Water quality amplifies event scale nitrous oxide emissions under fertilization and hydrothermal controls

Water quality is increasingly important under expanding mixed water sources, yet most nitrous oxide (N₂O) emission models treat water chemistry as a stable background condition, despite evidence of persistent effects on soil carbon and nitrogen cycling. Here, the study analyzed a four-year drip irrigated winter wheat-summer maize field experiment in the North China Plain using reclaimed water (RW) and groundwater (GW) irrigation. We developed a hierarchical Bayesian (HB) event based N₂O model driven by fertilization, soil temperature, and soil moisture, and evaluated three alternative structures that differed in how irrigation water quality was represented: M0, a baseline model without water quality effects; M1, a weak perturbation model in which water quality variability enters the parameter layer; and M2, a strong perturbation model in which water quality variability additionally enters the event response structure to modulate fertilization induced emission pulses and their attenuation. Explicit incorporation of water quality substantially improved predictive skill and reduced posterior uncertainty, with M2 showing higher expected log predictive density and tighter posterior predictive checks than both M0 and M1. Water quality reorganized the attribution of N₂O emission controls by accelerating fertilization pulse attenuation and reducing the apparent dominance of temperature and moisture sensitivities, thereby shifting variability toward event scale perturbations following irrigation. Event scale diagnostics further showed that prediction errors and inferred perturbation weights increased under intermediate to high soil moisture and temperature. Reactive nitrogen species and labile organic carbon as the dominant water quality drivers, primarily influencing the temperature and moisture sensitivity of fertilization induced emission pulses rather than baseline emissions. Taken together, resolving when and under which conditions water quality variability alters emission sensitivities advances the basis for adaptive irrigation and fertilization management.