Model structural uncertainty quantification and hydrologic parameter and prediction error analysis using airborne electromagnetic data
- Authors:
- Abstract:
- Model structure, or the spatial arrangement of subsurface lithological units, is fundamental to the hydrological behavior of Earth systems. Knowledge of geological model structure is critically important in order to make informed hydrological predictions and management decisions. Model structure is never perfectly known, however, and incorrect assumptions can be a significant source of error when making model predictions. We describe a systematic approach for quantifying model structural uncertainty that is based on the integration of sparse borehole observations and large-scale airborne electromagnetic (AEM) data. Our estimates of model structural uncertainty follow a Bayesian framework that accounts for both the uncertainties in geophysical parameter estimates given AEM data, and the uncertainties in the relationship between lithology and geophysical parameters. Using geostatistical sequential indicator simulation, we produce many realizations of model structure that are consistent with observed datasets and prior knowledge. Given estimates of model structural uncertainty, we incorporate hydrologic observations to evaluate the errors in hydrologic parameter or prediction errors that occur when assumptions about model structure are imperfect.
- Type:
- Conference abstract
- Language:
- English
- Main Research Area:
- Science/technology
- Review type:
- Undetermined
- Conference:
- SAGEEP 2017
- Submission year:
- 2017
- Scientific Level:
- Scientific
- ID:
- 2354981519
0000-0002-9251-2315