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Updated: Nov 30, 2025

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Published on: July 24, 2016
A framework for assessing the adequacy of Water Quality Index - Quantifying parameter sensitivity and uncertainties
Hui Ying Pak1, C Joon Chuah2, Mou Leong Tan3
1Nanyang Environment And Water Research Institute (NEWRI), Nanyang Technological University of Singapore, 1 Cleantech Loop, 637141, Singapore.
This study introduces an adjusted Water Quality Index (WQI) to better handle missing data and optimize monitoring. The research provides a new framework for assessing WQI adequacy and sampling needs, using the Johor River Basin as a case study.
Area of Science:
- Environmental Science
- Water Resource Management
- Analytical Chemistry
Background:
- Water quality monitoring is crucial for water resource management but is resource-intensive, particularly for developing nations.
- Traditional Water Quality Indices (WQI) summarize water quality but lack comprehensive assessment of their utility, flexibility, and practicality.
- Existing WQI frameworks have limitations in handling missing data and adapting to local water quality conditions.
Purpose of the Study:
- To introduce an adjusted Water Quality Index (WQIADJUSTED) framework to effectively manage missing data and utilize available information.
- To develop a Sub-WQI for addressing specific local water quality conditions.
- To establish a novel procedure for assessing WQI adequacy through sensitivity analysis and uncertainty quantification of missing parameter values.
Main Methods:
- Development of an adjusted WQI (WQIADJUSTED) incorporating a method for handling missing values.
- Comparison of WQI results derived from Multivariate Linear Regression (WQIMLR) and Principal Component Analysis (WQIPCA) for parameter optimization.
- Application of Monte Carlo probabilistic simulation to optimize sampling frequency based on user-defined acceptable WQI change.
Main Results:
- WQIMLR demonstrated superior performance in explaining general water quality compared to WQIPCA for weighted parameters.
- Optimized sampling frequency for the Johor River Basin suggests approximately 130 samples are needed for a 2% acceptable change in WQI.
- Total coliform was identified as the most sensitive parameter to missing values in the Johor River Basin study.
Conclusions:
- The proposed WQIADJUSTED framework enhances WQI development by effectively handling missing data and improving information utilization.
- The developed methodology provides a robust approach for assessing WQI adequacy and optimizing monitoring strategies.
- The case study in the Johor River Basin highlights the practical application of the framework for effective water resource management.
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