Evaluating BOD and DO Models in Context of the River Yamuna: A Critical Assessment

Abstract

Introduction: Dissolved Oxygen (DO) and Biochemical Oxygen Demand (BOD) are important parameters for evaluating the health of water bodies like rivers. Over time, many scientific models have been developed to foresee BOD and DO levels, and these models have been applied to rivers worldwide, including the Yamuna River in Delhi, India to test their pertinence.

Objectives: The research investigates different models for biochemical oxygen demand ( BOD) and Dissolved oxygen (DO) established in the past and were compared hence to gain insight into the existing water quality models for BOD and DO simulations in the River Yamuna of India . Our research addresses a critical gap in improved accuracy in stimulating BOD-DO dynamics, under varying environmental and climatic changes and pollution load.

Methods: A total of 384 field data sets were collected for the years 2013-2022. The key processes in the Yamuna River in Delhi are advection, dispersion, decay, settling, and pollutant loading. However, due to continuous wastewater disposal from different drains in the River Yamuna and unsteady-state flow conditions, the dispersion effects are significant. However, due to the disposal of huge quality of pollution without prior treatment its effect is insignificant. For the study purpose and to make sure that the optimization process converges efficiently, the model parameters were obtained using the Newton-Raphson technique. For evaluating BOD and DO values, correlation statistics (r²), standard error, and mean multiplicative error, which measures the proportion of variance, precision, and the average deviation among observed and projected values respectively were used.

Results: The importance of this work lies in critical advancement of the different models developed and to assess their applicability for the river Yamuna in India with the Real time data. We have been able to summarize that the results obtained by Jha et al. (2007) provided the best results

Conclusions: The conclusions indicate that there is a strong correlation between the observed data and the BOD-DO models created by Bhargava and Camp. Furthermore, the best results were found following Jha et al. (2007).