Université Paris-Est, LEESU, UMR-MA 102, UPEC, UPEMLV, ENPC, Agro ParisTech, 6 et 8 avenue Blaise Pascal - Cité Descartes, 77455, Champs-sur-Marne, Cedex 2, France.
Faculty of Engineering III, Lebanese University, Hadath, Lebanon.
Environ Sci Pollut Res Int. 2017 Dec;24(36):28205-28219. doi: 10.1007/s11356-017-0384-5. Epub 2017 Oct 11.
This article describes a stochastic method to calculate the annual pollutant loads and its application over several years at the outlet of three catchments drained by separate storm sewers. A stochastic methodology using Monte Carlo simulations is proposed for assessing annual pollutant load, as well as the associated uncertainties, from a few event sampling campaigns and/or continuous turbidity measurements (representative of the total suspended solids concentration (TSS)). Indeed, in the latter case, the proposed method takes into account the correlation between pollutants and TSS. The developed method was applied to data acquired within the French research project "INOGEV" (innovations for a sustainable management of urban water) at the outlet of three urban catchments drained by separate storm sewers. Ten or so event sampling campaigns for a large range of pollutants (46 pollutants and 2 conventional water quality parameters: TSS and total organic carbon (TOC)) are combined with hundreds of rainfall events for which, at least one among three continuously monitored parameters (rainfall intensity, flow rate, and turbidity) is available. Results obtained for the three catchments show that the annual pollutant loads can be estimated with uncertainties ranging from 10 to 60%, and the added value of turbidity monitoring for lowering the uncertainty is demonstrated. A low inter-annual and inter-site variability of pollutant loads, for many of studied pollutants, is observed with respect to the estimated uncertainties, and can be explained mainly by annual precipitation.
本文描述了一种随机方法，用于计算由单独雨水下水道排水的三个流域出口处的年污染物负荷及其多年应用。提出了一种使用蒙特卡罗模拟的随机方法，用于评估少数事件采样活动和/或连续浊度测量（代表总悬浮固体浓度 (TSS)）的年污染物负荷及其相关不确定性。事实上，在后一种情况下，所提出的方法考虑了污染物与 TSS 之间的相关性。所开发的方法应用于法国研究项目“INOGEV”（城市水资源可持续管理的创新）在由单独雨水下水道排水的三个城市流域出口处获得的数据。结合了数十次针对多种污染物（46 种污染物和 2 种常规水质参数：TSS 和总有机碳 (TOC)）的事件采样活动和数百次降雨事件，其中至少有一个连续监测的参数（降雨强度、流速和浊度）可用。对三个流域的结果表明，年污染物负荷可以在 10%至 60%的不确定范围内进行估算，并且证明浊度监测可降低不确定性。与估计的不确定性相比，许多研究的污染物的污染物负荷具有低的年际和站点间可变性，这主要可以归因于年降水量。
