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This article in SSSAJ

  1. Vol. 51 No. 2, p. 405-409
     
    Received: May 27, 1986
    Published: Mar, 1987


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doi:10.2136/sssaj1987.03615995005100020027x

Slope Gradient Effect on Erosion of Reshaped Spoil1

  1. S. A. Schroeder2

Abstract

Abstract

Eroded sediment from reshaped spoil areas of surface mines with steep slope gradients may damage the productivity of surrounding reclaimed and undisturbed areas. Spoil erosion is made more severe by low infiltration rates caused by high bulk densities and, thus, low porosities. The objective of this research was to determine the applicability of the Universal Soil Loss Equation (USLE) slope function for predicting spoil erosion rates. The effect of slope gradient on sediment losses from reshaped spoil at two surface mines was quantified by using a rainfall simulator. Slopes ranged from 0.1 to 11.1%. Three sites, differing in sodium adsorption ratio (SAR), were selected. Spoil surface conditions were either crusted (CR) or tilled by hand to simulate freshly respread (FR). Spoil losses (data combined over sites) were significantly greater from initially dry CR than FR surfaces but significantly less for wet and very wet surface conditions. Spoil loss increased linearly with increasing slope gradient at all sites for both surface conditions (CR and FR). The rainfall sequence at the low SAR site for the FR surface (two 1-h runs) contributed to the significant difference found for that site's slope gradient effect on spoil loss when compared to the other two sites (one 1-h and two 30-min application sequences). The latter two sites' slope gradient effects on spoil loss were not significantly different from one another. No differences in the slope gradient equations were found between the three sites for the CR surface condition. The USLE curvilinear soil loss ratio (SLR) function underestimated the slope gradient effect on spoil loss for slopes <9% and overestimated at slopes >9% compared to the developed spoil SLR function. Regression/correlation analyses showed a highly significant linear relationship between spoil K values predicted using the FR field data and the developed spoil SLR function to the K values estimated using the USLE nomograph. The K values from the field were approximately 81% of the nomograph. Use of the spoil SLR function and prediction model for K should allow adequate estimation of spoil erosion losses.

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