Modeling the Fate of Acetochlor and Terbuthylazine in the Field Using the Root Zone Water Quality Model

incubation studies. Although Walker’s model was generally found to overestimate total soil residues at later Data collected from a 3-yr controlled field study in Hamilton, New sampling dates (Walker, 1987), Heiermann et al. (1995) Zealand were used to examine whether the Root Zone Water Quality Model is capable of predicting water movement and pesticide fate in reported that this model greatly underestimated the perthe field based on key lab-measured parameters and environmental sistence of two pesticides during cold, wet seasons in a variables. Acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylGermany site. This suggests that the model’s perforphenyl) acetamide; 2.5 and 5.0 kg a.i. ha 1] and terbuthylazine mance is significantly affected by site-specific soil and (C9H16ClN5 ; 1.5 and 3.0 kg a.i. ha 1) were applied onto nine field plots environmental conditions. (3 by 9 m each). Soil core samples were taken to a depth of 1 m to A simple model, such as that developed by Walker determine soil water contents and pesticide concentrations. Dissipa(1974), has the advantages of easy operation and applition of both pesticides in the field at both application rates followed cation. The most obvious disadvantage is the difficulty first-order kinetics (adjusted r2 0.91). The mean dissipation halffor the users to explore the effects of various factors life was 16 d for acetochlor and 25 d for terbuthylazine. Relatively on model simulations as these factors are frequently small amounts of the pesticides leached below 5 cm and none leached below 10 cm. Predicted soil water contents in the soil profile were lumped. Moreover, the model was specifically designed not significantly different from those measured in the field (p 0.84). only for predicting pesticide persistence in the field. The Predicted acetochlor and terbuthylazine masses in the soil profile need for accurate predictions of pesticide concentration based on a linear instantaneous-equilibrium (I-E) partitioning model and persistence from chemical and physical processes matched those measured in the field (adjusted r2 0.93). However, has encouraged the development of more complex modpredicted pesticide concentrations in the soil profile were less satisfacels for simulating pesticide fate and transport in soils. tory, with 68 and 35% of the predicted concentrations being within GLEAMS (Leonard et al., 1987), LEACHM (Wagenet a factor of 2 of the measured concentrations for 0to 5and 5to and Hutson, 1987), MACRO (Jarvis, 1994), PRZM 10-cm depths, respectively. Calibration of each pesticide sensitive (Carsel et al., 1998), and RZWQM (Ahuja et al., 2000) parameter individually did not significantly improve the overall preare among the recently developed process-based moddictions of pesticide mass and concentrations in the soil profile when the I-E partitioning model was used. The predictions were improved els. They were developed in response to the demand when a two-site, equilibrium-kinetic (E-K) sorption model was used. for models with relatively high scientific credibility. RZWQM is one of the latest developed numerical models that incorporate detailed processes for simulating soil– water movement and pesticide dissipation and transport T concentration and persistence of pesticide resiin agricultural systems. Furthermore, RZWQM has a dues in soils have both economical and environmenuser-friendly, Microsoft Windows (Microsoft Inc., Redtal significance and are often used as key indicators for mond, WA) based interface that greatly enhances model environmental risk assessments. Therefore, significant parameterization and operations. In particular, the pestresearch efforts have been directed to the development icide submodel incorporates some of the findings and of effective tools for predicting pesticide concentration recommendations of the FOCUS and FIFRA modeling and persistence in the field. Simulation models have workshops (Wauchope et al., 2000). The hypothesis that been developed that integrate pesticide properties, soil process-based models should deliver better accuracy in properties, climatic conditions, and management pracmodel predictions, especially with enhanced model paratices for such predictions. The hypothesis is that ademeterization, seems to be supported by recent validation quate predictions of pesticide fate in the field can be studies with RZWQM (Ma et al., 1995; Singh and Kanwar, approached with these simulation models using key pa1995; Ahuja et al., 1996) and other models (Pennell et rameters measured in the lab coupled with measured al., 1990). environmental variables. A simulation model such as RZWQM has to be thorWalker (1974) predicted pesticide persistence in the oughly tested under local conditions before using as a field using parameters primarily derived from the lab management and analytical tool for local government and regulatory agencies. This is because of the siteQ. Ma, formerly with AgResearch, Hamilton, New Zealand; currently specific nature of simulation models. However, it has with Environmental & Turf Services, Inc., 11141 Georgia Ave., #208, Wheaton, MD 20902; A. Rahman and T. James, AgResearch, P. Holbeen frequently not possible to obtain suitably compreland and D. McNaughton, HortResearch, Ruakura Research Centre, hensive data for validating all processes and state variP.B. 3123, Hamilton, New Zealand; K. Rojas and L. Ahuja, USDAARS, Great Plains Systems Research, P.O. Box E, Fort Collins, CO Abbreviations: E-K, equilibrium-kinetic; FIFRA, Federal Insecticide, 80522. Received 14 May 2003. *Corresponding author (qinglima@aol. Fungicide and Rodenticide Act; FOCUS, Forum for the coordination com). of pesticide fate models and their uses; HPLC, high-pressure liquid chromatography; I-E, instantaneous equilibrium; MWHC, maximum Published in Soil Sci. Soc. Am. J. 68:1491–1500 (2004).  Soil Science Society of America water holding capacity; NRMSE, normalized root mean square error; OECD, Organization for Economic Co-operation and Development. 677 S. Segoe Rd., Madison, WI 53711 USA