An Adaptive Long-Term Monitoring and Operations System (aLTMOs^TM) for Optimization in Environmental Management

Long term monitoring and operations comprise a substantial and growing part of the present value cost of groundwater and soil cleanup systems. These burgeoning costs at groundwater cleanup sites present a significant opportunity for the use of optimization. Numerous optimization technologies have been researched and developed over the past two decades. These have been used to suggest ways to operate pump-and-treat remediation systems at effectively reduced costs. Contemporaneously, characterization methods based on kriging methods, artificial neural networks and Extended Kalman Filtering have been developed and deployed. In addition to mapping property values, the characterization methods detect and describe (spatial and temporal) correlations among aquifer properties, and are used in uncertainty assessments. These technologies are reusable and form the core of an Adaptive Long Term Monitoring and Operations System (aLTMOs) to assess and optimize long term monitoring network performance and costs. A preliminary application of the optimization system to the Army SSCOM in Massachusetts is presented.