Several manure-borne microorganism removal models have been developed to provide accurate estimations of the number of microorganisms removed from manure or manured soils undergoing rainfall. It has been commonly assumed that these models perform equally well when used to simulate microbe removal in runoff from manures of different consistency and levels of weathering. The objectives of this work were (a) to observe kinetics of the removal of Escherichia coli and enterococci with runoff for two different manure consistencies and three manure weathering durations, and (b) to compare performance of the log-linear, Vadas-Kleinman-Sharpley, and Bradford-Shijven models in simulation of the observed kinetics. Liquid and solid dairy manure were applied to grassed soil boxes that received simulated rainfall immediately after application and subsequently at 1 and 2 wk. Runoff samples were collected for 1 h at increasing time intervals during each event. Only the effective rainfall depth at the start of runoff was significantly affected by manure consistency (p = .033), whereas other parameters were not (p > .05). Substantial differences in microorganism removal kinetics during the initial, 1-, and 2-wk rainfall events were manifested by the significant (p < .05) effect of the degree of manure weathering in about 70% of cases. The log-linear model produced the largest fitting error especially during the initial rainfall event. The Vadas-Kleinman-Sharpley model and the Bradford-Schijven model were comparable in accuracy for all events. The latter model was slightly more accurate, and the former model had better expressed dependencies of parameter values on manure weathering. Ignoring manure weathering may lead to incorrect parameterization of manure removal models.

中文翻译：

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模拟径流中粪便中粪便指示剂去除的动力学

已经开发了几种粪便传播的微生物去除模型，以准确估计从粪便或经过降雨的粪肥土壤中去除的微生物数量。人们普遍认为，这些模型在用于模拟来自不同稠度和风化程度的粪便径流中的微生物去除时，表现同样出色。这项工作的目的是 (a) 观察两种不同粪便浓度和三种粪便风化持续时间下去除大肠杆菌和肠球菌的动力学，以及 (b) 比较对数线性、Vadas-Kleinman- Sharpley 和 Bradford-Sijven 模型模拟观察到的动力学。液体和固体乳制品肥料被施加到草地土壤箱中，在施加后立即接受模拟降雨，随后在第 1 周和第 2 周接受模拟降雨。在每个事件期间以增加的时间间隔收集径流样品 1 小时。只有径流开始时的有效降雨深度受粪便稠度的显着影响 (p = .033)，而其他参数不受 (p > .05) 的影响。在大约 70% 的情况下，粪便风化程度的显着影响 (p < .05) 表明，在最初、1 周和 2 周降雨事件期间微生物去除动力学的显着差异。对数线性模型产生最大的拟合误差，尤其是在初始降雨事件期间。Vadas-Kleinman-Sharpley 模型和 Bradford-Schijven 模型在所有事件的准确性上具有可比性。后一种模型精度稍高，前一种模型更好地表达了参数值对粪便风化的依赖性。忽略粪便风化可能会导致粪便清除模型的参数化不正确。