DOI: 10.5194/hess-21-1321-2017
Scopus记录号: 2-s2.0-85014521876
论文题名: Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy
作者: Christensen N ; K ; , Ferre T ; P ; A ; , Fiandaca G ; , Christensen S
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 2 起始页码: 1321
结束页码: 1337
语种: 英语
Scopus关键词: Electric discharges
; Forecasting
; Geophysics
; Groundwater
; Hydraulic conductivity
; Magnetometers
; Airborne electromagnetic
; Conductivity distributions
; Depositional environment
; Efficient construction
; Geophysical modeling
; Petrophysical relationship
; Predictive capabilities
; Smoothness constraints
; Recharging (underground waters)
; airborne survey
; calibration
; data quality
; electromagnetic survey
; groundwater resource
; hydraulic conductivity
; hydrological modeling
; prediction
; recharge
; three-dimensional modeling
英文摘要: We present a workflow for efficient construction and calibration of large-scale groundwater models that includes the integration of airborne electromagnetic (AEM) data and hydrological data. In the first step, the AEM data are inverted to form a 3-D geophysical model. In the second step, the 3-D geophysical model is translated, using a spatially dependent petrophysical relationship, to form a 3-D hydraulic conductivity distribution. The geophysical models and the hydrological data are used to estimate spatially distributed petrophysical shape factors. The shape factors primarily work as translators between resistivity and hydraulic conductivity, but they can also compensate for structural defects in the geophysical model. The method is demonstrated for a synthetic case study with sharp transitions among various types of deposits. Besides demonstrating the methodology, we demonstrate the importance of using geophysical regularization constraints that conform well to the depositional environment. This is done by inverting the AEM data using either smoothness (smooth) constraints or minimum gradient support (sharp) constraints, where the use of sharp constraints conforms best to the environment. The dependency on AEM data quality is also tested by inverting the geophysical model using data corrupted with four different levels of background noise. Subsequently, the geophysical models are used to construct competing groundwater models for which the shape factors are calibrated. The performance of each groundwater model is tested with respect to four types of prediction that are beyond the calibration base: a pumping well's recharge area and groundwater age, respectively, are predicted by applying the same stress as for the hydrologic model calibration; and head and stream discharge are predicted for a different stress situation. As expected, in this case the predictive capability of a groundwater model is better when it is based on a sharp geophysical model instead of a smoothness constraint. This is true for predictions of recharge area, head change, and stream discharge, while we find no improvement for prediction of groundwater age. Furthermore, we show that the model prediction accuracy improves with AEM data quality for predictions of recharge area, head change, and stream discharge, while there appears to be no accuracy improvement for the prediction of groundwater age. © Author(s) 2017. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79238
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Geoscience, Aarhus University, Aarhus, Denmark; Department of Hydrology and Water Resources, University of Arizona, Tucson, United States
Recommended Citation:
Christensen N,K,, Ferre T,et al. Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy[J]. Hydrology and Earth System Sciences,2017-01-01,21(2)