Abstract

Until the mid-1990s, a major limitation of using the Universal Soil Loss Equation and Revised Universal Soil Loss Equation erosion models at regional landscape scales was the difficulty in estimating LS factor (slope length and steepness) values suitable for use in geographic information systems applications. A series of ArcInfo™ Arc Macro Language scripts was subsequently created that enabled the production of either USLE- or RUSLE-based LS factor raster grids using a digital elevation model input data set. These scripts have functioned exceptionally well for both single- and multiple-watershed applications within targeted study areas. However, due to the nature and complexity of flowpath processing necessary to compute cumulative slope length, the scripts have not taken advantage of available computing resources to the extent possible. It was determined that the speed of the computer runs could be significantly increased without sacrificing accuracy in the final results by performing the majority of the elevation data processing in a two-dimensional array framework outside the ArcInfo environment. This paper describes the evolution of a major portion of the original RUSLE-based AML processing code to an array-based executable program using ANSI C++™ software. Examples of the relevant command-line arguments are provided and comparative results from several AML-vs.-executable time trials are also presented. In wide-ranging areas of the United States where it has been tested, the new RUSLE-based executable has produced LS-factor values that mimic those generated by the original AML as well as the RUSLE Handbook estimates. Anticipated uses of the executable program include water quality assessment, landscape ecology, land-use change detection studies, and decision support activities. This research has now given users the option of either running the executable file alone to process a single watershed reporting unit or running a supporting AML shell program that calls upon the executable file as necessary to perform automated processing for a user-specified number of watersheds.

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