TY - JOUR
T1 - A framework for assessing the adequacy of Water Quality Index – Quantifying parameter sensitivity and uncertainties in missing values distribution
AU - Pak, Hui Ying
AU - Chuah, C. Joon
AU - Tan, Mou Leong
AU - Yong, Ee Ling
AU - Snyder, Shane A.
N1 - Funding Information:
Funding: The authors are grateful for the financial support provided by the Economic Development Board - Singapore and also for the Research Fund for the Masters Programme by the Nanyang Environment and Water Research Institute, Nanyang Technological University and for the support of the School of Civil and Environmental Engineering, Nanyang Technological University .
Funding Information:
Funding: The authors are grateful for the financial support provided by the Economic Development Board - Singapore and also for the Research Fund for the Masters Programme by the Nanyang Environment and Water Research Institute, Nanyang Technological University and for the support of the School of Civil and Environmental Engineering, Nanyang Technological University. We would like to acknowledge the assistance provided by our collaborators Professor Ee Ling Yong from Universiti Teknologi Malaysia (UTM) and Mou Leong Tan from Universiti Sains Malaysia (USM). We would also like to thank the analytical team from the Advanced Environmental Biotechnology Centre (AEBC) of Nanyang Environment & Water Research Institute (NEWRI) for assisting us with the procurement of chemicals, and with operation and maintenance of analytical instruments. We would like to thank the reviews given by the three anonymous reviewers from Science and the Total Environment (STOTEN), which has helped to improve the manuscript significantly.
Publisher Copyright:
© 2020
PY - 2021/1/10
Y1 - 2021/1/10
N2 - Water quality monitoring is a pillar in water resource management, but it can be resource intensive, especially for developing countries with limited resources. As such, Water Quality Indices (WQI) are developed to summarise general water quality, but efforts to assess the utility, flexibility, and practicality of WQI have been limited. In this study, we introduced an additional step to the traditional WQI development framework by introducing an adjusted form of WQI (WQIADJUSTED) to handle missing values, and capitalise on the remaining available information for the development of a WQI. A Sub-WQI was also developed to address local water quality conditions. WQI results (weighted and non-weighted) developed using different parameter optimisation methods, namely Multivariate Linear Regression and Principal Component Analysis were compared. To build upon the current framework, a new procedure was developed to assess the adequacy of WQI based on the sensitivity analysis of parameters and uncertainties associated with each parameter's missing values distribution. The number of observations needed for the development of a robust WQI was optimised with respect to user-defined acceptable change in WQI, based on Monte Carlo probabilistic simulation. The Johor River Basin (JRB), Malaysia is used as a case-study for the application of this new framework. The JRB serves as an important resource for Johor, one of the most populous state in Malaysia, and Singapore, a country south of Johor. WQIMLR performed better in explaining the general water quality than WQIPCA for weighted water quality parameters. Optimisation of sampling frequency revealed that around 130 samples will be required if a 2% change in WQI can be tolerated. The results (specific to the JRB) also revealed that total coliform is the most sensitivity parameter to missing values, and the distribution of sensitive parameters are similar for both WQINON-ADJUSTED and WQIADJUSTED.
AB - Water quality monitoring is a pillar in water resource management, but it can be resource intensive, especially for developing countries with limited resources. As such, Water Quality Indices (WQI) are developed to summarise general water quality, but efforts to assess the utility, flexibility, and practicality of WQI have been limited. In this study, we introduced an additional step to the traditional WQI development framework by introducing an adjusted form of WQI (WQIADJUSTED) to handle missing values, and capitalise on the remaining available information for the development of a WQI. A Sub-WQI was also developed to address local water quality conditions. WQI results (weighted and non-weighted) developed using different parameter optimisation methods, namely Multivariate Linear Regression and Principal Component Analysis were compared. To build upon the current framework, a new procedure was developed to assess the adequacy of WQI based on the sensitivity analysis of parameters and uncertainties associated with each parameter's missing values distribution. The number of observations needed for the development of a robust WQI was optimised with respect to user-defined acceptable change in WQI, based on Monte Carlo probabilistic simulation. The Johor River Basin (JRB), Malaysia is used as a case-study for the application of this new framework. The JRB serves as an important resource for Johor, one of the most populous state in Malaysia, and Singapore, a country south of Johor. WQIMLR performed better in explaining the general water quality than WQIPCA for weighted water quality parameters. Optimisation of sampling frequency revealed that around 130 samples will be required if a 2% change in WQI can be tolerated. The results (specific to the JRB) also revealed that total coliform is the most sensitivity parameter to missing values, and the distribution of sensitive parameters are similar for both WQINON-ADJUSTED and WQIADJUSTED.
KW - Johor
KW - Multivariate linear regression
KW - Principal component analysis
KW - Sensitivity analysis
KW - Statistical decision theory
KW - Water Quality Index
UR - http://www.scopus.com/inward/record.url?scp=85090880195&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090880195&partnerID=8YFLogxK
U2 - 10.1016/j.scitotenv.2020.141982
DO - 10.1016/j.scitotenv.2020.141982
M3 - Article
C2 - 33181998
AN - SCOPUS:85090880195
SN - 0048-9697
VL - 751
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 141982
ER -