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CVEN 689 Instructor: Dr. Francisco Olivera

Estimating Salt Concentration at Ungaged Locations from Parameters derived using GIS Ganesh Krishnamurthy Water Resources Engineering. CVEN 689 Instructor: Dr. Francisco Olivera. Objectives. To become proficient in ArcView 3.2

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CVEN 689 Instructor: Dr. Francisco Olivera

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  1. Estimating Salt Concentration at Ungaged Locations from Parameters derived using GIS Ganesh Krishnamurthy Water Resources Engineering CVEN 689Instructor: Dr. Francisco Olivera

  2. Objectives • To become proficient in ArcView 3.2 • To prepare an empirical model to predict salt concentrations at ungaged locations using GIS

  3. Why is this Important? • Though water is diverted, the quality is not considered • Diversions often occur from ungaged locations where the salt concentration is unknown

  4. Datasets used • Grid: USGS 1-Degree DEM (1:250,000) • Grid: U.S. Curve Number • Grid: U.S. Mean Annual Precipitation • Lines: EPA RF3 and NHD Channel Lines (1:100,000) • Points:USGS Control Point Locations • Naturalized Salt Data at all gaging stations in the Brazos River Basin

  5. WRAP Parameters and Tools Menu

  6. Correcting the Stream Network Corrected Stream network without loops and braids Stream network with loops and braids

  7. Burning the Stream Network BRAZOS DEM STREAM NETWORK BURNED DEM

  8. Making the Flow Direction and the Flow Accumulation Grids FILLED DEM FLOW DIRECTION FLOW ACCUMULATION

  9. The CN and the Mean Annual Precipitation Grids The CN Grid The Mean Precipitation Grid

  10. Stream Network Questions??? Control point locations will match exactly to channel grid cells in the flow accumulation grid. The outlet locations in the flow accumulation grid are correctly defined. Downstream control points can be identified.

  11. Attribute Table

  12. Control Point Parameters

  13. Assumptions

  14. Empirical Equations

  15. Models • Model 1- uses the Area Ratio Parameter • Model 2- uses the Area-Precipitation Ratio Parameter • Model 3- uses the Area-Precipitation-CN Ratio Parameter • All three models have been applied to the following pairs of control points in the Brazos Basin for the years 1972-1976 : • CPID 8085500, CPID 8087300 • CPID 8082000, CPID 8082500 • CPID 8087300, CPID 8088000

  16. Results and Discussion R2= 0.97

  17. Results and Discussion R2= 0.82

  18. Results and Discussion R2= 0.71

  19. Results and Discussion R2= 0.67

  20. Results and Discussion • The r2 values obtained for the different models range between 0.48 and 0.91 for the period 1972-1977. • The closest fit is observed for the year 1977 for all the three models with an average r2 value of 0.97 for all five years. • The average of the r2 values for the 6 years for all three models is 0.69

  21. Conclusions • The deviations in the observed values and the predicted values can be attributed to : • parameters that affect salinity other than the ones considered in the assumption • Computational Errors in estimating naturalized salt concentrations at gaged locations • The model uses a monthly time scale, whereas sub monthly events like thunderstorms are not considered

  22. Future Work • To identify the “missing” parameters to improve the relation between the observed and the predicted values • To test run the model in WRAP for the Brazos river basin.

  23. QUESTIONS

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