TurfPQ, A Pesticide Runoff Model For Turf

J. Environ. Qual. 30:1033–1039 (2001). The author wishes to report several errors in the above paper. I am grateful to Charles W. Bennett, Cornell University, for determining that pesticide runoff was incorrectly calculated for several of the 52 events described in Table 4 These changes also affected Tables 6 and 7 The corrected Tables 4, 6, and 7 are shown below. Because of these corrections, several of the statements in the paper are modified. My apologies to the readers for any inconvenience this may have caused. Here are the locations and corrections to the article. Abstract, sentences 9 and 10 (page 1033). Mean predicted pesticide runoff was 2.9% of application, compared with an observed mean of 2.1%. TurfPQ captured the dynamics of the pesticide runoff events well with R2 = 0.65. Chemical Model section, last sentence in the paragraph following Eq. [6] (p. 1034). The model presumes first order, or exponential decay of the pesticide with rate α (d−1), given by α = 0.693/τ1/2, where τ1/2 is the decay half-life (d). Event Comparisons section of Results and Discussion (p. 1037), sentences 4 and 6. However, the model captures the differences among pesticide events well, explaining 75% of the variation in pesticide runoff… Differences among events are still captured well, although the explained variation drops to 65%. Event Comparisons section of Results and Discussion (p. 1037), last three sentences. For Case B, which evaluates the complete model (hydrology and chemistry), E = 0.176 suggesting that the model is relatively inefficient. However, this is mainly due to the two large overpredictions shown in Fig. 1. When these two events are eliminated, E increases to 0.600. Pesticide Comparisons section of Results and Discussion (p. 1037), second sentence. With the exception of diazinon and dicamba for Case B, model values are higher than observations for all pesticides. Conclusions (p. 1038), second paragraph, last sentence. TurfPQ captures the dynamics of the pesticide runoff events well with R2 = 0.65.