This work investigates the effectiveness of different forms of management policy implemented to reduce the negative impact of bacterially polluted marine coastal swimming waters on the health and welfare of visitors to two beaches in Orange County, CA as well as to the broader society that pays to implement these management policies. The main drawbacks to current beach management practices in southern California are three-fold: data accuracy is questionable due to the long time delays involved in culture-based testing methods, the timeliness of health risk information delivery is poor chiefly as a consequence of slow testing methods, and compliance with warning information is poorly understood and generally observed to be 50% or less.
Beach management policies under consideration in this analysis are derived from variations in four dimensions of beach management choice: level of gradation in health risk warning information, timeliness of information delivery, type of water quality monitoring test used, and frequency of water quality testing. All of these polices are considered for two beaches in Orange County. Huntington State Beach and Huntington City Beach that together cover a 7.5 km stretch of publicly accessible coastline starting just north of the outlet of the Santa Ana River.
A three-part model of beach visitor behavior is constructed to predict gross daily attendance at each of the two beaches, the fraction of these beach attendees who initially intend to swim in the ocean during their visit, and the likelihood that these visitors will comply with posted health risk warning signs and choose not to swim despite their original (pre-warning) intention. These three dependent variables were estimated on a combination of environmental data collected by established in-situ instrumentation with publicly retrievable telemetry and population-specific behavioral and attitudinal data collected by survey interviewers in the summer of 2005 as part of the present work.
A water quality model was developed in order to provide forecast and nowcast predictions of the concentration of one fecal indicator bacteria group, enterococci. The results of this model were applied to policies that used model predictions either instead or in conjunction with water quality monitoring in order to improve the accuracy of warning information and reduce the costs incurred by the testing itself as well as the negative consequences of faulty information.
A welfare model was constructed to determine the posting status and health risk at the beach sites, then to calculate four outcome metrics using inputs from the behavioral and water quality models. The welfare model factors calculated for each beach site and day are: relative risk, posting status, number of swimmers and number of illnesses. The four outcome metrics determined by the welfare model are: Societal Net Benefit, Personal Net Benefit, Illness Rate, and Risk-Weighted Marginal Cost. A total of 37 policies were derived from variations in the four dimensions of management choice, and these policies were compared using the four calculated outcome metrics.
Overall results of the policy comparison suggest that, as applied to conditions at the two beaches under consideration, a balanced improvement in outcome metrics can be achieved through the following choices in each of the four management dimensions:
Health risk information should be delivered to the public with an additional level of refinement by using a graded three-level warning system rather than a simple binary (safe/not safe) warning; additionally, new advanced tests should be applied that allow results to be returned in as little as three hours despite the additional cost of such tests; these tests should be applied adaptively as water quality varies, with more frequent tests as water quality worsens; finally, the warning information should be supplied only for the current beach day (a nowcast) rather than for the following day as a forecast, which would limit the accuracy of the warning.