基于粪便污染指标的台场海洋公园某海滩水质预报系统试运行

Chizuru Kitayama, Kenji Morita, H. Fukuchi, SungAe Lee, H. Furumai
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引用次数: 0

摘要

雨水过后,在城市滨水区观察到合流下水道溢流造成的粪便污染,导致粪便污染水平超过洗浴用水质量标准。为了保证城市滨水区的可游泳性,有必要对粪便污染情况进行预测,以确保安全沐浴。因此,我们旨在开发台场海洋公园海滩的水质预报系统,以大肠杆菌为粪便指标,确定人们在洗澡当天是否可以将脸浸入海水中。首先,利用聚类分析方法对东京都23个城市近10年的降水事件进行了时空分布特征分类。然后,使用三维水动力和水质模型计算了每个分类降雨组的公园内大肠杆菌浓度变化。利用不同潮汐条件下的计算结果,建立了大肠杆菌浓度变化数据库。结果表明,利用数据库预测的相应降雨组的大肠杆菌浓度与利用模型计算的浓度峰值在安全范围内一致。利用构建的数据库,我们于2018年对海滩水质预报系统进行了试运行,验证了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Trial Operation of Water-quality Forecasting System Based on Fecal Pollution Indicators for a Beach in Odaiba Marine Park
Fecal pollution caused by combined sewer overflows has been observed at urban waterfronts after rainfall and results in fecal pollution levels exceeding bathing water quality standards. To guarantee the swimmablility of urban waterfronts, it is necessary to predict the situation of fecal contamination to ensure safe bathing. Therefore, we aimed to develop a water-quality forecasting system for the beach in Odaiba Marine Park using Escherichia coli as a fecal indictor to determine whether people can submerge their faces in the seawater on the day of bathing. First, rainfall events in the 23 cities of Tokyo over the past 10 years were categorized by cluster analysis, considering their temporospatial distribution characteristics. Then, E. coli concentration changes in the park were calculated using a 3D hydrodynamic and water-quality model for each categorized rainfall group. Using the calculation results for various tidal conditions, we constructed a database of E. coli concentration changes. It was confirmed that the E. coli concentration predicted using the database for a corresponding rainfall group agrees with the concentration peak calculated using the model within a safe margin. Using the constructed database, we carried out a trial operation of the water-quality forecasting system for the beach in 2018 and verified its effectiveness.
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