Use of mathematical modeling and its inverse analysis for precise assessment of pesticide dissipation in a paddy environment

The extrapolability of the lysimeter test as a dissipation simulator in an actual paddy field was evaluated using mathematical models and their inverse analyses for predicting pesticide fate and transport processes in paddy test systems. As a source of experimental data, a four-year comparative experiment in lysimeters and paddy fields was conducted using various paddy pesticides. First, the dissipations for various active ingredients in granule pesticides under submerged applications were statistically compared using simple kinetic modeling. Second, the dissipation pathways, unobserved experimental components, and effect of the experimental setting were evaluated using a higher tier mathematical model with a novel inverse analysis protocol. Finally, owing to experimental constraints, the unobtainable parameters were extracted from the laboratory container test before being transferred to compare the outdoor experimental data under different formulation types.     

Pesticide paddy field model (PADDY) for predicting pesticide concentrations in water and soil in paddy fields

To evaluate the fate of pesticides in paddy fields, the pesticide paddy field model (PADDY) has been developed for predicting pesticide concentrations in paddy fields and the run-off amount of pesticides to the aquatic environment. This model focused particularly on granule formulation because these formulations have been used widely as herbicides on paddy fields in Japan. The behavior of pesticides in paddy fields was assessed by considering the main processes on the basis of a compartment system and the mass-balance equations of pesticides in the compartments were derived from kinetic data. The mathematical model, PADDY, was constructed by numerical solution techniques. A method for measuring the pesticide parameters for this model was also developed. To validate the model, a field experiment was carried out on a paddy field and the concentration changes of pesticides in water and soil were measured. These were in reasonably good agreement with those predicted by PADDY. © 1999 Society of Chemical Industry     

A refined lack‐of‐fit statistic to calibrate pesticide fate models for responsive systems

BACKGROUND: Calibration by inverse modelling was performed with the MACRO transport and fate model using long‐term (>10 years) drainflow and isoproturon (IPU) data from western France. Two lack‐of‐fit (LOF) indices were used to control the inverse modelling: sum of squares (SS) and an alternative statistic called the vertical‐horizontal distance integrator (VHDI), which is designed to account for offsets in observed and predicted arrival times of peak IPU concentration. With these data, SS was artificially inflated because it is limited to comparison of predicted and observed IPU concentrations that are concurrent in time. The LOFs were used along with the index of agreement (d) and the correlation coefficient (r) to ascertain the fit of the calibrated models. RESULTS: Predicted arrival times of peak IPU concentration differed somewhat from observed times. All four indices indicated better model fit for the second of two validation periods when inverse modelling was controlled by VHDI rather than SS (SS = 26.4, d = 0.660, r = 0.606 and VHDI = 1.25). The VHDI statistic was markedly lower compared with the uncalibrated model (38.0) and SS calibration results (24.5). The final maximum predicted IPU concentration (44.5 µg L^?1) for the calibration period was very similar to the observed value (44 µg L^?1). CONCLUSION: VHDI is seen as an effective alternative to SS for calibration and validation of pesticide fate models applied to responsive systems. VHDI provided a more realistic assessment of model performance for the transient flows and short‐lived concentrations observed here, and also effectively substituted for the objective function in inverse modelling. Copyright © 2009 Society of Chemical Industry     

基于DNDC模型的不同水文年稻田水碳管理模式优化

为探究不同水文年型下稻田最优的水碳管理模式,基于2 a田间试验数据校正并验证了DNDC模型,选取了3种典型的水文年,模拟了不同灌溉模式和秸秆还田水平下稻田土壤有机碳(SOC)和水稻产量的变化,并对结果进行了比选。结果表明:DNDC模型可以较好地模拟节水灌溉条件下稻田SOC和水稻产量变化;灌溉模式影响了稻田SOC和水稻产量,相同秸秆还田水平下,控灌稻田0～10 cm土层SOC略低于淹灌处理,但水稻产量更高,控灌稻田的SOC和水稻产量分别较淹灌稻田降低了0.25%～1.92%和增加了0.32%～8.13%。随着秸秆还田水平的提高,不同水文年的稻田SOC均呈阶梯状上升趋势,但水稻产量和水分生产率的结果存在差异,平水年呈先升高后稳定的趋势,在6 500 kg·hm^-2秸秆还田水平下达到峰值,丰水年条件下秸秆还田的增产作用较枯水年更为明显。与1 000 kg·hm^-2的秸秆还田水平相比,8 000 kg·hm^-2秸秆还田水平下水稻产量和水分生产率在1964年(枯水年)分别增加了1.95%和2.27%,而在1977年(丰水年)分别增...