Public Mis-Notification of Coastal Water Quality:  A Probabilistic Evaluation of Posting Errors at Huntington Beach, California

Abstract

Whenever measurements of fecal pollution in coastal bathing waters reach levels that might pose a significant health risk, warning signs are posted on public beaches in California. Analysis of historical shoreline monitoring data from Huntington Beach, southern California, reveals that protocols used to decide whether to post a sign are prone to error. Errors in public notification (referred to here as posting errors) originate from the variable character of pollutant concentrations in the ocean, the relatively infrequent sampling schedule adopted by most monitoring programs (daily to weekly), and the intrinsic error associated with binary advisories in which the public is either warned or not. In this paper, we derive a probabilistic framework for estimating posting error rates, which at Huntington Beach range from 0 to 41%, and show that relatively high sample-to-sample correlations (>0.4) are required to significantly reduce binary advisory posting errors. Public mis-notification of coastal water quality can be reduced by utilizing probabilistic approaches for predicting current coastal water quality, and adopting analog, instead of binary, warning systems.

Comparison of Fecal Indicator Bacteria Densities in Marine Recreational Waters by QPCR

“…Measurements of these FIB groups, however, are still performed by culture methods that produce results the next day. During this time, public exposure to waters of unacceptable quality may have already occurred (Kim and Grant 2004). More rapid methods are needed that can alert monitoring authorities of unsafe recreational waters on the same day samples are collected.…”

Noroviruses Surrogate Detection Using Loop-Mediated Isothermal Amplification (LAMP), Conventional RT-PCR and Quantitative RT-PCR in Sg. Tekala and Sg. Gabai Stream Water

“…Although this technique is being used for water quality criteria [7], it has limitation in protecting the public from recreational waterborne disease especially viruses infection. The requirement of 18 to 24 hours of virus incubation postexposure prior to issue advisory on infectivity may increased the greater risk of infection [8,9]. Another drawback of using FIB as indicator is that these bacteria has been reported to continuously grow in the environment, leads to a bias in assessment especially in tropical weather like Malaysia [10][11][12].…”

Improvements to Shellfish Harvest Area Closure Decision Making Using GIS, Remote Sensing, and Predictive Models

“…Fecal bacteria models have been attempted in limited applications for beach recreation areas (Olyphant et al 2003;Kim and Grant 2004;Olyphant and Whitman 2004), stormwater ponds (Siewicki et al 2007), and in previous shellfish management settings (Kelsey et al 2004). Important predictors in these models varied, but included precipitation, tide variables, water temperature, air temperature, salinity, and wind (Kelsey et al 2004;Kim and Grant 2004;Olyphant and Whitman 2004).…”

“…Important predictors in these models varied, but included precipitation, tide variables, water temperature, air temperature, salinity, and wind (Kelsey et al 2004;Kim and Grant 2004;Olyphant and Whitman 2004). Accurate prediction of current (now-cast) or future (forecast) bacteria concentrations in surface waters could enable proactive decision making, which would represent a significant advance in coastal resource regulation and management (Olyphant et al 2003;Olyphant and Whitman 2004).…”