LEESU, MA 102, École des Ponts, AgroParisTech, UPEC, UPE, 6-8 Avenue Blaise Pascal, 77455, Champs sur Marne Cedex 2, France.
Department of Analytical, Environmental & Geo-Chemistry (AMGC), Vrije Universiteit Brussel (VUB), Pleinlaan 2, 1050, Brussels, Belgium.
Water Res. 2017 Jan 1;108:422-431. doi: 10.1016/j.watres.2016.11.027. Epub 2016 Nov 7.
Models of runoff water quality at the scale of an urban catchment usually rely on build-up/wash-off formulations obtained through small-scale experiments. Often, the physical interpretation of the model parameters, valid at the small-scale, is transposed to large-scale applications. Testing different levels of spatial variability, the parameter distributions of a water quality model are obtained in this paper through a Monte Carlo Markov Chain algorithm and analyzed. The simulated variable is the total suspended solid concentration at the outlet of a periurban catchment in the Paris region (2.3 km), for which high-frequency turbidity measurements are available. This application suggests that build-up/wash-off models applied at the catchment-scale do not maintain their physical meaning, but should be considered as "black-box" models.
通常,城市流域尺度的径流水质模型依赖于通过小尺度实验获得的累积/冲刷公式。模型参数的物理解释通常从小尺度转置到大尺度应用。本文通过蒙特卡罗马尔可夫链算法获取了一个城市流域水质模型的参数分布,并对其进行了分析,以测试不同空间变异性水平。模拟变量是巴黎地区(2.3 公里)城郊流域出口处的总悬浮固体浓度,该流域有高频浊度测量数据。该应用表明,应用于流域尺度的累积/冲刷模型不再具有物理意义,而应被视为“黑箱”模型。