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Effect of different transport observations on inverse modeling results: case study of a long-term groundwater tracer test monitored at high resolution |
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| Authors: | Ehsan Rasa Laura Foglia Douglas M Mackay Kate M Scow |
| Institution: | 1. Department of Civil and Environmental Engineering, University of California-Davis, One Shields Avenue, Davis, CA, 95616, USA 2. Geosyntec Consultants, 1111 Broadway, 6th floor, Oakland, CA, 94607, USA 3. Department of Land, Air, and Water Resources, University of California-Davis, One Shields Avenue, Davis, CA, 95616, USA 4. Institute of Applied Geosciences, Technical University Darmstadt, 64287, Darmstadt, Germany |
| Abstract: | Conservative tracer experiments can provide information useful for characterizing various subsurface transport properties. This study examines the effectiveness of three different types of transport observations for sensitivity analysis and parameter estimation of a three-dimensional site-specific groundwater flow and transport model: conservative tracer breakthrough curves (BTCs), first temporal moments of BTCs (m 1), and tracer cumulative mass discharge (M d) through control planes combined with hydraulic head observations (h). High-resolution data obtained from a 410-day controlled field experiment at Vandenberg Air Force Base, California (USA), have been used. In this experiment, bromide was injected to create two adjacent plumes monitored at six different transects (perpendicular to groundwater flow) with a total of 162 monitoring wells. A total of 133 different observations of transient hydraulic head, 1,158 of BTC concentration, 23 of first moment, and 36 of mass discharge were used for sensitivity analysis and parameter estimation of nine flow and transport parameters. The importance of each group of transport observations in estimating these parameters was evaluated using sensitivity analysis, and five out of nine parameters were calibrated against these data. Results showed the advantages of using temporal moment of conservative tracer BTCs and mass discharge as observations for inverse modeling. |
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