The examination of wastewater and effluents flowing into receiving water bodies is crucial for identifying pollutant sources and implementing scenarios to reduce them. In this study, QUAL2kw was used to identify, assess, and predict the pollutant load of a drainage canal located 6 km away from Anzali Wetland. Initially, the model was calibrated and validated with data collected in 2017. The NRMSE of the values was mostly less than 20%, except for flow accounting for 37% during calibration. The model did well in simulating EC and ammonium levels, but there is room for improvement in predicting nitrate and inorganic P concentrations. Field visits and sampling were done during the rice growth period in April-June 2021. The model was simulated for a three-time series in 2021; the simulation showed that May was the most critical, as the levels of nitrates, ammonium, and phosphates were at their highest. This study focused on the employment of QUAL2kw to drainage canals, emphasizing its suitability for regions with limited data availability. Scenarios were employed to explore ways to enhance water resource quality, showcasing how targeted interventions can effectively mitigate nutrient loads. Scenarios were considered to reduce nutrient loads. Reducing the amount of fertilizer led to a 9-27% while applying water stress resulted in a 0.1-1% reduction in the discharge outflow from the drain and less than 1% reduction in the amount of ammonium and nitrate. It is concluded that reduction in fertilization is more efficient in reducing concentrations and pollutant loads at the exit point of the canal to water resources compared to applying water stress since urea fertilizer contains a high percentage of nitrogen, and declining water application can enhance the soil's nutrient retention ability but only to a small degree.

Keywords: Agricultural drainage; Irrigation management; Nitrate pollution; Nitrogen fertilizer management.

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