Abstract
River, as one of the surface water resources, has faced many contaminations due to domestic and industrial activities in its surrounding, and thus routine water quality monitoring is required. This activity yields a large number of water quality characteristics that can be very useful to evaluate the status of river quality status. In this study, we integrated a statistical multivariate analysis such as Principal Component Analysis (PCA) and conventional Water Quality Index (WQI) measure to produce a data-driven composite index for water quality assessment. We implemented this technique to evaluate the status of Brantas River, the largest river in East Java Province-Indonesia, using a long-term dataset collected from 2012 to 2021. The study area was divided into three classes: upstream, midstream, and downstream. Results of the study suggested that the level of pollution in the Brantas River fluctuates yearly wise. Meanwhile, the degree of contamination increased from upstream to downstream.
| Original language | English |
|---|---|
| Journal | Ecological Questions |
| Volume | 34 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 6 Clean Water and Sanitation
Keywords
- multivariate analysis
- principal component analysis
- surface water
- water quality evaluation
- WQI
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