Water Quality Prediction in Inland Lakes Using the Streeter Phelps Dissolved Oxygen Algorithm
DOI:
https://doi.org/10.70102/AEEF/V3I2/3Keywords:
Streeter-Phelps Model; Dissolved Oxygen Prediction; Inland Lakes; Water Quality Modelling; Biochemical Oxygen Demand (Bod); Oxygen Sag Curve; Hypoxia; Lake Pollution Assessment; Deoxygenation Rate; Environmental Sustainability.Abstract
Maintaining optimal water quality in inland lakes is important for ecological balance, human consumption,
and recreational use. This study employs the Streeter-Phelps Dissolved Oxygen (DO) algorithm to predict the
dynamics of water quality due to the lack of oxygen and recovery of water from the bottom of organic pollution
sources. The algorithm consists of major parameters such as biochemical oxygen demand (BOD), deoxygenation Rate
(K₁), and Rate (K₂), which are used to estimate the spatial and temporal distribution of dissolved oxygen
concentrations. Field data of selected inland lakes was integrated into the model to follow the pollution scenarios of
the real world. The results reveal oxygen relaxed curve behaviour under different environmental conditions, enabling
the identification of important areas for hypoxia. Verification against empirical water quality measurements displays
the reliability of the model in the forecast of DO levels and assesses pollution load effects. This modelling structure
provides a cost-effective and scientifically sound approach for lake management authorities to evaluate pollution
mitigation strategies and ensure the stability of aquatic ecosystems.
