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Quantification of vegetation and meteorological variables influencing the kinetic energy of raindrops
ID
Radulović, Lana
(
Author
),
ID
Zabret, Katarina
(
Author
),
ID
Šraj, Mojca
(
Author
)
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MD5: F8C17CD0B7CC5E27511FFCAC85C96F61
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https://www.sciencedirect.com/science/article/pii/S016819232500454X
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Abstract
The process of interception, whereby vegetation partitions rainfall, largely influences natural processes such as soil erosion. The kinetic energy of rainfall plays a crucial role in evaluating this impact. In this study, we measured rainfall characteristics using three disdrometers placed above and below vegetation, specifically under two distinct tree species (birch and pine) in an urban area in Ljubljana, Slovenia. The study period extends over two years, subdivided into a dry and a wet sub-period. The investigation encompasses the effects of vegetation characteristics, raindrops characteristics and meteorological variables on the kinetic energy of throughfall. Two methods, namely boosted regression trees and random forest, were used to evaluate the influence of vegetation and meteorological variables on raindrop characteristics and their kinetic energy. The results indicate that, in general, pine reduces the kinetic energy of raindrops to a much greater extent than birch, and that birch exerts a positive effect on the reduction of kinetic energy only during the leafed period. Both applied machine learning models confirmed that the amount of throughfall has the greatest influence on kinetic energy, regardless of vegetation type. Furthermore, rainfall intensity and median-volume drop diameter exhibited a greater influence in the case of pine compared to the birch tree. Additionally, the findings indicate that the influence of the event duration on kinetic energy of throughfall differs depending on the presence of foliage on the tree canopy.
Language:
English
Keywords:
rainfall interception
,
throughfall
,
kinetic energy
,
urban trees
,
machine learning
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:
2025
Number of pages:
11 str.
Numbering:
Vol. 375, art. 110835
PID:
20.500.12556/RUL-182671
UDC:
556
ISSN on article:
0168-1923
DOI:
10.1016/j.agrformet.2025.110835
COBISS.SI-ID:
249016067
Publication date in RUL:
20.05.2026
Views:
278
Downloads:
298
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Record is a part of a journal
Title:
Agricultural and forest meteorology
Shortened title:
Agric. for. meteorol.
Publisher:
Elsevier
ISSN:
0168-1923
COBISS.SI-ID:
5051143
Licences
License:
CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:
http://creativecommons.org/licenses/by-nc/4.0/
Description:
A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
Secondary language
Language:
Slovenian
Keywords:
prestrezanje padavin
,
prepuščene padavine
,
kinetična energija
,
urbana drevesa
,
strojno učenje
Projects
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
J2-4489
Name:
Vrednotenje vpliva prestrezanja padavin na erozijo tal
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
N2-0313
Name:
Lokalni vplivi na površinski odtok
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P2-0180
Name:
Vodarstvo in geotehnika: orodja in metode za analize in simulacije procesov ter razvoj tehnologij
Funder:
EC - European Commission
Funding programme:
HE
Project number:
101112738
Name:
Evidence and Solutions for improving SPONGE Functioning at LandSCAPE Scale in European Catchments for increased Resilience of Communities against Hydrometeorological Extreme Events
Acronym:
SpongeScapes
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