Department of Civil Engineering and eWater CRC, Institute for Sustainable Water Resources, Monash University, Victoria 3800, Australia.
Water Sci Technol. 2010;62(4):837-43. doi: 10.2166/wst.2010.325.
The complex nature of pollutant accumulation and washoff, along with high temporal and spatial variations, pose challenges for the development and establishment of accurate and reliable models of the pollution generation process in urban environments. Therefore, the search for reliable stormwater quality models remains an important area of research. Model calibration and sensitivity analysis of such models are essential in order to evaluate model performance; it is very unlikely that non-calibrated models will lead to reasonable results. This paper reports on the testing of three models which aim to represent pollutant generation from urban catchments. Assessment of the models was undertaken using a simplified Monte Carlo Markov Chain (MCMC) method. Results are presented in terms of performance, sensitivity to the parameters and correlation between these parameters. In general, it was suggested that the tested models poorly represent reality and result in a high level of uncertainty. The conclusions provide useful information for the improvement of existing models and insights for the development of new model formulations.
污染物积累和冲刷的复杂性，以及高时空变化，给开发和建立城市环境中污染产生过程的准确可靠模型带来了挑战。因此，寻找可靠的雨水质量模型仍然是一个重要的研究领域。为了评估模型性能，对这些模型进行校准和敏感性分析是至关重要的；未经校准的模型不太可能得出合理的结果。本文报告了对旨在代表城市集水区污染物产生的三个模型的测试。使用简化的蒙特卡罗马尔可夫链 (MCMC) 方法对模型进行评估。结果以性能、对参数的敏感性以及这些参数之间的相关性表示。一般来说，测试的模型被认为不能很好地反映现实，导致高度不确定性。结论为改进现有模型提供了有用的信息，并为开发新的模型配方提供了思路。
