STREAMLINED POTENTIOMETRIC SURFACE MAPPING FOR LONG-TERM MONITORING AT ENVIRONMENTAL SITES

Potentiometric surfaces are crucial for assessing contaminant transport, and potentiometric mapping is often performed repetitively (e.g., semi-annually or annually) as part of long-term site monitoring. The workflow typically involves data management, contour mapping, and map production. Maintaining quality and consistency over time can be time-consuming and tedious. We have developed a proven process to automate the bulk of the workflow while still maintaining the flexibility to allow environmental professionals with site knowledge to easily inject their understanding of the site hydrogeology into the workflow. This process yields more consistent and higher-quality mapping products while reducing labor costs by 75 to 90%.

At the heart of the process is the creation of a template grid, which can be readily generated from existing hand-drawn contours. Such contours honor water level data from a monitoring event and reflect flow pattern interpretations made by knowledgeable environmental professionals. However, the contours are static and not easily adapted from event to event as subtle to moderate water level changes occur. Translating these hand-drawn contours into a template grid permits prior events mapped manually to be used as the basis for automated mapping of subsequent monitoring events. Data from the subsequent monitoring event are simply compared to the template grid to generate a dataset of differences. These differences are then gridded, and the resulting correction grid is added to the template grid to produce a final grid which honors the current water level data but still maintains the shape (i.e., the hydrogeologic interpretations) captured in prior maps. Contours, at any desired interval, are automatically created and require only minor adjustments.

In addition, the semi-automated approach includes 1) managing data in a relational database, 2) exporting spatial data to a geodatabase, and 3) automating final map preparation in ArcGIS. The data management approach incorporates tools to easily export data for grid/contour production and to support automated custom-labeling used in final ArcGIS map production. For instance, water level labels are automatically updated using feature-linked geodatabase annotations in ArcGIS, thus eliminating labor costs for manual label repositioning.