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Council on Watershed Management Meeting MARCH 28, 2019 Meeting No. - PowerPoint PPT Presentation

Council on Watershed Management Meeting MARCH 28, 2019 Meeting No. 7 1 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E Old Business


  1. Council on Watershed Management Meeting MARCH 28, 2019 Meeting No. 7 1 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  2. Old Business Listening Tour Report Out 2019 Outreach & Engagement Plan Round 1 Project Application Summary and Evaluation Criteria Worksheets 2 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  3. Updates and Introductions Data Deliverables 3 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  4. Data and Modeling TAG Data Deliverable Summary Cindy How March 28, 2019 W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  5. Precipitation Why Model? Topography Hydraulic Structures DATA (REALITY) INPUTS Land Use / Predictive Land Cover CONCLUSIONS: Soils WHEN rain will cause floods Hydrography What DAMAGES will be caused Bathymetry • People Models Simplify • reality… Property River Gages • Environment Buildings/ What CHANGES we Assessor can make to reduce or Ecological and manage floods Biological Resources Water Quality …so that we can draw Image from: USGS Lower Mississippi- How does rain conclusions only from the Gulf Water Science Center -- Louisiana become relevant inputs flood? L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  6. Data and Modeling TAG Goals Phase 1: Make Smarter Distribute the “The root of all wise Decisions data decision making is Wisdom (Applied) accurate, complete, transparent, and accessible data” Find the Right Maintain the Answers Data Knowledge (Context) Ask the Right Organize the Questions Data Information (Meaning) Look at Available Collect the Data Information Data (Raw) L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  7. Summary of Data Deliverables Listening Tour and Data Delivery White Papers (6) Memorandum What data are How are we going to out there? share these data? Preliminary Data Gap Summary Where are we missing Data Quality quality data? Memorandum How do we test for data quality? How do we Data Requirements maintain data quality? for Modeling Efforts Memorandum What determines if the data are good/suitable? L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  8. Summary of Data Deliverables USGS Data Lifecycle White Papers Preliminary Data Gap Summary Data Requirements for Modeling Efforts Memorandum Data Management Plan Data Quality Quality Assurance Plan/ Quality Action Plan Memorandum Data Delivery Memorandum L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  9. Themes Across Findings and Recommendations Provide guidelines to contractors to ensure recommended methods are used uniformly for handling “Record Datasets” – Leverage and analyzing data How the data will be used drives Use widely accepted data existing “authoritative” data the required level of accuracy standards sources (USGS, USACE, DOTD, • Data Management Plan etc.) • Quality Assurance Plan • Modeling guidelines White “Value - Added Datasets” – Look for opportunities to Leverage existing tools, Papers Manage and store only cooperate on data collection knowledge, and experience local/project data Preliminary Data Gap Summary Data Requirements for Modeling Efforts Memorandum Data Quality Memorandum Data Delivery Memorandum L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  10. Data Gap Analysis Key Gaps LiDAR/ River Assessor/Built Bridge and Ecological/ Historical Gages/ NHD Inventory Culvert data Biological Flooding • Data gaps have been • No statewide standard • Data required for • Indicator datasets and • No existing identified data for assessor data modeling not available expert support needed consolidated dataset in statewide datasets for historical damages • Additional data are • No existing built • Recommendation: being collected / data inventory dataset • Recommendation: Create statewide • Recommendation: edits being made Create consolidated datasets and leverage Use of standard form • Recommendation: dataset based on a existing expertise to for collection • Recommendation: Standardization of template evaluate potential information after Continue on current minimal fields for project impacts flooding events, flood course of action assessor data complaint log L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  11. Data Gap Analysis Recurring Themes Importance of Need to consolidate consistent, well Hard copy records data from multiple documented horizontal need to be digitized sources and vertical references L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  12. Data Standards Memorandum Existing Comparison of standards for standards when each type of more than one data exists Recommended standards L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  13. Data Quality Assessment Examples of how Types of quality other control/quality organizations assurance manage quality approaches Recommended approaches by dataset L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  14. Data Quality Assessment Types of QA/QC Measures • Procedures and • Programmed tools to • Review by qualified certification check for acceptable staff requirements put into inputs or results place • Guidance documents and adopted standards Programmatic Automated Hands-on L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  15. Data Quality Assessment Example Dataset Specific Recommendations LiDAR: USGS 3DEP as Record Hydrography: NHD as Record Create record datasets, starting Dataset. Dataset. with bridge and culvert data collected and maintained by Rely on incorporation into USGS Additional data collection to DOTD. 3DEP products, 3DEP quality follow USGS standards and to be standards apply. submitted via the NHD Markup Coordinate multiple agencies for App. future data collection based on Survey: Track via polygon with SARP stream crossing survey contact and file location listed, templates. GIS and CADD data requirements. L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  16. Data Delivery Organization and Content Recommendations • Separate landing pages based on target audience • Public User • Technical User • Local Government User • Funding Applicant User • Include a site guide that helps the user navigate • Evaluate desired content and functionality based on existing examples L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  17. Data Delivery Data Delivery Recommendations • Rely on record dataset sources, with new framework for value-added and project- related data • Make links to available data sources available on LWI’s website (from White Papers and Preliminary Data Gap Summary) • Ensure that data is well organized based on data type and category/theme L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  18. Next Steps Data Data and Management Data Collection Prioritize Modeling TAG Plan / Ongoing and Plan Efforts Recommendations Quality Maintenance Implementation to Council Assurance Plans L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  19. THANK YOU watershed@la.gov L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  20. Updates and Introductions Statewide Modeling Framework 20 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

  21. Statewide Modeling Framework Ehab Meselhe, PhD PE Emad Habib, PhD PE Tulane University University of Louisiana at Lafayette 21 L O U I S I A N A W A T E R S H E D I N I T I A T I V E W O R K I N G T O G E T H E R F O R S U S T A I N A B I L I T Y A N D R E S I L I E N C E

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