• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of the American Water Resources Association >Estimating upper percentiles of surface water monitoring data with sparse samples
【24h】

Estimating upper percentiles of surface water monitoring data with sparse samples

机译：Estimating upper percentiles of surface water monitoring data with sparse samples

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相关主题

摘要

The estimation of upper percentiles of chemical concentrations in surface water systemswithin sites and regions may be necessary for the assessment of potential risk toecosystems and human health. Limited sample sizes at monitoring sites often limit theuse of direct methods to estimate upper percentiles. In such cases, upper percentileswithin regions within a time frame may be estimated by pooling data across sites andyears, and then deriving percentile estimates from the pooled dataset. The methoduses the observations resulting from either a known probability-samplingdesign ora sampling design treated like one because its observations come close to matchingthat of a probability-sample.These observations are then weighted to ensurethat estimates are representative of a target population across all the sites withinthe region and the range of years in the time frame. This method of estimating upperpercentiles of annual site concentration profiles is demonstrated using atrazine andvalidated using the monitoring data from both sparsely sampled and high-frequencywater monitoring programs, where point and interval estimates of the 90th, 95th, and99th pooled population percentiles are provided. This method shows that the pooleddata from multiple sparse datasets can be used to provide estimates of near-peakconcentrations with greater certainty, which are consistent with those generated byhigh-frequencysampling monitoring programs.

著录项

获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号