Developing a Model-based Drinking Water Decision Support System Featuring Remote Sensing and Fast Learning Techniques.

Timely adjustment of operating strategies in drinking water treatment in response to water quality variations of both natural and anthropogenic causes is a grand technical challenge. One essential approach is to develop and apply integrated sensing, monitoring, and modeling technologies to provide early warning messages to plant operators. This paper presents a thorough literature review of the technical methods, followed by the development of a model-based decision support system (DSS).