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| Titel |
Evaluating topographic wetness indices across central New York agricultural landscapes |
| VerfasserIn |
B. P. Buchanan, M. Fleming, R. L. Schneider, B. K. Richards, J. Archibald, Z. Qiu, M. T. Walter |
| 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. 8 ; Nr. 18, no. 8 (2014-08-28), S.3279-3299 |
| Datensatznummer |
250120451
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| Publikation (Nr.) |
 copernicus.org/hess-18-3279-2014.pdf |
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| Zusammenfassung |
| Accurately predicting soil moisture patterns in the landscape is a persistent
challenge. In humid regions, topographic wetness indices (TWIs) are widely
used to approximate relative soil moisture patterns. However, there are many
ways to calculate TWIs and very few field studies have evaluated the
different approaches – especially in the US. We calculated TWIs using over
400 unique formulations that considered different digital elevation model
(DEM) resolutions (cell size), vertical precision of DEM, flow direction and
slope algorithms, smoothing via low-pass filtering, and the inclusion of
relevant soil properties. We correlated each TWI with observed patterns of
soil moisture at five agricultural fields in central NY, USA, with each field
visited five to eight times between August and November 2012. Using a mixed
effects modeling approach, we were able to identify optimal TWI formulations
applicable to moderate relief agricultural settings that may provide guidance
for practitioners and future studies. Overall, TWIs were moderately well
correlated with observed soil moisture patterns; in the best case the
relationship between TWI and soil moisture had an average R2 and Spearman
correlation value of 0.61 and 0.78, respectively. In all cases, fine-scale
(3 m) lidar-derived DEMs worked better than USGS 10 m DEMs and, in general,
including soil properties improved correlations. |
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