Statistical methods of random selection were applied to the problem of water quality
sampling in distribution systems. A sampling methodology was developed to address
sampling goals using a statistical framework, thereby increasing the reliability of sample
data by including estimation of standard errors and confidence levels. The technique of
stratification was used to categorize locations and sampling times within the distribution
system and several different schemes for allocation of the samples among the strata were
investigated.
The sampling methodology was applied to a case-study distribution system, the City of
Durham, North Carolina, which serves approximately 150,000 customers. The goal of the case study
application was to assess the effect of sampling location, time of sample collection, and
overall sample size on the estimation of the proportion of samples with below-target
chlorine residual concentration, P.
To investigate the effectiveness of different sampling designs, expensive and time-consuming
sampling programs are often undertaken. However, for this study the
analysis was performed using numerical experiments based on a synthetic data set
derived from a free chlorine model of the distribution system (EPANET2). Includes 2 references, tables, figure.
| Edition : | Vol. - No. |
| File Size : | 1
file
, 240 KB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 5 |
| Published : | 06/17/2004 |
