JEQ Journal of Natural Resources and Life Sciences Education
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Published in J Environ Qual 21:426-432 (1992)
© 1992 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Comfort, S.D.
Right arrow Articles by Baham, J.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Comfort, S.D.
Right arrow Articles by Baham, J.
Agricola
Right arrow Articles by Comfort, S.D.
Right arrow Articles by Baham, J.

Modeling Soil Sulfate Sorption Characteristics

S.D. Comfort

Dep. of Agronomy, Univ. of Nebraska, Lincoln, NE 68583-0915;

R.P. Dick* and J. Baham

Dep. of Crop and Soil Science, Strand Agric. Hall 202, Oregon State Univ., Corvallis, OR 97331-2213.

* Corresponding author.

ABSTRACT

Knowledge of soil SO4 adsorption characteristics is required for predicting the fate of atmospheric S depositions on terrestrial ecosystems. This study developed two models for predicting the SO4 sorption characteristics of field moist soils from routinely measured soil physical and chemical properties. Sixty-two soil samples from the U.S. Northeastern (NE) and Southern Blue Ridge Province (SBRP) regions were used in model development. The first modeling approach used stepwise multiple regression to identify which combinations of soil properties best predicted each Langmuir constant. The Langmuir constant regression equations were then substituted back into the Langmuir model and used to predict SO4 sorption for each equilibrium SO4 concentration. This approach described SO4 sorption reasonably well for both regions (R2 of 0.57–0.89). In the second approach, a better fit of SO4 sorption was achieved (R2 of 0.81–0.92) using fewer soil properties by expressing the Langmuir constants as linear functions of selected soil properties and directly estimating the soil property coefficients by nonlinear regression. Soil properties used in the second model included: dithionite-citrate-extractable Al (Ald), total organic C (TOC), and extractable SO4 for the NE region; and Ald, TOC, clay content, pH, and CEC for the SBRP region. These results indicated that regional soil SO4 sorption characteristics could be predicted for field moist soils with the knowledge of only a few routinely measured soil properties.


NOTES

Oregon State Univ. Agric. Exp. Stn. Tech. Pap. 9518. Although the research reported in this article has been supported by the USEPA through assistant agreement CR-815370-0101 to Oregon State Univ., it has not been subjected to the Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.

Received for publication March 11, 1991.





HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education
Vadose Zone Journal
Soil Science Society of America Journal Journal of Plant Registrations The Plant Genome
Copyright © 1992 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.