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Effect of uncertainties of agricultural working schedule and Monte-Carlo evaluation of the model input in basin-scale runoff model analysis of herbicides

机译:农业生产计划不确定性的影响及蒙特卡洛模型输入对除草剂流域尺度径流模型分析的影响

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In the prediction of time-series concentrations of herbicides in river water with diffuse-pollution hydrological models, farming schedules (the dates of herbicide application and drainage of irrigation water from rice paddies) greatly affect the runoff behavior of the herbicides. For large catchments, obtaining precise data on farming schedules is impractical, and so the model input inevitably includes substantial uncertainty. This paper evaluates the effectiveness of using the Monte-Carlo method to generate sets of estimated farming schedules to use as input to a GIS-based basin-scale runoff model to predict the concentrations of paddy-farming herbicides in river water. The effects of using the Monte-Carlo method to compensate for uncertainty in the evaluated parameters for herbicide decomposition and sorption were also evaluated.
机译:在使用弥散污染水文模型预测河水中除草剂的时间序列浓度时,耕作时间表(除草剂的施用日期和稻田灌溉用水的排放日期)极大地影响了除草剂的径流行为。对于大流域,获取有关农业计划的精确数据是不切实际的,因此模型输入不可避免地会包含很大的不确定性。本文评估了使用蒙特卡洛方法生成估计的农业计划集以用作基于GIS的流域规模径流模型以预测河水中稻田除草剂浓度的有效性。还评估了使用蒙特卡洛方法来补偿除草剂分解和吸附评估参数不确定性的影响。

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