MAPPING THE SPATIAL VARIATION OF RIVERS WATER QUALITY USING MULTIVARIATE ANALYSIS. A CASE STUDY OF GREATER JAKARTA, INDONESIA

R. Yanidar, D. Hartono, S. Moersidik, Y. Andrès
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Abstract

Urban activities and runoff deteriorated the river water. Aim: This study aims to determine the primary contamination and mapping river's water quality variation in Greater Jakarta. Methodology and Results: Multivariate analysis was employed by Factor Analysis and Cluster Analysis (FA and CA) using the 12 parameters of the water quality dataset from 76 sampling stations in 19 rivers in the Greater Jakarta Region, Indonesia, between 2014 and 2015. The FA result showed that almost 66.6% of the total variance in water quality data was associated with four significant variators of which 36.12% identified the main parameters BOD, COD, TP, ammonia, nitrate, and detergent. The cluster analysis grouped the sampling locations into 3 (three) clusters to indicate the spatial classifications of river water. Cluster 1 indicates pollutants from the residential area, Cluster 2 from residential and commercial areas, while Cluster 3 is majorly pollutants from industrial areas. Conclusion, significance, and impact study: The results showed the conductivity and TDS concentrations in cluster 3 are higher than the others since most of the sampling points are located near an industrial area or downstream close to the estuary. The mapping gave a better understanding of the river water quality characteristic spatially and could assist local governments in prioritizing river pollution management.  
利用多变量分析绘制河流水质空间变异图。以印度尼西亚大雅加达为例
城市活动和径流恶化了河水。目的:本研究旨在确定大雅加达地区河流的主要污染源,并绘制河流水质变化图。方法与结果:利用2014 - 2015年印度尼西亚大雅加达地区19条河流76个采样站的水质数据集的12个参数,采用因子分析和聚类分析(FA和CA)进行多变量分析。分析结果表明,水质数据总方差的66.6%与4个显著变量相关,其中BOD、COD、总磷、氨、硝态氮和去污剂是主要参数,占36.12%。聚类分析将采样地点分为3个聚类,以表明河流水的空间分类。集群1为居住区污染物,集群2为居住区和商业区污染物,集群3主要为工业区污染物。结论、意义及影响研究:聚类3的电导率和TDS浓度较高,因为大部分采样点位于工业区附近或靠近河口的下游。该制图可以更好地了解河流水质的空间特征,并可以帮助地方政府确定河流污染治理的优先顺序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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