Assessment of the nutrient pollution in some agricultural drainage ditch–pond systems with the QUAL2K: Model calibration and validation with field data

Agricultural drainage systems play a dual role, sustaining irrigation while exporting nutrients to downstream waters. In small-scale regions, ditch–pond networks are especially important, as they drive nitrogen and phosphorus losses that intensify eutrophication risks. This study applied the QUAL2K water quality model to assess nutrient dynamics in a farmland ditch–pond network located in Jiangdu District, Yangzhou City, Jiangsu Province, China. Monitoring data collected during the rice-growing seasons of 2022 for calibration and 2023 for validation were used to simulate the transport and transformation of four key pollutants: total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH 4 -N), and nitrate (NO 3 -N). The model incorporated measured hydraulic parameters, meteorological data, and pollutant concentrations, with parameter calibration guided by literature ranges. Results demonstrated that QUAL2K effectively reproduced pollutant patterns, with strong performance for TP and TN (R 2 > 0.90; NSE > 0.85) and reasonable accuracy for NH 4 -N. NO 3 -N simulations were less accurate during calibration, but improved significantly in validation (R 2 = 0.93). Sensitivity analysis further revealed that reactive nitrogen species exhibited strong parameter sensitivity, with NH 4 -N primarily controlled by nitrification rates and NO 3 -N by denitrification processes, highlighting the nonlinear nature of nitrogen transformations in ditch–pond systems. Overall, QUAL2K reliably captured phosphorus and nitrogen dynamics, confirming its applicability for nutrient transport assessment in agricultural drainage systems. The findings highlight its value in supporting water quality management strategies, while future refinements should focus on nitrogen-related processes and improved monitoring resolution to further enhance predictive reliability. The results further indicate that reactive nitrogen species exhibit pronounced nonlinear responses to parameter variations and hydrological conditions, explaining the higher uncertainty observed for NH 4 -N and NO 3 -N compared to TP and TN.