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Classifying Soils for Acidic Deposition Aquatic Effects: A Scheme for the Northeast USA
Author(s) -
Lee J. J.,
Lammers D. A.,
Stevens D. L.,
Thornton K. W.,
Wheeler K. A.
Publication year - 1989
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1989.03615995005300040027x
Subject(s) - soil water , sampling (signal processing) , watershed , streams , environmental science , hydrology (agriculture) , acid deposition , deposition (geology) , sampling scheme , soil science , mathematics , statistics , geology , sediment , computer science , computer network , paleontology , geotechnical engineering , filter (signal processing) , machine learning , estimator , computer vision
The Direct/Delayed Response Project (DDRP) is estimating the number of lakes and streams in three U.S. regions that might become acidic due to current or altered levels of acidic deposition, and the long‐term time scales involved. Because of the influence of soils on aquatic chemistry, DDRP acquired data on soils that were mapped, sampled, and analyzed consistent methods across the regions. In the northeastern USA, about 600 soils (mainly phases of soil series) were identified during mapping of 145 watersheds. Because statistically adequate sampling of every soil was impractical, the soils were grouped into 38 sampling classes. Each of these classes was sampled across several (usually eight) watersheds. The properties of soils on specific watersheds (or portions of watersheds) can be estimated from the regional means and variances of the sampling classes and the percent occurrence of sampling classes on each watershed. This paper describes how the sampling classes for the northeastern USA were developed, the definitions of the classes, and the characteristics of soils within the classes. A preliminary statistical test indicates that the occurrence of sampling classes on watersheds is a significant predictor of Acid Neutralizing Capacity class of the corresponding lakes. Final evaluation of the utility of this scheme will come from the very extensive data analysis and modeling tasks of the DDRP.