The Stringfellow Superfund waste site is located approximately 50 miles east of Los Angeles in Southern California. The site includes a former Class I industrial waste disposal area that accepted industrial wastes from 1956 to 1972. Monitoring of the site includes over 400 monitoring wells, over 300 domestic wells, and over 1,000 locations made up of borings, CPTs, process measuring points, and other locations. There have been over 250,000 sampling events to date, resulting in over 3 million sample results and over 300,000 process data points. Tetra Tech has been successfully performing services for DTSC at the Stringfellow Site for over 12 years, including data management, software development (see related description), GIS, modeling, and production of annual reports. Data management services performed at the Stringfellow Site include:"

• Set up of a SQL Server database and migration of historical data housed in 4 separate Microsoft Access database.

• Design and set up of a secure Share Point site to manage the entire data flow. Via the website, a user can perform data uploads via an electronic data deliverable (EDD); manage his/her approval and notification rights; add, edit, and view all types of data in the database, including documents and site events; download EDD templates and software; access EQuIS Enterprise; and access reporting capabilities.

• Created numerous web-based reports, including Chain of Custody, analysis turnaround time, and water levels. Reports can be scheduled to be generated at specific times, and each user on the system has a folder to store their own reports.

• Generation of an approval and notification system for users. The Stringfellow system has over 75 users. For a given user, approval and notification are separately identified for each type of data uploaded, and emails are sent when data needs approval, when data has been successfully uploaded, and when data has been rejected. With this system, users only receive notifications about those types of data that they are interested in.

• Development of a completeness checker to compare chain of custody data to data in the database to ascertain whether all data on the chain of custody exists in the database and whether any extra data is present. This module has streamlined the generation of annual reports since, prior to its implementation, much effort was spent identifying and tracking down data that was missing from the database.

• Development of a Quality Assurance (QA) checker for process data to identify suspect data. The QA checker checks for inconsistent units, changes in equipment, readings outside valid ranges, and identifies likely meter rollovers. Based on this procedure, the data is qualified in the database for easy filtering of suspect data.