Development of function-specific indices for assessing water quality based on the proposed modifications of the expected conflicts on existing information entropy weights.

Abstract

Water serves numerous purposes besides drinking, such as irrigation and industrial usage. Most water quality indices developed have primarily focused on drinking water quality. However, assessing other functionalities of water bodies is also equally essential. The present study proposes a novel technique to measure water quality for two highly specific water use, i.e., assessing heavy metal contamination and irrigation suitability. The ambiguities in the current practice of entropy weights were identified, and a novel method was proposed, considering a three-dimensional approach instead of the conventional two-dimensional procedure. Weights to different parameters were assigned based on the probability estimates obtained from the frequency of observed values within acceptable limits. The proposed method's reliability, correctness, and applicability were tested using Deepor Beel's water quality dataset. Results were highly consistent with the experimental values and correlated well with other established methods. The efficacy of the method was determined by employing sensitivity analyses. Both indices showed high reliability and correctness, as no single parameter was found to be highly sensitive compared to others. Therefore, the proposed methodology proved to be the most reasonable, incorporating all the factors required for a reliable water quality monitoring program.