Integrated PCA-BN Approach for Identifying the Water Quality Response Patterns for Lakes in Yunnan Plateau

doi:10.13209/j.0479-8023.2017.113

Abstract

Abstract:

An integrated approach of principle components analysis (PCA) and Bayesian network (BN) for identify- ing the response pattern of different clusters were developed to understand sensitive relationships of water quality in lakes of Yunnan Plateau. The model includes four steps: data preconditioning, lakes clustering with PCA, Bayesian network learning and lake water quality response modeling. The results demonstrate that the 26 lakes can be clustered into two groups; the Chl a concentration responds more significantly to Total Nitrogen (TN) and Total Phosphorus (TP) in the first group, mainly resulting from much higher watershed disturbances; the Dissolved Oxygen (DO) in the first group with higher water temperature is close to saturation and have little change with Chl a increasing, while the second group is not; and there is good consistency on the relationship between Transpa-rency (SD)and Chl a in both groups.

Key words: plateau lakes, water quality, clustering, response pattern, principle components analysis, Bayesian network

摘要：

为探究湖泊群水质变量的响应模式, 构建适用于监测数据匮乏的湖泊群聚类和响应模式识别方法体系(PCA-BN), 包括4个步骤: 数据预处理、PCA降维与湖泊聚类、贝叶斯网络构建及参数学习、湖泊响应关系模拟。以云南高原湖泊群为例开展研究, 结果表明: 所研究的26个湖泊可分为两类; 由于第一类湖泊受到的人为干扰更严重, 因而叶绿素a对总氮和总磷的响应比第二类湖泊更敏感; 第一类湖泊表层水温高, 溶解氧趋近饱和, 随叶绿素a变化不显著, 第二类湖泊溶解氧随叶绿素a升高而显著升高; 两类湖泊的透明度与叶绿素a的关系一致。

关键词: 湖泊群, 水质, 聚类, 响应模式, 主成分分析, 贝叶斯网络

Qingsong JIANG, Zhongyao LIANG, Lei ZHAO, Yuzhao LI, Sifeng WU, Yong LIU. Integrated PCA-BN Approach for Identifying the Water Quality Response Patterns for Lakes in Yunnan Plateau[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2017, 53(5): 948-956.

蒋青松, 梁中耀, 赵磊, 李玉照, 吴思枫, 刘永. 云南高原湖泊群的统计学聚类识别及水质响应模式研究[J]. 北京大学学报自然科学版, 2017, 53(5): 948-956.

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URL: https://xbna.pku.edu.cn/EN/10.13209/j.0479-8023.2017.113

https://xbna.pku.edu.cn/EN/Y2017/V53/I5/948

Figures/Tables 8

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统计量	WT/ºC	DO/(mg · L^-1)	SD/m	TN/(mg · L^-1)	TP/(mg · L^-1)	Chl a/(mg · L^-1)	COD_Mn/(mg · L^-1)
平均值	21.39	7.155	2.569	0.544	0.039	0.008	4.626
标准差	3.61	2.020	2.726	0.532	0.042	0.009	2.668
变异系数	0.17	0.282	1.061	0.978	1.070	1.147	0.577
最小值	14.57	2.033	0.367	0.050	0.005	0.0004	0.900
最大值	28.67	13.400	11.933	1.998	0.167	0.035	11.600

统计量	WT/ºC	DO/(mg · L^-1)	SD/m	TN/(mg · L^-1)	TP/(mg · L^-1)	Chl a/(mg · L^-1)	COD_Mn/(mg · L^-1)
平均值	21.39	7.155	2.569	0.544	0.039	0.008	4.626
标准差	3.61	2.020	2.726	0.532	0.042	0.009	2.668
变异系数	0.17	0.282	1.061	0.978	1.070	1.147	0.577
最小值	14.57	2.033	0.367	0.050	0.005	0.0004	0.900
最大值	28.67	13.400	11.933	1.998	0.167	0.035	11.600

主成分载荷表	主成分1	主成分2
DO		0.915
SD	0.438
TN	-0.438
TP	-0.454	-0.237
Chl a	-0.431	0.225
COD_Mn	-0.464	-0.207
方差贡献率	0.587	0.181
累积方差贡献率	0.587	0.768

主成分载荷表	主成分1	主成分2
DO		0.915
SD	0.438
TN	-0.438
TP	-0.454	-0.237
Chl a	-0.431	0.225
COD_Mn	-0.464	-0.207
方差贡献率	0.587	0.181
累积方差贡献率	0.587	0.768

类别	R	特征	湖泊聚类结果
一	>1	人为干扰影响较大	滇池、阳宗海、洱海、抚仙湖、泸沽湖、摆龙湖、三角海、大屯海、海西海、普者黑、清水海、茈碧湖、月湖、草海湿地、长桥海
二	<1	人为干扰影响较小	碧塔海、海峰湿地、剑湖、拉市海、纳帕海、青海湖、蜀都湖、天池、西湖、长湖