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Fig. 4. Measurements

Fig. 4. Measurements. Fig. 5. Example Measurement Error. Errors are roughly normally distributed about a mean of zero and standard deviation of 15 cm for a given image at 50 m pixel resolution (~140,000 pixels). Fig. 7. Fig. 8. Results-Depth. Fig. 9. Results-Depth. Without EnKF

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Fig. 4. Measurements

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  1. Fig. 4. Measurements

  2. Fig. 5. Example Measurement Error Errors are roughly normally distributed about a mean of zero and standard deviation of 15 cm for a given image at 50 m pixel resolution (~140,000 pixels)

  3. Fig. 7.

  4. Fig. 8. Results-Depth

  5. Fig. 9. Results-Depth • Without EnKF • RMSE = 26.6 cm • 5.4% relative error • With EnKF • RMSE = 7.7 cm • 1.8% relative error

  6. Fig. 10. Results-Depth

  7. Fig. 11. Results-Depth • Without observations • R2=0.912 • With observations • R2=0.992

  8. Fig. 8. Results-Discharge

  9. Fig. 12. Results-Discharge • Without EnKF • RMSE = 101.5 m3/s • 8.8% relative error • With EnKF • RMSE = 29.7 m3/s • 3.2% relative error

  10. Fig. 13. Results-Discharge

  11. Fig. 14. Results-Discharge • Without observations • R2=0.913 • With observations • R2=0.992

  12. Future Research Needs • Implementation that includes floodplain flow • Model formulation error representation • Model parameters error representation (Manning’s n, channel width, elevation) • Model forcing error representation (temperature) • Seasonal performance

  13. Future Research Needs (cont.) • Temporal and spatial sampling sensitivity analysis • Implementation in different hydrologic environments (Amazon, Arctic, arid regions) • Derivation of hydraulic model parameters (channel width, bed elevation, channel location) from remotely-sensed data • Inclusion of tributaries

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