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  • 1. Effects of Nonpoint SourceMarsh Loading on Complex Estuaries Edwin A. Roehl, Jr. John B. Cook, PE Advanced Data Mining Intl Greenville, SC
  • 2. South Carolina coastal estuaries Myrtle Beach Grand Strand Georgetown Charleston Beaufort Savannah
  • 3. A brief review of tidal dynamics Freshwater Riverine Coastal Inputs Inputs Saltwater Saltwater-Freshwater Interface “…estuaries may never really be steady-state systems; they may be trying to reach a balance they never achieve.” Keith Dyer, from Estuaries – A Physical Introduction (1997)
  • 4. Difficult to wrestle down nonpointsource effects Difficult to measure and predict NPS impacts on upland areas  Data sets sparse as compared to point source data  Equations and models to estimate loads can have large prediction errors (50-100%) NPS problem compounded on the coast Low-gradient system with little or no slope  Tidal complexities of receiving stream  Poorly defined drainage areas  Limited understanding of runoff process along the coast
  • 5. Complex forces on a tidal river Overland flow from watershed•Smallcontributingwatershed•Little Tidal forcingfreshwater from oceaninflow connection•Tidallydominated
  • 6. Consider alternative approach toNPS modeling Data mining  Transforming data into information  Amalgamation of techniques from various disciplines: information theory, signal processing, statistics, machine learning, chaos theory, advanced visualization The physics is manifested in the data Need to extract the information from large data sets of continuous monitoring w/in estuary
  • 7. Artificial Neural Networks (ANN) models Mathematical representation of the brain  provides complicated behaviors from “simple” components - neurons and synapses x1 x2 y1 inputs x3 outputs y2 x4 x5  models created by training the ANN to learn relationships between variables in example data  form of machine learning from Artificial Intelligence (AI)
  • 8. 3D response surfaces for SC, WL, Q Surface created by ANN model “Unseen” variables set to constant value Manifestation of historical behavior of system Provides insight into the process dynamics or physics
  • 9. ANN model performance forhydrodynamic behavior
  • 10. Data mining NPS – Consider CooperRiver Estuary case study  Sensitivity of DO to rainfall, water tidal-level flushing action and tidal range determined  Model able to simulate rainfall effects/amounts  System had long-term data bases  >3 years of 15-minute WL, DO, SC, WT
  • 11. Cooper RiverEstuaryArea of nodevelopmentLittle impactfrom all pointsources
  • 12. Signal decomposition of water level Periodic component – Tidal rangeChaotic component –Filtered water level
  • 13. Dissolved oxygen (DO) dynamics Measured DO time seriesDissolved-oxygen deficit= difference b/w saturationand measured
  • 14. Or, in equation form:DO deficit (DOD) =DO [saturated f(T and salinity)]- DO (measured)
  • 15. Effects of rainfall Z-axis – DOD on Cooper River X & Y axis – 1- and 3- day rainfalls ∆2 mg/LThe sensitivity of DODto rainfall :DOD/inch ≈ 2 mg/L/ 8 in. 2 inchesof rainfall over 2 days 2 in ches= 0.25 mg/L per inch ofrainfall.
  • 16. Cooper River measured and predictedDO-deficit (DOD) as result of rainfall only RAINAA=2-day moving window average
  • 17. In addition to rainfall effects, responsesurfaces show effects of WLs on DOD1st response surface shows “Low WL” = higher DOD(range of 3.0 to 4.5 mg/L)2nd response surface shows “High WL” = lower DOD(range of 1.5 to 2.8 mg/L)
  • 18. Data-Driven model’s accuracy, Cooper R. • Mixing - Tides, Flows from 3 Rivers • Weather (T, P Dew Point) • Point Discharge Wastewater Treatment Plants • Non-Point Discharges - rainfall, 50% overbank storage Measured Neural Network BRANCH/BLTM 10 32 9 30 28 Dissolved oxygen (mg/L) 8 Water temperature (degree Celsius) 26 Temperature 7 24 6 22 5 20 4 18 Dissolved oxygen 3 16 8/21/93 0:30 8/22/93 0:30 8/23/93 0:30 8/24/93 0:30 Date and time
  • 19. Beaufort RiverEstuaryComplex tidal system>9 foot tide rangeNet flow to the northModel developed forTMDL and NPDES permitsModel simulates 3.5 yearsof historical conditions
  • 20. Decision Support Systems make “what-ifs”easy for Beaufort River TMDL
  • 21. Savannah Harbor deepening  Model hydrodynamics  How far does salinity intrude when Harbor is deepened?  What happens when fresh water flows are low?
  • 22. Accuracy insights: EFDC vs. ANN model for Savannah River, GA Salinity, Practical Salinity Streamflow (cfs) EFDC R2=0.10 M2M R2=0.90 Units EFDC unable toSource: Conrads, P., and Greenfield, J., (2008) predict peaks
  • 23. Simulate reduced freshwater flows withEFDC and ANN model and compare EFDC R2=0.10 Salinity, Practical Salinity M2M R2=0.90 Streamflow (cfs) UnitsSource: Conrads, P., and Greenfield, J., (2008)
  • 24. Summary for NPS Estuary Modeling Stormwater and tidal effects (as well as point source impacts) can be quantified using Data Mining techniques 3D visualization gives valuable insight into process physics of the system Data Mining can be used with traditional approaches to minimize errors in load estimates from NPS
  • 25. QuestionsContact:John B. CookAdvanced Data Mining Intl; Greenville, SCJohn.cook@advdmi.com843.513.2130www.advdmi.com