MULTIVARIATE STATISTICAL ANALYSIS FOR THE ASSESSMENT OF GROUNDWATER QUALITY IN SEMARANG LOWLAND AREA

Authors

  • Thomas Triadi Putranto
  • TRN Amanah
  • Budi Warsito
  • Hartuti Purnaweni
  • Muhammad Helmi

Keywords:

Groundwater, Multivariate, PCA, HCA, Semarang

Abstract

Groundwater is the primary water resources for the human activities in Semarang lowland area. Serious threats against sustainable development concerning groundwater are inevitable. Therefore, it is essential to assess groundwater quality. The primary objective of the research is assessing groundwater quality using the multivariate statistical analysis using Principal Component Analysis (PCA) and Hierarchical Component Analysis (HCA) to evaluate 30 groundwater samples which are collected from dug wells. The results show the concentration of pH, Fe3+, Cl-, Mn2+, SO42-, NO2-, exceeding the Indonesian water drinking standard. Cluster and factorial analysis showed three primary factors in groundwater. Factor 1 explained that 63.5% from total variant with EC, CaCO3, Mg2+, K+
, Na+, Cl- and TDS show a potential contamination source from seawater intrusion. Factor 2 explained that 13.5% from total variant with pH and NO3-show a potential contamination source from household waste. Factor 3 explained that 10.4% from total variant
with Fe3+ is assumed to be contaminants from rocks around Semarang.

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Published

2020-02-26

How to Cite

Thomas Triadi Putranto, TRN Amanah, Budi Warsito, Hartuti Purnaweni, & Muhammad Helmi. (2020). MULTIVARIATE STATISTICAL ANALYSIS FOR THE ASSESSMENT OF GROUNDWATER QUALITY IN SEMARANG LOWLAND AREA. GEOMATE Journal, 18(66), 124–131. Retrieved from https://geomatejournal.com/geomate/article/view/455