Two-Pool BOD Kinetics and Short-Test Bias: Data, Code, and DO-Sag Analysis for Long-Term Oxygen Demand in Wastewater Effluents

This dataset contains the data and computational resources supporting the study: “A hidden slow oxygen-demand pool in long-term biochemical oxygen demand (BOD) data: two-pool reanalysis and implications for receiving-water oxygen budgets.” The repository includes scripts used to perform kinetic modeling, statistical evaluation, and dissolved oxygen (DO) sag analysis. A two-pool (fast and slow) first-order kinetic model was applied to quantify ultimate oxygen demand and assess bias introduced by short-term BOD tests (5–30 days). The results demonstrate that a slow-degrading pool, comprising 30–67% of ultimate demand, is largely undetected in standard tests, leading to substantial underestimation of oxygen demand and mischaracterization of DO dynamics in slow-flushing receiving waters. Contents of this repository:- Processed BOD time-series datasets- Python scripts for model fitting (single and two-pool kinetics)- Code for AIC/BIC calculation and residual analysis- DO sag simulation scripts (Streeter–Phelps framework)- Figure generation scripts corresponding to manuscript figures- README file with instructions for reproducing all results The materials are organized to ensure full reproducibility of the study results. Users can regenerate all figures and statistical outputs using the provided scripts. Original data source:Borsuk, M. E., & Stow, C. A. (2000). Bayesian parameter estimation in a mixed-order model of BOD decay. Water Research, 34(3), 915–923. License:[Choose appropriate license, e.g., CC-BY 4.0] Keywords:biochemical oxygen demand; BOD kinetics; two-pool model; dissolved oxygen sag; wastewater; environmental modeling; reproducibility