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Colin Kikuchi, MSc Student University of Arizona Department of Hydrology and Water Resources

Improving measurement selection: Multi-model analysis with discriminatory data collection (MMA-DDC). Colin Kikuchi, MSc Student University of Arizona Department of Hydrology and Water Resources 2/1/2011. The problem….

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Colin Kikuchi, MSc Student University of Arizona Department of Hydrology and Water Resources

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  1. Improving measurement selection:Multi-model analysis with discriminatory data collection (MMA-DDC) Colin Kikuchi, MSc Student University of Arizona Department of Hydrology and Water Resources 2/1/2011

  2. The problem… • General: How can we optimize data collection to most efficiently answer a scientific question of interest? • Specifically: For a one-dimensional solute transport experiment • What are the hydraulic and transport properties of the porous medium? Steady state flow -Hydraulic conductivity? -Retardation coefficient? -Dispersivity? Point injection (of solute) Measure solute concentration at location x Not so good. Good.

  3. Method: MMA-DDC • For five proposed “models” (distinct hydraulic /transport properties), compute dissimilarity index, DI Sampling location, SL (a) x=80 cm (b) x=50 cm (c) x=10 cm

  4. Results • Assume sampling at regular time intervals… where should we sample? Does MMA-DDC work? Yes, for this case. What about… -Competing model structures? -Boundary/initial conditions?

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