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Erosion prediction

About: Erosion prediction is a research topic. Over the lifetime, 551 publications have been published within this topic receiving 25280 citations.


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Book
01 Jan 1978
TL;DR: The Universal Soil Loss Equation (USLE) as discussed by the authors is a model designed to predict the average rate of soil erosion for each feasible alternative combination of crop system and management practices in association with a specified soil type, rainfall pattern and topography.
Abstract: The Universal Soil Loss Equation (USLE) enables planners to predict the average rate of soil erosion for each feasible alternative combination of crop system and management practices in association with a specified soil type, rainfall pattern, and topography. When these predicted losses are compared with given soil loss tolerances, they provide specific guidelines for effecting erosion control within specified limits. The equation groups the numerous interrelated physical and management parameters that influence erosion rate under six major factors whose site-specific values can be expressed numerically. A half century of erosion research in many states has supplied information from which at least approximate values of the USLE factors can be obtained for specified farm fields or other small erosion prone areas throughout the United States. Tables and charts presented in this handbook make this information available for field use. Significant limitations in the data are identified. The USLE is an erosion model designed to compute longtime average soil losses from sheet and rill erosion under specified conditions. It is also useful for construction sites and other non-agricultural conditons, but it does not predict deposition and does not compute sediment yields from gully, streambank, and streambed erosion

6,947 citations

Book
01 Mar 1997
TL;DR: Renard, K.G., G.R.Weesies, D.K. McCool, and D.C. Yoder as mentioned in this paper have developed an erosion model predicting the average annual soil loss.
Abstract: Renard, K.G., G.R. Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder, coordinators. Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). U.S. Department of Agriculture, Agriculture Handbook No. 703, 404 pp. The Revised Universal Soil Loss Equation (RUSLE) is an erosion model predicting longtime average annual soil loss (A) resulting from raindrop splash and runoff from specific field slopes in specified cropping and management systems and from rangeland. Widespread use has substantiated the RUSLE’s usefulness and validity. RUSLE retains the six factors of Agriculture Handbook No. 537 to calculate A from a hillslope. Technology for evaluating these factor values has been changed and new data added. The technology has been computerized to assist calculation. Thus soil-loss evaluations can be made for conditions not included in the previous handbook using fundamental information available in three data bases: CITY, which includes monthly precipitation and temperature, front-free period, annual rainfall erosivity (R) and twice monthly distributions of storm erosivity (E); CROP, including below-ground biomass, canopy cover, and canopy height at 15-day intervals as well as information on crop characteristics; and OPERATION, reflecting soil and cover disturbances that are associated with typical farming operations.

4,326 citations

Journal ArticleDOI
TL;DR: In this paper, a model was developed for estimating soil erosion by water on hillslopes for use in new USDA erosion prediction technology. Detachment, transport, and deposition processes were represented.
Abstract: Amodel was developed for estimating soil erosion by water on hillslopes for use in new USDA erosion prediction technology. Detachment, transport, and deposition processes were represented. The model uses a steady-state sediment continuity equation for predicting rill and interrill processes. Net detachment in rills is considered to occur when the hydraulic shear stress of flow exceeds the critical shear stress of the soil and when sediment load in a rill is less than the sediment transport capacity. Net deposition is calculated when the sediment load is greater than the transport capacity. Rill detachment rate is dependent upon the ratio of sediment load to transport capacity, rill erodibility, hydraulic shear stress, surface cover, below ground residue, and consolidation. Rill hydraulics are used to calculate shear stresses and a simplified transport equation, calibrated with the Yalin transport equation, is used to compute transport capacity in rills. Interrill erosion is represented as a function of rainfall intensity, residue cover, canopy cover, and interrill soil erodibility. The model has capabilities for estimating spatial distributions of net soil loss and is designed to accommodate spatial variability in topography, surface roughness, soil properties, hydrology, and land use conditions on hillslopes..

1,192 citations

Journal ArticleDOI
TL;DR: Raindrop-impact-induced erosion is initiated when detachment of soil particles from the surface of the soil results from an expenditure of raindrop energy as mentioned in this paper, and particles are transported away from the site of the impact by one or more of the following transport processes: drop splash, raindrop-induced flow transport, or transport by flow without stimulation by drop impact.
Abstract: Raindrop-impact-induced erosion is initiated when detachment of soil particles from the surface of the soil results from an expenditure of raindrop energy. Once detachment by raindrop impact has taken place, particles are transported away from the site of the impact by one or more of the following transport processes: drop splash, raindrop-induced flow transport, or transport by flow without stimulation by drop impact. These transport processes exhibit varying efficiencies. Particles that fall back to the surface as a result of gravity produce a layer of pre-detached particles that provides a degree of protection against the detachment of particles from the underlying soil. This, in turn, influences the erodibility of the eroding surface. Good understanding of rainfall erosion processes is necessary if the results of erosion experiments are to be properly interpreted. Current process-based erosion prediction models do not deal with the issue of temporal variations in erodibility during a rainfall event or variabilities in erodibility associated with spatial changes in dominance of the transport processes that follow detachment by drop impact. Although more complex erosion models may deal with issues like this, their complexity and high data requirement may make them unsuitable for use as general prediction tools. Copyright © 2005 John Wiley & Sons, Ltd.

483 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20221
202128
202021
201929
201834
201725