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Comparison of rainfall generators with regionalisation for the estimation of rainfall erosivity at ungauged sites
ID
Pidoto, Ross
(
Author
),
ID
Bezak, Nejc
(
Author
),
ID
Müller-Thomy, Hannes
(
Author
),
ID
Shehu, Bora
(
Author
),
ID
Callau-Beyer, Ana Claudia
(
Author
),
ID
Zabret, Katarina
(
Author
),
ID
Haberlandt, Uwe
(
Author
)
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https://esurf.copernicus.org/articles/10/851/2022/
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Abstract
Rainfall erosivity values are required for soil erosion prediction. To calculate the mean annual rainfall erosivity (R), long-term high-resolution observed rainfall data are required, which are often not available. To overcome the issue of limited data availability in space and time, four methods were employed and evaluated: direct regionalisation of R, regionalisation of 5 min rainfall, disaggregation of daily rainfall into 5 min time steps, and a regionalised stochastic rainfall model. The impact of station density is considered for each of the methods. The study is carried out using 159 recording and 150 non-recording (daily) rainfall stations in and around the federal state of Lower Saxony, Germany. In addition, the minimum record length necessary to adequately estimate R was investigated. Results show that the direct regionalisation of mean annual erosivity is best in terms of both relative bias and relative root mean square error (RMSE), followed by the regionalisation of the 5 min rainfall data, which yields better results than the rainfall generation models, namely an alternating renewal model (ARM) and a multiplicative cascade model. However, a key advantage of using regionalised rainfall models is the ability to generate time series that can be used for the estimation of the erosive event characteristics. This is not possible if regionalising only R. Using the stochastic ARM, it was assessed that more than 60 years of data are needed in most cases to reach a stable estimate of annual rainfall erosivity. Moreover, the temporal resolution of measuring devices was found to have a significant effect on R, with coarser temporal resolution leading to a higher relative bias.
Language:
English
Keywords:
rainfall generator
,
rainfall erosivity
,
ungauged site
,
regionalization
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FGG - Faculty of Civil and Geodetic Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2022
Number of pages:
Str. 851-863
Numbering:
Vol. 10, iss. 4
PID:
20.500.12556/RUL-140933
UDC:
556.1
ISSN on article:
2196-632X
DOI:
10.5194/esurf-10-851-2022
COBISS.SI-ID:
120255235
Publication date in RUL:
21.09.2022
Views:
1638
Downloads:
144
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Record is a part of a journal
Title:
Earth surface dynamics
Shortened title:
Earth surf. dyn.
Publisher:
Copernicus Publications, European Geosciences Union
ISSN:
2196-632X
COBISS.SI-ID:
522780953
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
generator padavin
,
erozivnost padavin
,
nemerjene lokacije
,
regionalizacija
Projects
Funder:
Slovenia
Name:
Stochastic rainfall models for rainfall erosivity evaluation
Funder:
Germany
Name:
Stochastic rainfall models for rainfall erosivity evaluation
Funder:
ARRS - Slovenian Research Agency
Project number:
P2-0180
Name:
Vodarstvo in geotehnika: orodja in metode za analize in simulacije procesov ter razvoj tehnologij
Funder:
DFG
Funding programme:
Research Fellowship
Project number:
MU 4257/1-1
Funder:
BMBF - Germany, Federal Ministry of Education and Research
Name:
Validation of precipitation reanalysis products for rainfall-runoff modelling in Slovenia
Acronym:
PRE-PROMISE
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