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| Titel |
Large-scale groundwater modeling using global datasets: a test case for the Rhine-Meuse basin |
| VerfasserIn |
E. H. Sutanudjaja, L. P. H. Beek, S. M. Jong, F. C. Geer, M. F. P. Bierkens |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 15, no. 9 ; Nr. 15, no. 9 (2011-09-15), S.2913-2935 |
| Datensatznummer |
250012962
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| Publikation (Nr.) |
 copernicus.org/hess-15-2913-2011.pdf |
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| Zusammenfassung |
| The current generation of large-scale hydrological models does not include a groundwater
flow component. Large-scale groundwater models, involving aquifers and basins of multiple
countries, are still rare mainly due to a lack of hydro-geological data which are
usually only available in developed countries. In this study, we propose a
novel approach to construct large-scale groundwater models by using global
datasets that are readily available. As the test-bed, we use the combined
Rhine-Meuse basin that contains groundwater head data used to verify the
model output. We start by building a distributed land surface model (30
arc-second resolution) to estimate groundwater recharge and river discharge.
Subsequently, a MODFLOW transient groundwater model is built and forced by
the recharge and surface water levels calculated by the land surface model.
Results are promising despite the fact that we still use an offline procedure to couple the land surface and MODFLOW
groundwater models (i.e. the simulations of both models are separately performed).
The simulated river discharges compare well to the observations. Moreover,
based on our sensitivity analysis, in which we run several groundwater model
scenarios with various hydro-geological parameter settings, we observe that
the model can reasonably well reproduce the observed groundwater head time series. However, we note that there are still some limitations in the current
approach, specifically because the offline-coupling technique
simplifies the dynamic feedbacks between surface water levels and groundwater
heads, and between soil moisture states and groundwater heads. Also the
current sensitivity analysis ignores the uncertainty of the land surface
model output. Despite these limitations, we argue that the results of the
current model show a promise for large-scale groundwater modeling practices,
including for data-poor environments and at the global scale. |
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