Wyer Mark D, Kay David, Morgan Huw, Naylor Sam, Clark Simon, Watkins John, Davies Cheryl M, Francis Carol, Osborn Hamish, Bennett Sarah
Department of Geography and Earth Sciences, Llandinam Building, Aberystwyth University, SY23 3DB, UK.
Place, Housing and Public Protection Services, Pollution Control, Swansea Council, The Guildhall, Swansea, SA1 4PE, UK.
Water Res X. 2018 Nov 3;1:100006. doi: 10.1016/j.wroa.2018.10.003. eCollection 2018 Dec 1.
Prediction of bathing water quality is recommended by the World Health Organization (WHO), the European Union (EU) and the United States Environmental Protection Agency (USEPA) and is an established element in bathing water management designed to protect public health. Most commonly, historical regulatory compliance data are used for model calibration and provide the dependent variable for modelling. Independent (or predictor) variables (e.g. rainfall, river flow and received irradiance) measured over some antecedent period are used to deliver prediction of the faecal indicator concentration measured on the day of the regulatory sample collection. The implied linked assumptions of this approach are, therefore, that; (i) the independent variables accurately predict the bathing-day water quality; which is (ii) accurately characterized by the single regulatory sample. Assumption (ii) will not be the case where significant within-day variability in water quality is evident. This study built a detailed record of water quality change through 60 days at a UK coastal bathing water in 2011 using half-hourly samples each subjected to triplicate filtration designed to enhance enumeration precision. On average, the mean daily variation in FIO concentrations exceeded 1 log order, with the largest daily variations exceeding 2 log orders. Significant diurnality was observed at this bathing water, which would determine its EU Directive compliance category if the regulatory samples were collected at the same time each day. A sampling programme of this intensity has not been reported elsewhere to date and, if this pattern is proven to be characteristic of other bathing waters world-wide, it has significance for: (a) the design of regulatory sampling programmes; (b) the use of historical data to assess compliance, which often comprises a single sample taken at the compliance point on a regular, often weekly, basis; and (c) the use of regulatory compliance data to build predictive models of water quality.
世界卫生组织(WHO)、欧盟(EU)和美国环境保护局(USEPA)都建议对浴场水质进行预测,这是浴场水管理中为保护公众健康而确立的一项内容。最常见的是,利用历史监管合规数据进行模型校准,并为建模提供因变量。在某个前期测量的自变量(或预测变量)(例如降雨量、河流流量和接收辐照度)用于预测在监管样本采集当天测量的粪便指示物浓度。因此,这种方法隐含的相关假设是:(i)自变量能准确预测浴场日水质;(ii)单一监管样本能准确表征浴场日水质。如果水质在一天内存在明显的显著变化,假设(ii)就不成立。本研究通过对2011年英国一个沿海浴场水质变化进行了为期60天的详细记录,每半小时采集一次样本,每个样本进行三次重复过滤以提高计数精度。平均而言,粪便指示物浓度的日均变化超过1个对数级,最大日变化超过2个对数级。在这个浴场观察到了显著的日变化,如果每天在同一时间采集监管样本,这种日变化将决定其是否符合欧盟指令类别。迄今为止,其他地方尚未报道过如此密集的采样计划,如果这种模式被证明是全球其他浴场的特征,那么它对以下方面具有重要意义:(a)监管采样计划的设计;(b)利用历史数据评估合规情况,历史数据通常包括在合规点定期(通常每周)采集的单个样本;(c)利用监管合规数据建立水质预测模型。