How geostatistics can help you find lead and galvanized water service lines: The case of Flint, MI.
How geostatistics can help you find lead and galvanized water service lines: The case of Flint, MI.
复制标题
地质统计学如何帮助您找到铅和镀锌供水管道：以密歇根州弗林特为例。
DOI：
10.1016/j.scitotenv.2017.05.094
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Goovaerts,Pierre
中科院分区：
文献类型：
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作者：
Goovaerts,Pierre
在弗林特饮用水危机之后，大多数美国城市都在争先恐后地在其供水系统中找到所有铅服务线（LSL）。这一信息往往不准确或缺乏，但对于评估铅铜规则的遵守情况和计划更换弗林特目前正在进行的铅和镀锌服务线至关重要。本文提出了第一种基于相邻字段数据（即，房屋检查）和次要信息（即，建筑年份和城市记录）。该方法适用于弗林特市的3254家已被密歇根州环境质量部检查，以确定服务线材料。GSL和LSL主要分别在1934年之前和二战期间建造的房屋中观察到。城市记录导致LSL的过度识别，可能是因为旧的记录没有更新，因为这些线路正在被替换。指标半变异函数表明，这两种类型的服务线在空间上聚集的范围为1.4公里的LSL和2.8公里的GSL。这种空间自相关性与使用残差指示克里金法的二级数据相结合，以预测在税收地块级别找到每种材料的概率。使用受试者工作特征（ROC）曲线的交叉验证分析表明，相对于目前针对40年代建造的房屋的方法，克里金模型的准确性更高;特别是随着更多的实地数据变得可用。计算不同采样策略的假阳性率和检测百分比。这种方法非常灵活，可以容纳更多的信息来源，例如当地法规和监管变更、历史许可记录、维护和操作记录或客户自我报告。
In the aftermath of Flint drinking water crisis, most US cities have been scrambling to locate all lead service lines (LSLs) in their water supply systems. This information, which is most often inaccurate or lacking, is critical to assess compliance with the Lead and Copper Rule and to plan the replacement of lead and galvanized service lines (GSLs) as currently under way in Flint. This paper presents the first geospatial approach to predict the likelihood that a home has a LSL or GSL based on neighboring field data (i.e., house inspection) and secondary information (i.e., construction year and city records). The methodology is applied to the City of Flint where 3254 homes have been inspected by the Michigan Department of Environmental Quality to identify service line material. GSLs and LSLs were mostly observed in houses built prior to 1934 and during World War II, respectively. City records led to the over-identification of LSLs, likely because old records were not updated as these lines were being replaced. Indicator semivariograms indicated that both types of service line are spatially clustered with a range of 1.4 km for LSLs and 2.8 km for GSLs. This spatial autocorrelation was integrated with secondary data using residual indicator kriging to predict the probability of finding each type of material at the tax parcel level. Cross-validation analysis using Receiver Operating Characteristic (ROC) Curves demonstrated the greater accuracy of the kriging model relative to the current approach targeting houses built in the forties; in particular as more field data become available. Anticipated rates of false positives and percentages of detection were computed for different sampling strategies. This approach is flexible enough to accommodate additional sources of information, such as local code and regulatory changes, historical permit records, maintenance and operation records, or customer self-reporting.