Water Quality Index Models for Lotic and Lentic Ecosystems-A Systematic Review

Abstract

AbstractThis review article intends to survey the information on water quality indices developed for the general evaluation of surface water and establish whether the water quality indices (WQIs) can be used to evaluate both lentic and lotic ecosystems simultaneously. Water quality index (WQI) models have gradually gained popularity since their maiden introduction in the 1960s. WQIs transform complex water quality data into a single dimensionless number to enable accessible communication of the water quality status of water resource ecosystems. To screen relevant articles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed to include or exclude articles. A total of 17 peer-reviewed articles were used in the final paper synthesis. Among the reviewed WQIs, only the Canadian Council for Ministers of the Environment (CCME) index, Waski & Parker index, and Hahn index are used to assess both lotic and lentic ecosystems. Furthermore, the CCME index is the only exception from rigidity because it does not specify parameters to select. Except for the West-Java WQI, none of the reviewed WQI performed sensitivity and uncertainty analysis to improve the acceptability and reliability of the WQI. It has been revealed that despite the use of statistical methods such as cluster analysis (CA), factor analysis (FA), and analytic hierarchy process (AHP), WQI models continue to suffer from either eclipsing, ambiguity, or uncertainty limitations because natural ecosystems tend to be too complex for these statistical methods. This review thus recommends coupling statistical methods with machine learning techniques such as artificial neural networks (ANN) in the WQI model development processes.