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Surface Water Quality Monitoring Information System (SWQMIS) Cindi Atwood Tetra Tech, Inc. (703) 385-6000 Nancy Ragland TCEQ.

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Presentation on theme: "Surface Water Quality Monitoring Information System (SWQMIS) Cindi Atwood Tetra Tech, Inc. (703) 385-6000 Nancy Ragland TCEQ."— Presentation transcript:

1 Surface Water Quality Monitoring Information System (SWQMIS) Cindi Atwood Tetra Tech, Inc. (703) 385-6000 cynthia.atwood@tetratech.com Nancy Ragland TCEQ (512) 239-6546 NRagland@tceq.state.tx.us

2 TCEQ’s New Enterprise Data System for Managing Ambient Water Quality Data

3 Benefits

4 Consolidate and centralize data Consolidate and centralize data Increase data consistency and integrity Increase data consistency and integrity Assist your agency with internal and external data requests Assist your agency with internal and external data requests Help management to turn around urgent, high priority requests quickly Help management to turn around urgent, high priority requests quickly Save time and money Save time and money

5 One Week vs One Day 44 Hours down to 8 Hours 44 Hours down to 8 Hours 2 person task down to a 1 person task 2 person task down to a 1 person task

6 System Deployment

7 Deployed the system successfully in early 2007 Deployed the system successfully in early 2007 Developed the system as: Developed the system as:  Web-based  J2EE and Oracle Integrated the system with web-based GIS functionalities using ESRI ArcIMS and ArcSDE Integrated the system with web-based GIS functionalities using ESRI ArcIMS and ArcSDE

8 Core System Modules Monitoring Stations Monitoring Stations Equipment Equipment Geographical Areas Geographical Areas Constituents Constituents Sampling Sampling Comparison Information Comparison Information Projects Projects Reports and Extracts Reports and Extracts Maps (GIS) Maps (GIS) Assessment Assessment Administration Administration

9 Manage Ambient Water Quality Data

10 Organize data in a way that enhances business processes Organize data in a way that enhances business processes Protect data integrity through clean system design Protect data integrity through clean system design Involve stakeholders at all levels of organization in design and test Involve stakeholders at all levels of organization in design and test Keep system flexible to meet future needs Keep system flexible to meet future needs

11 Consolidate & Centralize Databases

12 Allow core data submittal from various data owners Allow core data submittal from various data owners Consolidate and centralize databases containing : Consolidate and centralize databases containing :  Field measurements  Toxics and organics in a variety of media  Biological  Habitat parameters, etc.  Spatial data

13 Various Data Sources

14 Supply custom interfaces for manual entry Supply custom interfaces for manual entry  Administrators  Data Managers  Field Personnel  Assessors Provide mass data loaders for various data sources including Provide mass data loaders for various data sources including  Continuous data from data loggers  LIMS  USGS  River and municipal authorities in Texas

15 Data Integrity

16 Provide custom interfaces for manual entry Provide custom interfaces for manual entry Enforce consistent data entry of all types of data Enforce consistent data entry of all types of data  Typographical errors  Outlier checks Validate data from manual and mass loaded data Validate data from manual and mass loaded data Review of submitted data by data managers to approve or deny Review of submitted data by data managers to approve or deny

17 Mass Loaded Data Validation The automated validation checks are all run, without stopping after the first “failure.” In this way, a complete list of errors can be shown. The automated validation checks are all run, without stopping after the first “failure.” In this way, a complete list of errors can be shown. Over 50 validation checks run on mass loaded data Over 50 validation checks run on mass loaded data  Check for outliers. Check measurements against predefined ranges (min/max). Compares verify flag in the Results file to see if the outlier value has already been verified by the collector.  If sample collected when raining or has rained within the last 24 hours, report a value of <1. In other words, is days since precipitation (72053) < 1?  Check for duplicates in data set based on station ID, sample date, sample time, and parameter code.

18 GIS Integration

19 Allow map-based creation of sites Allow map-based creation of sites Automatically assign geographic attributes such as basin, county and ecoregion to a site Automatically assign geographic attributes such as basin, county and ecoregion to a site Provide map-based search and reporting features Provide map-based search and reporting features Synchronize geographic data with tabular data Synchronize geographic data with tabular data

20 GIS Integration

21

22 Public Access

23 Allow the public and other organizations to retrieve water quality data Allow the public and other organizations to retrieve water quality data

24 Public Access

25 Public Access – Drill Down 100 x 100 Mile Square

26 Public Access – Drill Down 25 x 25 Mile Square

27 Public Access – Drill Down 6.25 x 6.25 Mile Square

28 Public Access – Select Stations

29 Public Access -- Reports

30 Public Access – Text Reports

31 Reports & Data Extractions

32 Avaliable in: Avaliable in:  HTML  CSV (Comma Separated Values)  Pipe delimited “|” (text) format

33 Reports & Data Extractions Station Inventory Report

34 Reports & Data Extractions Sampling History Report

35 Assessments

36 Integrates SWQMIS with the statistical SAS tools in order to: Integrates SWQMIS with the statistical SAS tools in order to:  Summarize data  Calculate various statistics  Provide reports for assessors

37 Assessments

38 Assessments – Business Logic Identify and convert preferred parameters to correct units Identify and convert preferred parameters to correct units Handle profile samples appropriately Handle profile samples appropriately  Identification of the mixed surface layer Summarize data and calculate statistics Summarize data and calculate statistics  Mean, geometric mean, median, standard deviation, percentiles, confidence intervals

39 Assessments – Business Logic (cont.) Determine appropriate criteria and identify exceedances Determine appropriate criteria and identify exceedances  Basin-specific  Segment-specific  Site-specific  Formulas (acute & chronic metals) Ascertain waterbody’s support status Ascertain waterbody’s support status Provide full documentation for all steps of the process Provide full documentation for all steps of the process

40 Data Flow

41 Transfer of core data to EPA automatically on a periodic basis through web services and the Central Data Exchange (CDX via the Water Quality Exchange (WQX) Transfer of core data to EPA automatically on a periodic basis through web services and the Central Data Exchange (CDX via the Water Quality Exchange (WQX)

42 Data Flow Actively flowing data to the EPA since September, 2007 Actively flowing data to the EPA since September, 2007 Fully automated process Fully automated process Currently transfer physical and chemical data Currently transfer physical and chemical data Will transfer biological data at a later date Will transfer biological data at a later date

43 Administration

44 Track the “history” of data changes Track the “history” of data changes Provide interfaces that allow a database administrator to manage: Provide interfaces that allow a database administrator to manage:  Users  Security  Reference data

45 Lessons Learned Allow design time that is adequate for the scope Allow design time that is adequate for the scope Employ tried technology Employ tried technology Use agile development techniques Use agile development techniques Start third party integration communication and testing early Start third party integration communication and testing early


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