Livestock farming dominates nitrogen and phosphorus loads under interannual rainfall variability in the Shaying River Basin

Non-point source pollution (NPSP) poses a significant threat to water quality in the Shaying River Basin, yet the impacts of interannual rainfall variability and topographic factors on nutrient load estimations remain poorly understood. This study improved the Export Coefficient Model (ECM) by integrating rainfall and topographic factors to estimate total nitrogen (TN) and total phosphorus (TP) loads in the Henan section of the basin during a normal-flow year (2023, 830 mm) and a pluvial year (2024, 1010 mm). Monte Carlo simulations were employed to quantify the 95% confidence intervals (CIs) and assess uncertainties under varying hydrological conditions. The results showed that the enhanced model effectively captured the spatial heterogeneity of NPSP. During the wet year, the heavily and sub-heavily polluted zones expanded substantially, covering over 57% of the total basin area. Source apportionment revealed a marked structural shift: livestock and poultry breeding has replaced agricultural land use as the dominant contributor to both TN (76%) and TP (87.9%) loads in this basin, driven by China’s fertilizer reduction policies and the intensive livestock farming. Within the livestock sector, cattle farming dominated TN loads, while pig farming dominated TP loads. The 95% CIs for TN and TP were significantly wider in the wet year than in the normal year. This increased uncertainty indicates that NPSP loads are highly sensitive to rainfall anomalies. Our findings underscore the impracticality of fixed annual reduction targets under climate change. We propose a “flexible threshold” management framework, advocating for stricter controls during wet years and relaxed limits during normal years. The quantified CIs provide a robust scientific basis for implementing these climate-adaptive water quality strategies, offering critical insights for targeted NPS pollution mitigation in the face of increasing hydroclimatic extremes.