Water management has long relied on reactive measures. When rainfall increases, dams open to regulate water levels. But what if this process could be optimized using advanced algorithms? Alan Tehan and his team at Technical Services in Syracuse, Indiana, are exploring that very question by leveraging real-time water level data shared by the Turkey Creek Dam & Dike Conservancy District to better understand and optimize dam operations. With extensive experience in automotive control and engine systems, his team is investigating predictive modeling as a tool for refining our dam operations.
The Current Approach
As it stands, dam operations follow a straightforward formula. Rain arrives, the dam opens, and water levels adjust accordingly. While functional, this reactive approach may lack efficiency. Tehan believes there is enough aggregated data, historical rainfall trends, inflow rates, sun exposure, and local water usage to predict dam behavior for us with more precision.
Applying Engine Control Principles
Technical Services Inc. has expertise in electronic control systems, primarily focused on automotive applications. Many modern engine management systems rely on predictive algorithms to optimize fuel consumption and mission-critical performance. Tehan sees potential in applying similar predictive techniques to Turkey Creek’s dam operations, using data-driven modeling to anticipate changes in water inflow and adjust our dam controls accordingly.
Building the Predictive Model
The foundation of this initiative is historical data; rainfall trends spanning 50 years, patterns from the past decade, and recent records from the last year. Additional environmental factors such as sprinkler usage and sun exposure are included to build a more comprehensive forecast model. Despite its promising potential, this process will take time. Our dam is currently functioning properly, so the goal isn’t to replace manual operations but to enhance efficiency for all. Initial testing would involve running predictive algorithms alongside manual operations for at least a year or more, observing the accuracy before implementation.
Safeguarding the System
Caution is key in any shift toward automation, and this project is no exception. Observations will take priority before any adjustments to dam operations are made. Even if implemented, a manual override will remain intact by our dam operators, ensuring that unexpected scenarios don’t disrupt our water management. One possible improvement could involve a more incremental approach, rather than waiting for a major rainfall event to open the dam by several inches. Predictive modeling could facilitate smaller, controlled adjustments over time. This could lead to smoother water level fluctuations, improving conditions for those who rely on our lakes.
The Road Ahead
While predictive modeling in water management is still an emerging concept, the potential is promising. If successful, this initiative could set a precedent for a more proactive dam control for our district, ultimately leading to better-managed reservoirs and more efficient use of natural resources.