|
|
||||||||
a Bayer CropScience and Texas A&M Univ., 17745 South Metcalf, Stilwell, KS 66085
b COMSYS, 360 Prairie Heritage Dr., O'Fallon, MO 63368
c Bayer CropScience, 17745 South Metcalf, Stilwell, KS 66085
d 120 Agricultural Hall, Dep. of Biosystems and Agr. Engr., Oklahoma State Univ., Stillwater, OK
* Corresponding author (garey.fox{at}okstate.edu).
Received for publication June 12, 2008. Pesticide trapping efficiency of vegetated filter strips (VFS) is commonly predicted with low success using empirical equations based solely on physical characteristics such as width and slope. The objective of this research was to develop and evaluate an empirical model with a foundation of VFS hydrological, sedimentological, and chemical specific parameters. The literature was reviewed to pool data from five studies with hypothesized significant parameters: pesticide and soil properties, percent reduction in runoff volume (i.e., infiltration) and sedimentation, and filter strip width. The empirical model was constructed using a phase distribution parameter, defined as the ratio of pesticide mass in dissolved form to pesticide mass sorbed to sediment, along with the percent infiltration, percent sedimentation, and the percent clay content (R2 = 0.86 and standard deviation of differences [STDD] of 7.8%). Filter strip width was not a statistically significant parameter in the empirical model. For low to moderately sorbing pesticides, the phase distribution factor became statistically insignificant; for highly sorbing pesticides, the phase distribution factor became the most statistically significant parameter. For independent model evaluation datasets, the empirical model based on infiltration and sediment reduction, the phase distribution factor, and the percent clay content (STDD of 14.5%) outperformed existing filter strip width equations (STDD of 38.7%). This research proposed a procedure linking a VFS hydrologic simulation model with the proposed empirical trapping efficiency equation. For datasets with sufficient information for the VFS modeling, the linked numerical and empirical models significantly (R2 = 0.74) improved predictions of pesticide trapping over empirical equations based solely on physical VFS characteristics.
Abbreviations: CF, compaction factor d50, diameter of soil particle in which 50% is finer (mm)
E, sediment mass reduction (%) Fph, phase distribution factor (-) Kd, linear sorption coefficient (L kg–1) Koc, organic carbon sorption coefficient (L kg–1) Ksat, saturated hydraulic conductivity (cm h–1)
Q, runoff volume reduction (%)
P, pesticide mass reduction (%) SAV, suction depth (m) WB, filter strip width (m)
o, initial soil water content (-)
s, saturated soil water content (-) %C, percent clay content (%) %OM, percent organic matter content (%) %S, percent sand content (%) %Si, percent silt content (%)
| 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 | |||