A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution
Estimation of extreme event distributions and depth-duration-frequency (DDF) curves is achieved at any target site by repeated sampling among all available raingauge data in the surrounding area. The estimate is computed over a gridded domain in Northern Italy, using precipitation time series from 1...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2014-03-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/18/981/2014/hess-18-981-2014.pdf |
| Summary: | Estimation of extreme event distributions and depth-duration-frequency
(DDF) curves is achieved at any target site by repeated sampling among
all available raingauge data in the surrounding area. The estimate
is computed over a gridded domain in Northern Italy, using precipitation
time series from 1929 to 2011, including data from historical analog
stations and from the present-day automatic observational network.
The presented local regionalisation naturally overcomes
traditional station-point methods, with their demand
of long historical series and their sensitivity to very rare events occurring
at very few stations, possibly causing unrealistic spatial gradients
in DDF relations. At the same time, the presented approach allows
for spatial dependence, necessary in a geographical domain such as
Lombardy, complex for both its topography and its climatology.
The bootstrap technique enables evaluating uncertainty maps for all
estimated parameters and for rainfall depths at assigned return periods. |
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| ISSN: | 1027-5606 1607-7938 |