Data analysis continues to play a key role in decision-making sediment investigations. It underpins much of the investigation, remediation, and restoration of the environmental and economic vitality of waterways and aquatic systems. The amount of information available is expanding rapidly, often through remote sensing and large-scale data collection efforts. Scientists and engineers are increasingly finding novel ways to leverage digital tools, automation, and algorithms to evaluate sediment and water quality datasets in order to make informed data-driven decisions.

This session focused on advanced data analysis and decision tools that provide new insights into sediment remediation and improving water quality. The session highlighted platform and poster presentations from 18 academic and industry participants. Presentations covered a wide range of examples related to advanced data analysis and decision tools, such as machine learning, artificial neural network modeling, data mining, remote sensing and GIS, and interactive web-based information management systems.

A full list of presentations in the session is available in the technical program.