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| Titel |
Prediction, time variance, and classification of hydraulic response to recharge in two karst aquifers |
| VerfasserIn |
A. J. Long, B. J. Mahler |
| 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 ; 17, no. 1 ; Nr. 17, no. 1 (2013-01-24), S.281-294 |
| Datensatznummer |
250017690
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| Publikation (Nr.) |
 copernicus.org/hess-17-281-2013.pdf |
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| Zusammenfassung |
| Many karst aquifers are rapidly filled and depleted and therefore are likely
to be susceptible to changes in short-term climate variability. Here we
explore methods that could be applied to model site-specific hydraulic
responses, with the intent of simulating these responses to different
climate scenarios from high-resolution climate models. We compare hydraulic
responses (spring flow, groundwater level, stream base flow, and cave drip)
at several sites in two karst aquifers: the Edwards aquifer (Texas, USA) and
the Madison aquifer (South Dakota, USA). A lumped-parameter model simulates
nonlinear soil moisture changes for estimation of recharge, and a
time-variant convolution model simulates the aquifer response to this
recharge. Model fit to data is 2.4% better for calibration periods than
for validation periods according to the Nash–Sutcliffe coefficient of
efficiency, which ranges from 0.53 to 0.94 for validation periods. We use
metrics that describe the shapes of the impulse-response functions (IRFs)
obtained from convolution modeling to make comparisons in the distribution
of response times among sites and between aquifers. Time-variant IRFs were
applied to 62% of the sites. Principal component analysis (PCA) of
metrics describing the shapes of the IRFs indicates three principal
components that together account for 84% of the variability in IRF shape:
the first is related to IRF skewness and temporal spread and accounts for
51% of the variability; the second and third largely are related to
time-variant properties and together account for 33% of the variability.
Sites with IRFs that dominantly comprise exponential curves are separated
geographically from those dominantly comprising lognormal curves in both
aquifers as a result of spatial heterogeneity. The use of multiple IRF
metrics in PCA is a novel method to characterize, compare, and classify the
way in which different sites and aquifers respond to recharge. As
convolution models are developed for additional aquifers, they could
contribute to an IRF database and a general classification system for karst
aquifers. |
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