 |
| Titel |
Performance evaluation of groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs |
| VerfasserIn |
P. A. Marker, N. Foged, X. He, A. V. Christiansen, J. C. Refsgaard, E. Auken, P. Bauer-Gottwein |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 9 ; Nr. 19, no. 9 (2015-09-15), S.3875-3890 |
| Datensatznummer |
250120808
|
| Publikation (Nr.) |
 copernicus.org/hess-19-3875-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| Large-scale hydrological models are important decision support tools in
water resources management. The largest source of uncertainty in such models
is the hydrostratigraphic model. Geometry and configuration of
hydrogeological units are often poorly determined from hydrogeological data
alone. Due to sparse sampling in space, lithological borehole logs may
overlook structures that are important for groundwater flow at larger
scales. Good spatial coverage along with high spatial resolution makes
airborne electromagnetic (AEM) data valuable for the structural input to
large-scale groundwater models. We present a novel method to automatically
integrate large AEM data sets and lithological information into large-scale
hydrological models. Clay-fraction maps are produced by translating
geophysical resistivity into clay-fraction values using lithological
borehole information. Voxel models of electrical resistivity and clay
fraction are classified into hydrostratigraphic zones using k-means
clustering. Hydraulic conductivity values of the zones are estimated by
hydrological calibration using hydraulic head and stream discharge
observations. The method is applied to a Danish case study. Benchmarking
hydrological performance by comparison of performance statistics from
comparable hydrological models, the cluster model performed competitively.
Calibrations of 11 hydrostratigraphic cluster models with 1–11 hydraulic
conductivity zones showed improved hydrological performance with an increasing
number of clusters. Beyond the 5-cluster model hydrological performance did
not improve. Due to reproducibility and possibility of method
standardization and automation, we believe that hydrostratigraphic model
generation with the proposed method has important prospects for groundwater
models used in water resources management. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|