Coagulation is the most commonly used chemical treatment process that is used to remove contaminants from drinking water. In this study, the Log‐Dose‐Response (LDR) model and theoretical isotherm models (Langmuir and Freundlich) were employed to predict the DOC removal in the coagulation process during La Nina events. The six months water samples were collected during an intense La Niña cycle at various locations along the River Murray and elsewhere in South Australia. The Jar testing was conducted with different Alum dose and pH levels, that is, at 5.5, 6.0 and 7.0. The result indicates that the optimum dose of Alum for DOC removal is 15.0 mg/L and the LDR model is the best one for predicting the DOC removal in the coagulation process. The mean of standard error for this model is less than 5% for all pHs compared to Langmuir and Freundlich predictions with a value of 11% and 8%, respectively. Moreover, the standard deviation for the LDR model was low at 2.49, 1.22 and 0.75 for pH 5.5, pH 6.0 and pH 7.0, respectively.

中文翻译：

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比较对数响应曲线和吸附等温线模型以去除La Nina事件期间的溶解有机物

混凝是最常用的化学处理工艺，可用于去除饮用水中的污染物。在这项研究中，采用对数剂量反应（LDR）模型和理论等温线模型（Langmuir和Freundlich）来预测拉尼娜事件期间凝血过程中的DOC去除。在强烈的拉尼娜周期中，沿着默里河沿岸的不同地点以及南澳大利亚其他地区收集了六个月的水样。Jar测试是在不同的明矾剂量和pH值（即5.5、6.0和7.0）下进行的。结果表明，明矾去除DOC的最佳剂量为15.0 mg / L，LDR模型是预测混凝过程中DOC去除的最佳模型。与Langmuir和Freundlich的预测值（分别为11％和8％）相比，该模型在所有pH值下的标准误均值均小于5％。此外，对于LDR模型，pH 5.5，pH 6.0和pH 7.0的标准偏差分别较低，分别为2.49、1.22和0.75。