Skip to main content
ARS Home » Research » Publications at this Location » Publication #151940

Title: PARAMETERIZATION OF WEPS FROM SITE DATA

Author
item Skidmore, Edward
item RETTA, AMARE - KANSAS STATE UNIVERSITY
item ANDERSON, ALAN - USAERDC, CERL
item GEBHART, D - USAERDC, CERL
item Van Donk, Simon

Submitted to: ASA-CSSA-SSSA Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 7/23/2003
Publication Date: 11/2/2003
Citation: Skidmore, E.L., Retta, A.L., Anderson, A.B., Gebhart, D.L., Van Donk, S.J. 2003. Parameterization of weps from site data. ASA-CSSA-SSSA Annual Meeting, Denver, Colorado, November 2-6, 2003.

Interpretive Summary:

Technical Abstract: The Wind Erosion Prediction System (WEPS) was developed to estimate soil erosion by wind from agricultural lands. A need exists to extend the use of WEPS as a management tool for additional lands, including military training lands, where input data are often limited. The objective of this research was to parameterize WEPS for application when the site data are not as complete as desired. Since the stand-alone version of the WEPS erosion sub-model, dubbed EROSION, requires much less data we used it to simulate individual wind storm event sand compare with measured data. Five arrays of BSNE sediment traps, and five Sensits (instrument for detecting saltating soil particles) were installed at five sites representing typical surfaces at the Marine Corps Air Ground Combat Center (MCAGCC), Twentynine Palms, CA. Protective value of vegetation was estimated from vegetation survey reports in the MCAGCC. For creosote bush (Larrea Tridentata), the dominant plant in the MCAGCC, a relationship for calculating frontal area index from cover data was developed. Agreement between measured (calculated from BSNE and Sensit data) and simulated results, using the stand-alone erosion sub-model, was best when frontal area index of 0.06 m2m-2 and height of 0.5m were used. Work is continuing to more completely parameterize WEPS from incomplete site data.