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| Titel |
Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan |
| VerfasserIn |
Ting-Yin Huang, Ssu-Yao Yang, Chyan-Deng Jan |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250140942
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| Publikation (Nr.) |
 EGU/EGU2017-4397.pdf |
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| Zusammenfassung |
| Soil erosion is a natural process on hillslopes that threats people’s life and properties, having
a considerable environmental and economic implications for soil degradation, agricultural
activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss
Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall
intensity (I30), is widely used as an indicator to measure the potential risks of soil loss
caused by rainfall at a regional scale. This R factor can represent the detachment
and entrainment involved in climate conditions on hillslopes, but lack of 30-min
rainfall intensity data usually lead to apply this factor more difficult in many regions.
In recent years, fixed-interval, hourly rainfall data is readily available and widely
used due to the development of automatic weather stations. Here we assess the
estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data,
and hourly rainfall data obtained from Taipei weather station during 2004 to 2010.
Results show that there is a strong correlation among R-factors estimated from
different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g.,
1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity
(ratio of values estimated from the resolution lower than 30-min rainfall data to
those estimated from 60-min and hourly rainfall data, respectively) range from
1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as
the time resolution increasing from 30-min to 1-min. This paper provides useful
information on estimating R-factor when hourly rainfall data is only available. |
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