Evaluation of performance of water quality models for a tropical lake system. Issue 2 (June 2016)

• Record Type: Journal Article
• Authors: Albert Moses, Sheela; Janaki, Letha; Joseph, Sabu; Joseph, Justus
• Is Part Of: Lakes & reservoirs. Volume 21:Issue 2(2016)
• Page Start: 82
• Page End: 93
• Publication Date: 2016-06
• Subjects: model -- regression -- remote sensing -- tropical lake -- water quality analysis simulation program; Lakes -- Periodicals; Reservoirs -- Periodicals; Gestion de l'environnement; Gestion écologique; Lac; Lac de barrage; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 333.9163
• DOI: 10.1111/lre.12125
• Languages: English
• ISSNs: 1320-5331

Abstract

Abstract: The ability to predict water quality is a major requirement for planning and execution of developmental projects. It helps entrepreneurs to effectively plan and implement pollution control measures. This study evaluates the ability of different water quality models (statistical; remote sensing; mathematical) to predict salinity in Akkulam–Veli Lake, a tropical lake system. The performance of these three water quality models was evaluated. Prediction of salinity was made accurately with the mathematical model (WASP), compared to the other models. WASP facilitates prediction of daily water quality variations, which is not possible with the other models. A limitation of this model, however, was its ability to predict only a few water quality parameters. The statistical methods are reliable when the number of sampling sites and frequency of sample collection are high, making this method exhaustive and expensive. Remote sensing techniques proved to be less tedious, but are suitable only under specific situations, and not able to produce a high level of accuracy. Nevertheless, this method provides a continuous picture of spatial variations of different water quality parameters to a reasonable level of accuracy. The choice of the 'best' model varies on the basis of climatic and field conditions of the lake system of concern. Thus, a combination of water quality models was found to be the most ideal approach for analysing water quality data.