Southern California Coastal Water Research Project, 3535 Harbor Blvd., Suite 110, Costa Mesa, CA 92626, USA.
Environ Monit Assess. 2011 Sep;180(1-4):283-302. doi: 10.1007/s10661-010-1788-6. Epub 2010 Nov 27.
Accurate quantification of stormwater pollutant levels is essential for estimating overall contaminant discharge to receiving waters. Numerous sampling approaches exist that attempt to balance accuracy against the costs associated with the sampling method. This study employs a novel and practical approach of evaluating the accuracy of different stormwater monitoring methodologies using stormflows and constituent concentrations produced by a fully validated continuous simulation watershed model. A major advantage of using a watershed model to simulate pollutant concentrations is that a large number of storms representing a broad range of conditions can be applied in testing the various sampling approaches. Seventy-eight distinct methodologies were evaluated by "virtual samplings" of 166 simulated storms of varying size, intensity and duration, representing 14 years of storms in Ballona Creek near Los Angeles, California. The 78 methods can be grouped into four general strategies: volume-paced compositing, time-paced compositing, pollutograph sampling, and microsampling. The performances of each sampling strategy was evaluated by comparing the (1) median relative error between the virtually sampled and the true modeled event mean concentration (EMC) of each storm (accuracy), (2) median absolute deviation about the median or "MAD" of the relative error or (precision), and (3) the percentage of storms where sampling methods were within 10% of the true EMC (combined measures of accuracy and precision). Finally, costs associated with site setup, sampling, and laboratory analysis were estimated for each method. Pollutograph sampling consistently outperformed the other three methods both in terms of accuracy and precision, but was the most costly method evaluated. Time-paced sampling consistently underestimated while volume-paced sampling over estimated the storm EMCs. Microsampling performance approached that of pollutograph sampling at a substantial cost savings. The most efficient method for routine stormwater monitoring in terms of a balance between performance and cost was volume-paced microsampling, with variable sample pacing to ensure that the entirety of the storm was captured. Pollutograph sampling is recommended if the data are to be used for detailed analysis of runoff dynamics.
准确量化雨水污染物水平对于估算受纳水体的整体污染物排放量至关重要。存在许多采样方法,这些方法试图在采样方法相关成本与准确性之间取得平衡。本研究采用一种新颖实用的方法,使用经过全面验证的连续模拟流域模型产生的雨水流量和成分浓度来评估不同雨水监测方法的准确性。使用流域模型模拟污染物浓度的一个主要优势是,可以应用大量代表广泛条件的雨水来测试各种采样方法。通过对加利福尼亚州洛杉矶附近的 Ballona 溪 14 年来的 166 个不同大小、强度和持续时间的模拟雨水进行“虚拟采样”,评估了 78 种不同的方法。这 78 种方法可以分为四种一般策略:体积定时组合、时间定时组合、污染图采样和微采样。通过比较每个采样策略的(1)虚拟采样和每个雨水事件的真实模型事件平均浓度(EMC)的中位数相对误差(准确性)、(2)相对误差中位数或“MAD”的中位数绝对偏差(精度)以及(3)采样方法在 10%范围内的雨水比例,评估了每种采样策略的性能。最后,估算了每种方法的现场设置、采样和实验室分析的相关成本。污染图采样在准确性和精度方面均优于其他三种方法,但成本最高。时间定时采样始终低估,而体积定时采样则高估了雨水 EMC。微采样的性能在成本大幅降低的情况下接近污染图采样。从性能和成本之间的平衡角度来看,用于常规雨水监测的最有效方法是体积定时微采样,并采用可变的采样定时以确保捕获整个雨水事件。如果数据要用于径流动态的详细分析,则推荐使用污染图采样。