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| Titel |
Using the SWAT model to improve process descriptions and define hydrologic partitioning in South Korea |
| VerfasserIn |
C. L. Shope, G. R. Maharjan, J. Tenhunen, B. Seo, K. Kim, J. Riley, S. Arnhold, T. Koellner, Y. S. Ok, S. Peiffer, B. Kim, J.-H. Park, B. Huwe |
| 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 ; 18, no. 2 ; Nr. 18, no. 2 (2014-02-12), S.539-557 |
| Datensatznummer |
250120276
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| Publikation (Nr.) |
 copernicus.org/hess-18-539-2014.pdf |
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| Zusammenfassung |
| Watershed-scale modeling can be a valuable tool to aid in quantification of
water quality and yield; however, several challenges remain. In many
watersheds, it is difficult to adequately quantify hydrologic partitioning.
Data scarcity is prevalent, accuracy of spatially distributed meteorology is
difficult to quantify, forest encroachment and land use issues are common,
and surface water and groundwater abstractions substantially modify
watershed-based processes. Our objective is to assess the capability of the
Soil and Water Assessment Tool (SWAT) model to capture event-based and long-term monsoonal rainfall–runoff
processes in complex mountainous terrain. To accomplish this, we developed a
unique quality-control, gap-filling algorithm for interpolation of high-frequency meteorological data. We used a novel multi-location,
multi-optimization calibration technique to improve estimations of
catchment-wide hydrologic partitioning. The interdisciplinary model was
calibrated to a unique combination of statistical, hydrologic, and plant
growth metrics. Our results indicate scale-dependent sensitivity of
hydrologic partitioning and substantial influence of engineered features.
The addition of hydrologic and plant growth objective functions identified
the importance of culverts in catchment-wide flow distribution. While this
study shows the challenges of applying the SWAT model to complex terrain and
extreme environments; by incorporating anthropogenic features into modeling
scenarios, we can enhance our understanding of the hydroecological impact. |
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