Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/27/1997
Publication Date: N/A
Interpretive Summary: Water table management practices have potential for both improving crop yield and protecting water quality. However, when this practice is applied to a new range of conditions outside those previously tested, the results could be quite different from expected. Water quality models such as the Agricultural Drainage and Pesticide Transport (ADAPT) model, when tested and calibrated, can predict results outside the realm of previous experiments. This study tested the ADAPT model for pesticide concentration values under various water table management practices. The results indicated ADAPT is suitable for this use, but that further testing is required before wide application of the model.
Technical Abstract: A water quality model for subirrigation and subsurface drainage, ADAPT (Agricultural Drainage And Pesticide Transport), was tested with field data collected under various water table management practices near Ames, IA. Atrazine and alachlor concentrations at various soil depths for water table depths of 30, 60, and 90 cm were simulated using ADAPT model for corn growing seasons of 1989 through 1991. Daily pesticide concentrations in groundwater predicted by the model were compared with available observed data for the same site. Predicted values of atrazine and alachlor concentrations in groundwater decreased when shallow water table depths were maintained in the lysimeters. Similar trends were noticed with the observed data. Reasonable agreement was obtained between the observed and predicted values of atrazine and alachlor for 1989 to 1991. However, in few cases, results showed a wide variation between observed and predicted values. Because no observed data was available for pesticide concentrations in the unsaturated zone, predicted results could not be compared. Based on our investigation, it appears that ADAPT may be used for predicting subsurface water quality under water table management practices; however, further validation is necessary with more field observed data from similar studies before wider application of this model is made.