Soil Sample Selection for Environmental Analysis

Journal of Soil and Water Conservation 56:165-171

Posted: 27 Nov 2014

See all articles by Channing Arndt

Channing Arndt

United Nations - World Institute for Development Economics Research (UNU/WIDER)

Paul V. Preckel

Purdue University - Department of Agricultural Economics

Date Written: 2001

Abstract

Estimating variables, such as erosion rates, across a diverse soil and water resource base is a problem of interest in natural resource management. Here, we propose an alternative to the predominant soils (PS) approach of Stoneman, Brown, and Spivey. Our method called Gaussian quadrature (GQ), is adapted from the numerical integration literature. Two experiments compare GQ with PS. The first plugs sample input into a simulation model to approximate erosion rates, surface runoff, and crop yield for a region. The second estimates erosion in three regions using the Universal Soil Loss Equation (USLE). Results for the GQ samples are compared to results for the full population and results from random samples. GQ sampling tends to be more effective, particularly with respect to measures related to the heterogeneity of the population, such as the variance and skewness, than PS or random sampling. Judiciously used GQ sample selection permits reductions in the number of soils sampled with only a moderate loss of accuracy.

Suggested Citation

Arndt, Channing and Preckel, Paul V., Soil Sample Selection for Environmental Analysis (2001). Journal of Soil and Water Conservation 56:165-171, Available at SSRN: https://ssrn.com/abstract=2530647

Channing Arndt (Contact Author)

United Nations - World Institute for Development Economics Research (UNU/WIDER) ( email )

Katajanokanlaituri 6 B
Helsinki, FI‐00160
Finland

Paul V. Preckel

Purdue University - Department of Agricultural Economics ( email )

1145 Krannert Building
West Lafayette, IN 47907-1145
United States
765-494-4240 (Phone)
765-494-4240 (Fax)

HOME PAGE: http://www.agecon.purdue.edu/academic/agec652/index.htm

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