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Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE).

PB97153704

Publication Date	1997
Personal Author	Renard, K. G.; Foster, G. R.; Weesies, G. A.; McCool, D. K.; Yoder, D. C.
Page Count	408
Abstract	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. 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.
Keywords	Soil erosion Predictions Erosion rates Surface runoff Rain erosion Water erosion Surface erosion Rill erosion Soil classification Soil moisture Surface roughness Rainfall-runoff relationships Cultivated lands Ground cover Land use Strip cropping Contour farming Biomass Canopies(Vegetation) Farm management Range management Agronomy Soil management Soil conservation Soil stabilization Erosion control Revised Universal Soil Loss Equation
Source Agency	Agriculture Research Service
Corporate Authors	Agricultural Research Service, Greenbelt, MD.; Tennessee Univ., Knoxville. Dept. of Agricultural Engineering.; National Soil Erosion Lab., West Lafayette, IN.
Supplemental Notes	Prepared in cooperation with National Soil Erosion Lab., West Lafayette, IN. and Tennessee Univ., Knoxville. Dept. of Agricultural Engineering.
Document Type	Technical Report
Title Note	Agriculture handbook.
NTIS Issue Number	199714

Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE).

Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE).
PB97153704

Publication Date	1997
Personal Author	Renard, K. G.; Foster, G. R.; Weesies, G. A.; McCool, D. K.; Yoder, D. C.
Page Count	408
Abstract	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. 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.
Keywords	Soil erosion Predictions Erosion rates Surface runoff Rain erosion Water erosion Surface erosion Rill erosion Soil classification Soil moisture Surface roughness Rainfall-runoff relationships Cultivated lands Ground cover Land use Strip cropping Contour farming Biomass Canopies(Vegetation) Farm management Range management Agronomy Soil management Soil conservation Soil stabilization Erosion control Revised Universal Soil Loss Equation
Source Agency	Agriculture Research Service
Corporate Authors	Agricultural Research Service, Greenbelt, MD.; Tennessee Univ., Knoxville. Dept. of Agricultural Engineering.; National Soil Erosion Lab., West Lafayette, IN.
Supplemental Notes	Prepared in cooperation with National Soil Erosion Lab., West Lafayette, IN. and Tennessee Univ., Knoxville. Dept. of Agricultural Engineering.
Document Type	Technical Report
Title Note	Agriculture handbook.
NTIS Issue Number	199714