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The DECOMP Physical Model (DPM) A Philosophical Muse of Addressing Restoration Uncertainty

The DECOMP Physical Model (DPM) A Philosophical Muse of Addressing Restoration Uncertainty . Dr. Scot E. Hagerthey Decomp Science Workshop 2 December 2010. Ecosystem & Restoration Science. The science of Everglades yesterday and today Description of patterns past

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The DECOMP Physical Model (DPM) A Philosophical Muse of Addressing Restoration Uncertainty

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  1. The DECOMP Physical Model (DPM)A Philosophical Muse of Addressing Restoration Uncertainty Dr. Scot E. Hagerthey Decomp Science Workshop 2 December 2010

  2. Ecosystem & Restoration Science • The science of Everglades yesterday and today • Description of patterns past • Identification of the present patterns and processes • Hypotheses of fundamental drivers • The science of Everglades restoration • Restoration vision • Ecological restoration of degraded systems (theory and practice) • Intimately linked to social, policy, and management issues

  3. CHAOS AND MAYHEM • By February 2005 it was recognized by the DECOMP Project Development Team (PDT) that there were fundamental problems hindering the development of the Project Implementation Report (PIR). • Lack of consensus/uncertainty* on restoration vision. • Scientific and engineering uncertainty on how to quantify benefits of sheetflow, engineer the system to achieve sheetflow, and maintain cost effectiveness. *Uncertainty exists when two or more contradictory explanations are ventured to explain the same phenomenon.

  4. DECOMP Scientific Uncertainties • Is complete backfilling of canals an ecological and/or a hydrological necessity for restoration? • What are the quantifiable ecological benefits of sheet flow and ecosystem benefits? • Is it necessary to completely remove levees? • What are the water depth and hydroperiodtolerances of ridges, sloughs, and tree islands? • What are the effects of water levels in WCA-3B and Shark River Slough on seepage to the Lower East Coast? • Would hydrologic models used to evaluate design alternatives benefit from better parameterization?

  5. The Solution The DECOMP Adaptive Management Plan (DAMP) • Find best restoration design for DECOMP, without compromising water supply or flood control. • Combine data mining, historical analysis, PHYSICAL MODELS, and evaluation tools. • Address specific scientific uncertainties and incorporate new information. • Use multi-agency collaborative approach (with stakeholder input). • Increase understanding of system responses to various activities. • Select optimal project alternative(s).

  6. EIS/FWCAR/ENP DECOMP - PIR DAMP FWS PAL Scoping Data Mining Management Approach Alternatives Physical Models ENP Report Passive Approach Numerical Model Review Draft CAR Initial Screening Information Requirements PM Review Final CAR Final Alternatives Monitor & Report Revised Models Revised PM’s Alternative Evaluations TSP ROD CAR- Coordination Act report EIS- Environmental Impact Statement ENP- Everglades National Park FWS- Fish and Wildlife Service PAL- Planning Aid Letter PIR- Project Implementation Report PM- Performance Measure ROD- Record of Decision TSP- Tentatively Selected Plan

  7. X X X X X X X X X X X X X X X X X X X X X X X X X X X X • DPM Steps I-75 PIR 3 –Backfill/Degrade L-68A Stay within cost cap and operational constraints the DPM was reduced in scale to a BACI flow-way and pulsed flow operations. MIAMI CANAL L-67A PIR 3 – Weirs in L-67A L-67C WCA 3A X X X Identify uncertainty General hypothesis development Team development Hypothesis refinement Scientific approach Initial plan development Plan review Plan refinement Final plan review Project approval Project implementation X PIR 2 – Backfill/Degrade Miami Canal X PIR 2 – Add S-345s Physical Model PIR 3 –Backfill/Degrade L-67C PIR 3 –Backfill /Degrade L-28/L-29 PIR 3 – Backfill L-67A WCA 3B X PIR 3 – Remove S-12s, 343s, 344 PIR 2 – Raise & Bridge East Portion of TT PIR 3 – Bridge West Portion of TT PIR 2 – Degrade L-29 Levee/Canal X X X X X X X X X X X X X X X X X X X X X X X X X

  8. DPM Designed… • to produce scientifically defensible data • with stakeholder involvement • within constraints (risk reduction) • water quality • hydrology • ecology • recreation • to integrate science and engineering

  9. Canal Backfilling Conceptual Model Driver: Structure Transport Driver: Conveyance Flow transport Driver: Sheetflow transport Canal Depth as a function of backfill treatments (No backfill, partial backfill, complete backfill) Groundwater Local Velocity Profile Particle entrainment and deposition Dispersal Marsh Connectivity Canal Connectivity Primary Production Resource and Organic Matter Export to Marsh Thermal Profile Oxygen Profile Water Quality Native Fauna Organic Matter Decomposition Biogeochemistry Physical Transport Exotic Fauna Ecology

  10. Ridge & Slough Conceptual Model Driver: Solute supply Driver: Discharge Water Table transport Subhydro Biogeochem P conc Redox Evapotranspiration Differential peat accretion VegType Hydroperiod Ridge and slough geomorphology Drag Re Particle trapping Lateral Transport of bed sediment by gravity or episodic events Local Velocity Profile Sediment distribution Sed Trans Zones of net particle entrainment and deposition Larsen et al. 2006

  11. Hypothesis Conceptual Model Linkages • Canal Backfilling • 9 hypotheses developed • 6 directly testable within DPM • 3 testable by inference • Ridge and Slough • 17 hypotheses developed • 7 directly testable within DPM • 6 testable by inference • 4 not testable Examples: • SH01: A flow regime that exceeds a critical flow velocity and bed shear stress is not necessary to entrain sediment. It is expected that sustained periods (days to weeks) of flow velocities exceeding a threshold of 3 cm/sec is required to entrain and redistribute a quantity of sediment particles. The long-term cumulative effect of these flow events will result in the restoration and maintenance of the historic ridge & slough landscape. • BH03: Habitat quality (oxygen and temperature depth profiles) will not differ among backfilling treatments. The greater water depths in canals relative to marsh depths may develop different vertical profiles of ecologically important physiochemical constituents (e.g., dissolved oxygen or temperature). Of special concern is the development of waters with low dissolved oxygen concentrations (hypoxia) which could be detrimental to aquatic fauna and affect biogeochemical cycling.

  12. THE DECOMP PHYSICAL MODEL 12

  13. The role of Science in PIR #1 • What is the restoration vision for northern WCA-3A? • What are the key uncertainties? • What are the fundamental hypotheses? • What are the data gaps? • How are they best tested? • What are the risks and how can they be reduced? • Are there opportunities?

  14. Management Options Analysis • Management Options Considered • Passive Management (Natural Recovery) • Adaptive Management (Accelerated Recovery) • Prescribed Burns • Herbicide Application • Mechanical Methods • Chemical Treatment • Seeding • Hydrologic Management • Genetic Constraints • Evaluation Criteria • Literature Review • Costs • Financial (Short-term & Long-term) • Environmental (Direct & Indirect) • Benefits • Uncertainty • Bottom Line

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