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Long-Term Salinity Prediction with Uncertainty Analysis: Application for Colorado River Above Glenwood Springs, CO

Long-Term Salinity Prediction with Uncertainty Analysis: Application for Colorado River Above Glenwood Springs, CO. 2 nd Federal Interagency Hydrologic Modeling Conf. James Prairie

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Long-Term Salinity Prediction with Uncertainty Analysis: Application for Colorado River Above Glenwood Springs, CO

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  1. Long-Term Salinity Prediction with Uncertainty Analysis:Application for Colorado River Above Glenwood Springs, CO 2nd Federal Interagency Hydrologic Modeling Conf. James Prairie Water Resources Division, Civil, Architectural, and Environmental Engineering Department, and U.S. Bureau of Reclamation, University of Colorado, Boulder Balaji Rajagopalan Water Resources Division, Civil, Architectural, and Environmental Engineering Department, University of Colorado, Boulder Terry Fulp U.S. Bureau of Reclamation, University of Colorado, Boulder

  2. Motivation • Colorado River Basin • arid and semi-arid climates • irrigation demands for agriculture • “Law of the River” • Mexico Treaty Minute No. 242 • Colorado River Basin Salinity Control Act of 1974 • Salinity Control Forum

  3. Existing Salt Model Over-Prediction

  4. Stochastic Simulation • Simulate from the conditional probability function • joint over the marginal densities

  5. Parametric PAR(1) • Periodic Auto Regressive model (PAR) • developed a lag(1) model • Stochastic Analysis, Modeling, and Simulation (SAMS) (Salas, 1992) • Data must fit a Gaussian distribution • Expected to preserve • mean, standard deviation, lag(1) correlation • skew dependant on transformation • gaussian probability density function

  6. Modified Nonparametric K-NN Natural Flow Model • Improvement on traditional K-NN • keeps modeling simple yet creates values not seen in the historic record • perturbs the historic record within its representative neighborhood • allows extrapolation beyond sample

  7. e * t y * t y t-1 Residual Resampling yt = yt* + et*

  8. Conditional PDF June May

  9. Statistical Nonparametric Model for Natural Salt Estimation • Based on calculated natural flow and natural salt mass from water year 1941-85 • calculated natural flow = observed historic flow + total depletions • calculated natural salt = observed historic salt - salt added from agriculture + salt removed with exports • Nonparametric regression (local regression) • natural salt = f (natural flow) • Residual resampling

  10. Comparison with Observed Historic Salt

  11. Comparison With Calculated Natural Salt

  12. CRSS Simulation Model for Historic Validation Natural flow 1906-95 Natural salt 1941-95 Constant salinity pickup 137,000 tons/year Exports removed @ 100 mg/L Compare results to observed historic for validation

  13. Annual Model With Resampling • Based on 1941-1995 natural flow • 1941-1995 annual salt model • Simulates 1941-1995 • Historic Flow and Concentration

  14. Modified and Existing CRSS ComparisonHistoric Salt Mass • Based on 1906-1995 natural flows • 1941-1995 monthly salt models • Simulates 1941-1995

  15. Policy AnalysisHistoric Simulation > 650,000 tons salt > 350 mg/L salt concentration

  16. Stochastic Planning Runs Projected Future Flow and Salt Mass • Passing gauge 09072500 • Based on 1906-1995 natural flows • 1941-1995 monthly salt models • Simulating 2002 to 2062

  17. Conclusion • Developed a modeling framework for long-term salinity with uncertainty in the Colorado River • modified nonparametric K-NN natural flow model • statistical nonparametric natural salt model • validation of historic record • demonstrated future projection

  18. Acknowledgements • Dr. Balaji Rajagopalan, Dr. Terry Fulp, Dr. Edith Zagona for advising and support • Upper Colorado Regional Office of the US Bureau of Reclamation, in particular Dave Trueman for funding and support • CADSWES personnel for use of their knowledge and computing facilities

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