Wang Hui, Liu Zhe, Sun Lina, Luo Qing
Key Laboratory of Regional Environment and Eco-Remediation, Ministry of Education, Shenyang University, Shenyang, Liaoning Province, 110044, China.
Key Laboratory of Pollution Ecology and Environment Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning Province, 110016, China.
PLoS One. 2015 May 29;10(5):e0127535. doi: 10.1371/journal.pone.0127535. eCollection 2015.
The objective of this study is to optimize the river monitoring network in Taizihe River, Northeast China. The situation of the network and water characteristics were studied in this work. During this study, water samples were collected once a month during January 2009 - December 2010 from seventeen sites. Futhermore, the 16 monitoring indexes were analyzed in the field and laboratory. The pH value of surface water sample was found to be in the range of 6.83 to 9.31, and the average concentrations of NH4(+)-N, chemical oxygen demand (COD), volatile phenol and total phosphorus (TP) were found decreasing significantly. The water quality of the river has been improved from 2009 to 2010. Through the calculation of the data availability and the correlation between adjacent sections, it was found that the present monitoring network was inefficient as well as the optimization was indispensable. In order to improve the situation, the matter element analysis and gravity distance were applied in the optimization of river monitoring network, which were proved to be a useful method to optimize river quality monitoring network. The amount of monitoring sections were cut from 17 to 13 for the monitoring network was more cost-effective after being optimized. The results of this study could be used in developing effective management strategies to improve the environmental quality of Taizihe River. Also, the results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems.
本研究的目的是优化中国东北太子河的河流监测网络。在这项工作中,研究了该网络的情况和水体特征。在2009年1月至2010年12月期间,每月从17个站点采集一次水样。此外,在现场和实验室对16项监测指标进行了分析。发现地表水水样的pH值在6.83至9.31范围内,并且NH4(+)-N、化学需氧量(COD)、挥发酚和总磷(TP)的平均浓度显著下降。从2009年到2010年,该河流水质有所改善。通过计算数据可用性和相邻断面之间的相关性,发现当前的监测网络效率低下,因此优化是必不可少的。为了改善这种情况,在河流监测网络优化中应用了物元分析和重心距离法,事实证明这是一种优化河流水质监测网络的有效方法。优化后的监测网络更具成本效益,监测断面数量从17个减少到了13个。本研究结果可用于制定有效的管理策略,以改善太子河的环境质量。此外,结果表明所提出的模型可有效地用于河流系统监测网络的优化设计。