001     203401
005     20210129220352.0
024 7 _ |2 doi
|a 10.1016/j.jhydrol.2015.06.031
024 7 _ |2 ISSN
|a 0022-1694
024 7 _ |2 ISSN
|a 1879-2707
024 7 _ |2 WOS
|a WOS:000358968200017
037 _ _ |a FZJ-2015-05344
041 _ _ |a English
082 _ _ |a 690
100 1 _ |0 P:(DE-HGF)0
|a Peñuela, Andrés
|b 0
|e Corresponding author
245 _ _ |a How do slope and surface roughness affect plot-scale overland flow connectivity?
260 _ _ |a Amsterdam [u.a.]
|b Elsevier
|c 2015
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1440406200_27025
|2 PUB:(DE-HGF)
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|0 0
|2 EndNote
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a article
|2 DRIVER
520 _ _ |a Surface micro-topography and slope drive the hydrological response of plots through the gradual filling of depressions as well as the establishment of hydraulic connections between overflowing depressions. Therefore, quantifying and understanding the effects of surface roughness and slope on plot-scale overland flow connectivity is crucial to improve current hydrological modeling and runoff prediction. This study aimed at establishing predictive equations relating structural and functional connectivity indicators in function of slope and roughness. The Relative Surface Connection function (RSCf) was used as a functional connectivity indicator was applied. Three characteristic parameters were defined to characterize the RSCf: the surface initially connected to the outlet, the connectivity threshold and the maximum depression storage (DSmax). Gaussian surface elevation fields (6 m × 6 m) were generated for a range of slopes and roughnesses (sill σ and range R of the variogram). A full factorial of 6 slopes (0–15%), 6 values of R (50–400 mm) and 6 values of σ (2–40 mm) was considered, and the RSCf calculated for 10 realizations of each combination. Results showed that the characteristic parameters of the RSCf are greatly influenced by R, σ and slope. At low slopes and high ratios of σ/2R, the characteristic parameters of the RSCf appear linked to a single component of the surface roughness (R or σ). On the contrary, both R and σ are needed to predict the RSCf at high slopes and low ratios of σ/2R. A simple conceptualization of surface depressions as rectangles, whose shape was determined by R and σ, allowed deriving simple mathematical expressions to estimate the characteristic parameters of the RSCf in function of R, σ and slope. In the case of DSmax, the proposed equation performed better than previous empirical expressions found in the literature which do not account for the horizontal component of the surface roughness. The proposed expressions allow estimating the characteristic points of the RSCf with reasonable accuracy and could therefore prove useful for integrating plot-scale overland flow connectivity into hydrological models whenever the RSCf presents a well-defined connectivity threshold.Keywords
536 _ _ |0 G:(DE-HGF)POF3-255
|a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255)
|c POF3-255
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef
700 1 _ |0 P:(DE-Juel1)129477
|a Javaux, Mathieu
|b 1
700 1 _ |0 P:(DE-HGF)0
|a Bielders, Charles L.
|b 2
773 _ _ |0 PERI:(DE-600)1473173-3
|a 10.1016/j.jhydrol.2015.06.031
|g Vol. 528, p. 192 - 205
|p 192 - 205
|t Journal of hydrology
|v 528
|x 0022-1694
|y 2015
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.pdf
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.gif?subformat=icon
|x icon
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.jpg?subformat=icon-1440
|x icon-1440
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.jpg?subformat=icon-180
|x icon-180
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.jpg?subformat=icon-640
|x icon-640
|y Restricted
856 4 _ |u https://juser.fz-juelich.de/record/203401/files/1-s2.0-S0022169415004448-main.pdf?subformat=pdfa
|x pdfa
|y Restricted
909 C O |o oai:juser.fz-juelich.de:203401
|p VDB
|p VDB:Earth_Environment
910 1 _ |0 I:(DE-588b)5008462-8
|6 P:(DE-Juel1)129477
|a Forschungszentrum Jülich GmbH
|b 1
|k FZJ
913 1 _ |0 G:(DE-HGF)POF3-255
|1 G:(DE-HGF)POF3-250
|2 G:(DE-HGF)POF3-200
|a DE-HGF
|l Terrestrische Umwelt
|v Terrestrial Systems: From Observation to Prediction
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Erde und Umwelt
914 1 _ |y 2015
915 _ _ |0 StatID:(DE-HGF)0100
|2 StatID
|a JCR
|b J HYDROL : 2013
915 _ _ |0 StatID:(DE-HGF)0200
|2 StatID
|a DBCoverage
|b SCOPUS
915 _ _ |0 StatID:(DE-HGF)0300
|2 StatID
|a DBCoverage
|b Medline
915 _ _ |0 StatID:(DE-HGF)0199
|2 StatID
|a DBCoverage
|b Thomson Reuters Master Journal List
915 _ _ |0 StatID:(DE-HGF)0110
|2 StatID
|a WoS
|b Science Citation Index
915 _ _ |0 StatID:(DE-HGF)0150
|2 StatID
|a DBCoverage
|b Web of Science Core Collection
915 _ _ |0 StatID:(DE-HGF)0111
|2 StatID
|a WoS
|b Science Citation Index Expanded
915 _ _ |0 StatID:(DE-HGF)1060
|2 StatID
|a DBCoverage
|b Current Contents - Agriculture, Biology and Environmental Sciences
915 _ _ |0 StatID:(DE-HGF)1160
|2 StatID
|a DBCoverage
|b Current Contents - Engineering, Computing and Technology
915 _ _ |0 StatID:(DE-HGF)1050
|2 StatID
|a DBCoverage
|b BIOSIS Previews
915 _ _ |0 StatID:(DE-HGF)9900
|2 StatID
|a IF < 5
920 1 _ |0 I:(DE-Juel1)IBG-3-20101118
|k IBG-3
|l Agrosphäre
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)IBG-3-20101118
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21