Parameter uncertainty-based pattern identification and optimization for   robust decision making on watershed load reduction

doi:10.1016/j.jhydrol.2017.02.035

CORC > 北京大学 > 环境科学与工程学院

	Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction
	Jiang, Qingsong ; Su, Han ; Liu, Yong ; Zou, Rui ; Ye, Rui ; Guo, Huaicheng
刊名	JOURNAL OF HYDROLOGY
	2017
关键词	Parameter uncertainty Pattern identification Robustness Decision preference Hybrid clustering analysis Lake Bali K-MEANS QUALITY MODEL AUTOMATIC CALIBRATION CLUSTERING-ALGORITHM CLIMATE-CHANGE MANAGEMENT RELIABILITY NETWORKS SENSITIVITY STORMWATER
DOI	10.1016/j.jhydrol.2017.02.035
英文摘要	Nutrients loading reduction in watershed is essential for lake restoration from eutrophication. The efficient and optimal decision-making on loading reduction is generally based on water quality modeling and the quantitative identification of nutrient sources at the watershed scale. The modeling process is influenced inevitably by inherent uncertainties, especially by uncertain parameters due to equifinality. Therefore, the emerging question is: if there is parameter uncertainty, how to ensure the robustness of the optimal decisions? Based on simulation-optimization models, an integrated approach of pattern identification and analysis of robustness was proposed in this study that focuses on the impact of parameter uncertainty in water quality modeling. Here the pattern represents the discernable regularity of solutions for load reduction under multiple parameter sets. Pattern identification is achieved by using a hybrid clustering analysis (i.e., Ward-Hierarchical and K-means), which was flexible and efficient in analyzing Lake Bali near the Yangtze River in China. The results demonstrated that urban domestic nutrient load is the most potential source that should be reduced, and there are two patterns for Total Nitrogen (TN) reduction and three patterns for Total Phosphorus (TP) reduction. The patterns indicated different total reduction of nutrient loads, which reflect diverse decision preferences. The robust solution was identified by the highest accomplishment with the water quality at monitoring stations that were improved uniformly with this solution. We conducted a process analysis of robust decision-making that was based on pattern identification and uncertainty, which provides effective support for decision making with preference under uncertainty. (C) 2017 Elsevier B.V. All rights reserved.; National Basic Research Program of China [2015CB458900]; China National Water Pollution Control Program [2013ZX07102-006]; SCI(E); ARTICLE; 708-717; 547
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/474299]
专题	环境科学与工程学院
推荐引用方式 GB/T 7714	Jiang, Qingsong,Su, Han,Liu, Yong,et al. Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction[J]. JOURNAL OF HYDROLOGY,2017.
APA	Jiang, Qingsong,Su, Han,Liu, Yong,Zou, Rui,Ye, Rui,&Guo, Huaicheng.(2017).Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction.JOURNAL OF HYDROLOGY.
MLA	Jiang, Qingsong,et al."Parameter uncertainty-based pattern identification and optimization for robust decision making on watershed load reduction".JOURNAL OF HYDROLOGY (2017).