Abstract:
Water is a necessary resource for life to continue living on Earth, and in the current
environment, finding clean, safe drinking water has become a major and daunting
challenge. The Rawal Dam is a major supply of drinking water for Pakistan's twin cities of
Rawalpindi and Islamabad. Natural freshwater from various streams and rivers supplies
Rawal dam. A few significant tributaries of the Rawal dam are the Korang River, the
Nurpur and Shahdara streams, the Jinnah stream, and the Filtration Plant, among others.
These streams in Islamabad, Pakistan, are constantly being contaminated by anthropogenic
activity due to their proximity to residential and industrial areas. The intrusion of waste
into these freshwater bodies is seriously compromising the water quality, endangering the
health of those who live in the vicinity to them. The current study focuses on forecasting
the pollution and assessment of the water quality of Rawal Dam and its tributaries.
Physiochemical testing, microbiological analysis, molecular analysis (DNA extraction and
qPCR analysis), and heavy metal analysis have all been used to determine the water quality
of the chosen sites. Deep learning models (LSTM, GRU, Bi-LSTM, and Bi-GRU) are used
for pollution forecasting prediction. This study will contribute significantly to forecasting
the pollution load inside the water bodies, identifying, and quantifying infamous pathogens
like Salmonella, Shigella, and E. Coli, and Campylobacter.
