23rd Annual NARPM Training Program

Case Study in Data

Management: San Fernando

Valley Superfund Site

Data Management at the Site Specific Level

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Site Location • 4 Ous

• 3 Sites

• 3 treatment facilities

• Over 40 data providers

• VOCs (TCE, PCE), 1,4-dioxane,

CrVI, vapor intrusion???

• 3 cities

• Drinking water source

• Water rights

• State/EPA leads

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2-D plume maps are the primary

deliverable for understanding remedy

performance and contamination!

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Problems with historic SFV database

Does not allow RPMs/data users to interact with data without contractor assistance

SFV Database is expensive and difficult to maintain

Limited functionality

A library of data for a high cost

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The SFV Database

The SFV database is a repository for analytical and groundwater data from RWQCB facilities, PRPs, and Cities in the SFV.

The original database was an EXCEL file containing some ltihology, water quality, and water level data.

With each passing year the database grows. As it grows it’s harder to manage

Evolution of SFV Database

1992: MS Excel database

1998: Microsoft Access

2004: SQL Database, very specialized and contractor dependent to access and query

2013: Migration to EQuIS

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Components of the Historic SFV Database

2M records, 74 data tables

Required the support of a SQL expert to maintain and query

40+ facilities tracked (and growing)

Updated once or twice a year due to high cost ($40-$80K to upgrade)

Distributed as a Microsoft Access DB (1 GB file and growing) through a sharepoint website

SQL database maintenance is 40-50% of SFV Basinwide OU costs

SFV Data Costs

2009 Monthly = $14,000

2009 Total = $168,000

2010 Monthly= $12,000

2010 = $150,000

2011 Monthly = $19,000

2011 Total = $225,000

Average 2012= $16,000

Total = $200,000

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Solution: SFV Pilot Database

Purpose

Tested the utility of the EQuIS environmental data management platform for SFV data

Test the features, functionality, and ease of use of the platform

Tested 3rd party software to generate data products useful to EPA’s mission in the SFV

Evaluate adopting platform for long term data management in the SFV

Goals

Reduce costs by 50% or more

Use technology to assist with tracking and characterizing the contaminants in the SFV aquifer

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Why Environmental Quality Information

System (EQuIS)? Successfully used in Regions 2,3,4,5, 7 and 9; used for

Deepwater Horizon oil spill

Thoughtfully designed data management software that includes

Web interface for easy retrieval and data viewing (direct access to data!)

Easily interfaces with popular environmental software

Method to standardize data (EPA custom templates)

Tool data submitters can use to QC submitted data

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What is EQuIS

EQuIS Professional: Desktop application for data analysis. Interfaces with popular environmental analysis software such as RockWorks, ArcGIS, and EnviroInsite; for EPA and consultants.

EQuIS Enterprise: Web-based interface, storage for site docs and photos, easily exports to Excel, Google Earth, ArcGIS; for Superfund staff.

EQuIS Data Processor (EDP): Desktop application for uploading data to the EQuIS database. Checks quality and completeness of data before uploading; for data submitters.

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EQUIS Professional

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EQuIS Professional Interface Capabilities

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EQuIS Enterprise

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EQuIS Data Processor

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Pilot Results – Water Level Map

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Pilot Results - Chemical Cross Sections

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Pilot Results- Digitized Contouring

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Pilot Results - Google Earth CrVI Well

Concentration Visualization

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Pilot Results - Instant Conceptual Site

Lithologic Models

Rockworks

Fence

Diagram

Rockworks

Conceptual

Site Model

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SFV Database Project Status

Purchased EQuIS in Sept 2012

Migrated 15 years of data

Challenges: Poor contractor performance, lack of internal support, RAC transition, funding

EDD has been provided to all data submitters as of Spring 2014

LADWP and Lockheed both adopted EDD and platform in 2014

Biggest success is standardizing data across the site

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Next Steps

Summer 2014: Work with the site RPMs to learn how to tailor the tool to meet their needs

2015: Move out of the data management phase into the data analysis phase. Begin generating data products to better refine CSM with the goal of providing information that will be valuable in improving approaches to remedies.

Final Thoughts - EPA should lead by example; EPA sets precedents