AN INTEGRATED APPROACH FOR THE PREDICTION OF WATER QUALITY INDEX BASED ON LAND USE ATTRIBUTES USING DATA GENERATION METHOD AND BACK PROPAGATION NETWORK ALGORITHM
DOI:
https://doi.org/10.21837/pm.v7i1.73Keywords:
Water Quality Index, ANN, Gombak River, Back Propagation, Land-Use Data GenerationAbstract
Malaysian experts have warned that several major cities, including the capital Kuala Lumpur, could face serious water shortages due to over-pollution of the country's rivers by problems brought about by over-development. As 97 per cent of Malaysia's water supply is sourced from surface water, the main aim of this study was to identify a relationship between water quality and land use attributes. The study which was conducted on Gombak River and its watershed in Malaysia, introduced data generation method for the prediction and forecast of LU/LC data within the watershed. The method used exponential model equation, Lagrange model equation third & fourth degree polynomial fit; saturation growth-rate model in order to generate the required data: and artificial neural network's back propagation network algorithm. The study also introduces the LA-WQI model. This model was developed by associating the appropriate loading factors to a set of sub-indices. The findings revealed that as the activities increased throughout the watershed, the values of WQI quality decreased accordingly. The accuracy of prediction of the proposed LA-WQI ranged from 94.3% to 99.3% between Actual DOE-WQI and LA-WQI for station 18 in Gombak River. The results of predicted WQI obtained using LA-WQI, showed a continuous decrease of water quality. Despite the high accuracy attained by the application of LA-WQI model on Gombak River; it has not yet been tested on other rivers. It is recommended that future studies should be able to further test the current model on a regional scale.
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