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Accounting for sensor calibration, data validation, measurement and sampling uncertainties in monitoring urban drainage systems [Review]

机译:在监测城市排水系统中考虑传感器校准,数据验证,测量和采样不确定性[综述]

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摘要

Assessing the functioning and the performance of urban drainage systems on both rainfall event and yearly time scales is usually based on online measurements of flow rates and on samples of influent and effluent for some rainfall events per year. In order to draw pertinent scientific and operational conclusions from the measurement results, it is absolutely necessary to use appropriate methods and techniques in order to i) calibrate sensors and analytical methods, ii) validate raw data, iii) evaluate measurement uncertainties, iv) evaluate the number of rainfall events to sample per year in order to determine performance indicator with a given uncertainty. Based on previous work, the paper gives a synthetic review of required methods and techniques, and illustrates their application to storage and settling tanks. Experiments show that, despite controlled and careful experimental conditions, relative uncertainties are about 20% for flow rates in sewer pipes, 6-10% for volumes, 25-35% for TSS concentrations and loads, and 18-276% for TSS removal rates. In order to evaluate the annual pollutant interception efficiency of storage and settling tanks with a given uncertainty, efforts should first be devoted to decrease the sampling uncertainty by increasing the number of sampled events. [References: 7]
机译:通常基于在线流量测量以及每年某些降雨事件的进水和出水样本评估城市排水系统在降雨事件和年度时间尺度上的功能和性能。为了从测量结果中得出相关的科学和操作结论,绝对有必要使用适当的方法和技术来i)校准传感器和分析方法,ii)验证原始数据,iii)评估测量不确定度,iv)评估为了确定具有给定不确定性的绩效指标,每年要采样的降雨事件的数量。在先前工作的基础上,本文对所需的方法和技术进行了综合综述,并说明了其在存储和沉淀池中的应用。实验表明,尽管实验条件受控且谨慎,但下水道流量的相对不确定度约为20%,体积的不确定度为6-10%,TSS浓度和负荷的相对不确定度为25-35%,TSS去除率为18-276% 。为了评估在给定不确定性的情况下储存和沉淀池的年度污染物截留效率,首先应致力于通过增加采样事件的数量来减少采样不确定性。 [参考:7]

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