Improved slope adjustment functions for soil erosion prediction

Sheridan, G. J., So, H. B. and Loch, R. J. (2003) Improved slope adjustment functions for soil erosion prediction. Australian Journal of Soil Research, 41 8: 1489-1508. doi:10.1071/SR02029

Author Sheridan, G. J.
So, H. B.
Loch, R. J.
Title Improved slope adjustment functions for soil erosion prediction
Journal name Australian Journal of Soil Research   Check publisher's open access policy
ISSN 0004-9573
Publication date 2003
Sub-type Article (original research)
DOI 10.1071/SR02029
Volume 41
Issue 8
Start page 1489
End page 1508
Total pages 20
Editor J. Fegent
S. Banerjee
Place of publication Sydney, Australia
Publisher CSIRO Publishing
Collection year 2003
Language eng
Subject C1
300104 Land Capability and Soil Degradation
771007 Rehabilitation of degraded mining lands
Abstract Numerous studies in the last 60 years have investigated the relationship between land slope and soil erosion rates. However, relatively few of these have investigated slope gradient responses: ( a) for steep slopes, (b) for specific erosion processes, and ( c) as a function of soil properties. Simulated rainfall was applied in the laboratory on 16 soils and 16 overburdens at 100 mm/h to 3 replicates of unconsolidated flume plots 3 m long by 0.8 m wide and 0.15 m deep at slopes of 20, 5, 10, 15, and 30% slope in that order. Sediment delivery at each slope was measured to determine the relationship between slope steepness and erosion rate. Data from this study were evaluated alongside data and existing slope adjustment functions from more than 55 other studies from the literature. Data and the literature strongly support a logistic slope adjustment function of the form S = A + B/[1 + exp (C - D sin theta)] where S is the slope adjustment factor and A, B, C, and D are coefficients that depend on the dominant detachment and transport processes. Average coefficient values when interill-only processes are active are A - 1.50, B 6.51, C 0.94, and D 5.30 (r(2) = 0.99). When rill erosion is also potentially active, the average slope response is greater and coefficient values are A - 1.12, B 16.05, C 2.61, and D 8.32 (r(2) = 0.93). The interill-only function predicts increases in sediment delivery rates from 5 to 30% slope that are approximately double the predictions based on existing published interill functions. The rill + interill function is similar to a previously reported value. The above relationships represent a mean slope response for all soils, yet the response of individual soils varied substantially from a 2.5-fold to a 50-fold increase over the range of slopes studied. The magnitude of the slope response was found to be inversely related ( log - log linear) to the dispersed silt and clay content of the soil, and 3 slope adjustment equations are proposed that provide a better estimate of slope response when this soil property is known. Evaluation of the slope adjustment equations proposed in this paper using independent datasets showed that the new equations can improve soil erosion predictions.
Keyword Agriculture, Soil Science
Loss Equation
Raindrop Impact
Q-Index Code C1

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 5 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Access Statistics: 192 Abstract Views  -  Detailed Statistics
Created: Wed, 15 Aug 2007, 02:30:59 EST