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| Titel |
Accurate rainfall erosivity estimation from daily precipitation records in the Ebro basin (NE Spain) |
| VerfasserIn |
M. Angulo-Martínez, M. López-Vicente, S. M. Vicente-Serrano, S. Beguería |
| Konferenz |
EGU General Assembly 2009
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 11 (2009) |
| Datensatznummer |
250021731
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| Zusammenfassung |
| Precipitation is one of the major causal factors of soil erosion. Its direct impact in
the soil and the runoff generated are involved in the concept of rainfall erosivity.
Rainfall erosivity is a function of the storm kinetic energy and the raindrop size
distribution. Accurate estimation of rainfall erosivity, such as the RUSLE R factor,
need sub-hourly rainfall records which are hardly available with a good spatial and
temporal coverage. The use of daily precipitation records would allow a better
knowledge of rainfall erosivity. In this study rainfall erosivity was estimated from daily
precipitation records and precipitation indices and compared with the RUSLE R
factor computed by using 15-minutes rainfall data. Several goodness-of-fit and error
statistics were used to determine the reliability of the estimations using daily data.
Two approaches were used for estimating the annual rainfall erosivity from daily
data:
First, daily precipitation records were transformed into daily rainfall erosivity
by means of a seasonally-adjusted exponential relationship. The seasonal spatial
distribution of the coefficients was coherent with the type of rainfall in the study
area.
Second, the relationship between the annual rainfall erosivity and several precipitation
intensity statistics computed from daily data series was explored by means of linear
regression. The annual erosivity was highly related to the five maximum precipitation events
occurred during the year, plus the maximum wet spell duration and the ratio between the
average wet and dry spells duration.
Both methods yielded good estimations of the RUSLE R factor, providing an accurate
means of predicting rainfall erosivity in the region. An in-depth comparison of both
approaches was made considering several aspects besides the goodness-of-fit statistics. |
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