditions throughout the system.

Utilities are increasingly facing challenges that include cost constraints, aging infrastructure, increasing regulations, variable source water quality, impacts of droughts and other extreme events, and the need to balance competing stakeholder objectives. In increasingly complex systems that often include regional water supply issues, many utilities lack the robust, integrated analytical tools necessary to evaluate system vulnerabilities, make cost-effective capital decisions, and develop robust system operating policies. This presentation will demonstrate how Decision Support Systems (DSS) can be used along with forecasting information to support robust and efficient long-term planning, including evaluating the need and timing of capital expenditures and developing triggers for adaptive reservoir management.

A DSS developed for long-term planning can be expanded with data acquisition functionalities and near-term forecasts to support routine and event-based evaluation of alternative operating strategies. This approach provides a robust analytical basis for determining and documenting risk-based operations decisions in the near-term that, because it uses the same tools, is linked to long-term water supply planning. A DSS for operations support combines current system data with inflow forecast data and system operating rules to project the likely range of reservoir levels and water quality over the coming weeks and months. This presentation will demonstrate how a DSS can be used to help system managers make efficient and defensible operating decisions that best meet near-term objectives.

The expanded analytical capabilities afforded by a DSS can be perceived as a double-edged sword: they provide utilities with better actionable information, but typically will be based on risk that includes a non-zero chance of failure to meet one or more objectives. Further, since most water supply decisions will result in some objectives being met while others are not, managers relying on DSS output will need to defend decisions that explicitly fall short of meeting some set of objectives. At the same time, a DSS provides solid analytical support and documentation with which to defend decisions and demonstrate the risks associated with alternative policies. The risks of operating decisions will not have changed, but the water supply manager’s understanding of those risks will have improved. We will offer a perspective on how water supply managers and operators can use the probabilistic information provided by a DSS to make better decisions, both for long-term capital expenditures and near-term operating policies.

This paper will provide an overview of the analytical tools available to water supply system managers and operators to support robust, multi-objective decision-making under increasingly complex and uncertain conditions. We will demonstrate how supply and demand forecasting tools can be combined into a single Decision Support System (DSS) that can be used in both long-term planning and near-term operations. We will draw upon our experiences developing and applying these analytical tools to systems facing widely different challenges, including Tampa Bay Water and New York City.

For more information, please contact the author at jweiss@hazenandsawyer.com.

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Horizons Fall 2017 (pdf)

Horizons showcases significant water, wastewater, reuse, and stormwater projects and innovations that help our clients to achieve their goals, and can help you achieve yours. Articles are written by top engineers and process group leaders, demonstrating and explaining the beneficial application of a variety of technologies and tools.

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