Mietzel T, Frehmann T, Geiger W F, Schilling W
University of Essen, Urban Water Management, Universitätsstr. 15,45141 Essen, Germany.
Water Sci Technol. 2003;47(2):165-70.
Norwegian receiving waters are of such high water quality that authorities consider opening them for bathing. The leading parameter to monitor the quality of bathing waters is fecal coliform bacteria (FC). For this parameter no rapid detection method is available. The main objective of this case study was to find a way to quickly predict bacteria contamination by observing different online parameters such as flow, conductivity or spectral absorption coefficient (SAC). In this study historical data from 1994 to 2000 was analyzed, and over a period of five weeks water samples were taken and analyzed for bacteria. The analysis of the historical data revealed fundamental sampling problems, which made the data useless for the purpose of this study. The analysis of the data collected for this study showed that exceeding the bathing water standard for bacteria can be predicted by evaluating the SAC with an acceptable accuracy. Furthermore a simple river quality model was implemented, including bacteria as a load fraction. With the help of rain data and discharge predictions expected bacteria numbers exceeding the bathing water standard could also be forecast.
挪威的受纳水体水质极高，当局考虑开放这些水域用于游泳。监测游泳水域水质的主要参数是粪大肠菌群（FC）。对于该参数，尚无快速检测方法。本案例研究的主要目的是找到一种方法，通过观察不同的在线参数，如流量、电导率或光谱吸收系数（SAC），快速预测细菌污染情况。在本研究中，分析了1994年至2000年的历史数据，并在五周的时间内采集水样并分析其中的细菌。对历史数据的分析揭示了基本的采样问题，这使得这些数据对本研究毫无用处。对本研究收集的数据进行分析表明，通过评估SAC可以以可接受的准确度预测细菌是否超过游泳水域标准。此外，还实施了一个简单的河流质量模型，将细菌作为负荷分数纳入其中。借助降雨数据和流量预测，也可以预测预期超过游泳水域标准的细菌数量。
