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WATER RESOURCES RESEARCH, VOL. 40, W12411, doi:10.1029/2004WR003313, 2004

A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system

Claire R. Tiedeman

U.S. Geological Survey, Menlo Park, California, USA


D. Matthew Ely

U.S. Geological Survey, Tacoma, Washington, USA


Mary C. Hill

U.S. Geological Survey, Boulder, Colorado, USA


Grady M. O'Brien


Abstract

We develop a new observation-prediction (OPR) statistic for evaluating the importance of system state observations to model predictions. The OPR statistic measures the change in prediction uncertainty produced when an observation is added to or removed from an existing monitoring network, and it can be used to guide refinement and enhancement of the network. Prediction uncertainty is approximated using a first-order second-moment method. We apply the OPR statistic to a model of the Death Valley regional groundwater flow system (DVRFS) to evaluate the importance of existing and potential hydraulic head observations to predicted advective transport paths in the saturated zone underlying Yucca Mountain and underground testing areas on the Nevada Test Site. Important existing observations tend to be far from the predicted paths, and many unimportant observations are in areas of high observation density. These results can be used to select locations at which increased observation accuracy would be beneficial and locations that could be removed from the network. Important potential observations are mostly in areas of high hydraulic gradient far from the paths. Results for both existing and potential observations are related to the flow system dynamics and coarse parameter zonation in the DVRFS model. If system properties in different locations are as similar as the zonation assumes, then the OPR results illustrate a data collection opportunity whereby observations in distant, high-gradient areas can provide information about properties in flatter-gradient areas near the paths. If this similarity is suspect, then the analysis produces a different type of data collection opportunity involving testing of model assumptions critical to the OPR results.

Received 30 April 2004; accepted 20 September 2004; published 22 December 2004.

Keywords: advective transport; prediction uncertainty; sensitivities; system state observations.

Index Terms: 1829 Hydrology: Groundwater hydrology; 1832 Hydrology: Groundwater transport; 3210 Mathematical Geophysics: Modeling; 6309 Policy Sciences: Decision making under uncertainty.

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Citation: Tiedeman, C. R., D. M. Ely, M. C. Hill, and G. M. O'Brien (2004), A method for evaluating the importance of system state observations to model predictions, with application to the Death Valley regional groundwater flow system, Water Resour. Res., 40, W12411, doi:10.1029/2004WR003313.