Inverse modeling of laboratory experiment to assess parameter transferability of pesticide environmental fate into outdoor experiments under paddy test systems. Issue 8 (10th April 2020)

• Record Type: Journal Article
• Authors: Kondo, Kei; Wakasone, Yoshiki; Iijima, Kazuaki; Ohyama, Kazutoshi
• Is Part Of: Pest management science. Volume 76:Issue 8(2020)
• Page Start: 2768
• Page End: 2780
• Publication Date: 2020-04-10
• Subjects: paddy herbicides -- inverse modeling -- parameter transfer -- persistence -- partitioning -- time dependent sorption; Pests -- Control -- Periodicals; Pesticides -- Periodicals; 632.9
• DOI: 10.1002/ps.5824
• Languages: English
• ISSNs: 1526-498X

Abstract

Abstract: Background: Extraction of environmental fate parameters for pesticides by inverse modeling in laboratory experiments has evolved to become a common practice in higher tier exposure modeling. This study focuses on flooded paddy soil conditions using a simple container test system. Four active ingredients of paddy herbicide were tested. The results were parameterized and transferred to analyze the effect of formulation types on the outdoor experimental data via inverse analyses of two structurally‐compatible mathematical models, namely: pesticide concentration in paddy field for laboratory (PCPF‐LR) and PCPF for outdoors (PCPF‐1Rv1.1 ). Results: After in‐laboratory calibration, the PCPF‐LR model revealed statistically acceptable or ideal simulations of pesticide concentrations in both the aqueous and soil phases (e.g . Nash–Sutcliffe efficiency > 0.7), in addition to determining the apparent sorption from the laboratory data. The extracted persistence indicators (degradation half‐life, DegT50 ) in the aqueous phase were 1.4–38.7 times higher than those of the dissipation (DT50 ) due to the exclusion of partitioning and phase transfer processes (diffusion and sorption). In the outdoor experiment, 72% of the outdoor‐calibrated simulations of the PCPF‐1Rv1.1 model, showed statistically acceptable representations of the concentrations in paddy water. Furthermore, the DegT50 as 'bulk' degradation in paddy water was statistically insignificant between the formulation types; however, the DT50 demonstrated statistically different results. Conclusion: The laboratory/outdoor data interconnections using proposed modeling approach facilitate the data‐specific model calibration and analysis. These can be useful in the exposure modeling of paddy pesticide by manipulating the parameter uncertainties associated with the experimental constraints. © 2020 Society of Chemical Industry Abstract : The two‐step inverse analysis using two structurally‐compatible models was developed to interconnect the laboratory/outdoor data in paddy test system. This leads to a more realistic exposure modeling of paddy pesticides. © 2020 Society of Chemical Industry