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SPATIAL AND TEMPORAL VARIABILITY OF SOIL SURFACE ROUGHNESS AND THE APPLICATION IN HYDROLOGICAL AND SOIL EROSION MODELLING
Author(s) -
CREMERS N. H. D. T.,
VAN DIJK P. M.,
DE ROO A. P. J.,
VERZANDVOORT M. A.
Publication year - 1996
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/(sici)1099-1085(199608)10:8<1035::aid-hyp409>3.0.co;2-#
Subject(s) - erosion , environmental science , spatial variability , hydrology (agriculture) , soil science , surface finish , geology , surface roughness , geomorphology , geotechnical engineering , materials science , statistics , mathematics , composite material
Accurate estimations of water retention and detention are needed to simulate surface runoff and soil erosion following a rainfall event in a catchment. Several equations to estimate the amount of surface depressional storage, the fraction of the soil surface covered by water and the amount of rainfall excess needed to start surface runoff have been developed by Onstad (1984). The random roughness and slope gradient are needed for those estimations. Surface micro‐elevation data have been gathered by a photographic method. The random roughness was determined from those elevation measurements. Several factors which have an impact on the soil surface roughness were taken into account. The main sources of influence are the type of land use, the crop stage within the growing period and tillage direction. Analyses of variance indicated that the variation in the RR‐index could be explained mainly by type of land use, orientation and field type. The temporal variation was relatively small. Gradient data have been determined from a digital elevation model, constructed by digitizing contours. Combining the random roughness and the steepness of slope, the amounts of surface water retention and detention could be estimated. Knowledge of water retention and detention will improve the estimations of runoff and soil erosion modelling in catchments, such as those made with the LISEM model. The agricultural systems examined in this study have similar random roughness values in summer. Different soil erosion rates for several types of land use can not therefore be explained by the random roughness.