Croplands are important sources of nitrous oxide (N₂O) emissions. The lack of both long‐term field measurements and reliable methods for extrapolating these measurements has resulted in a large uncertainty in quantifying and mitigating N₂O emissions from croplands. This is especially relevant in regions where cropping systems and farming management practices (FMPs) are diverse. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was tested against N₂O measurements from five cropping systems (alfalfa, wheat, lettuce, vineyards, and almond orchards) representing diverse environmental conditions and FMPs. The model tests indicated that DNDC was capable of predicting seasonal and annual total N₂O emissions from these cropping systems, and the model's performance was better than the Intergovernmental Panel on Climate Change emission factor approach. DNDC also captured the impacts on N₂O emissions of nitrogen fertilization for wheat and lettuce, of stand age for alfalfa, as well as the spatial variability of N₂O fluxes in vineyards and orchards. DNDC overestimated N₂O fluxes following some heavy rainfall events. To reduce the biases of simulating N₂O fluxes following heavy rainfall, studies should focus on clarifying mechanisms controlling impacts of environmental factors on denitrification. DNDC was then applied to assess the impacts on N₂O emissions of FMPs, including tillage, fertilization, irrigation, and management of cover crops. The practices that can mitigate N₂O emissions include reduced or no tillage, reduced N application rates, low‐volume irrigation, and cultivation of nonleguminous cover crops. This study demonstrates the necessity and potential of utilizing process‐based models to quantify N₂O emissions from regions with highly diverse cropping systems.

Crop production with intensive nitrogen (N) application is an important source of atmospheric nitrous oxide (N₂O). However, there remains large uncertainty in quantifying cropland N₂O emissions and their mitigation potential, especially in regions where cropping systems and farming management practices are highly diverse. Because N₂O production in soils is tightly linked to N application rate and type, soil moisture, and oxygen status, improving irrigation is a potential strategy for N₂O mitigation. We applied a process‐based biogeochemical model, DeNitrification‐DeComposition, to evaluate the influence of irrigation management on N₂O emissions from California cropland, where cropping systems are extremely diverse and irrigation management has changed rapidly. We constructed a database containing data on weather, crop types and areas, soil properties, and farming management practices and predicted N₂O emissions from California cropland under four typical irrigation methods (surface gravity, sprinkler, drip, and subsurface drip). We also assessed impact on N₂O emissions of large‐scale changes in irrigation management experienced in California from 2001 to 2010 that was driven by the demand of reducing water use in agriculture. Simulations under different irrigation methods indicated that drip and subsurface drip irrigation reduced N₂O emissions by 55% and 67%, respectively, compared to surface gravity irrigation. We estimated baseline N₂O emissions from California cropland as 7.94 × 10³ metric ton (MT) N/year under actual irrigation management in 2002. The large‐scale changes in irrigation management likely reduced N₂O emissions by 7.3% from 2001 to 2010. This study showed the potential for reducing N₂O emissions by using low‐volume irrigation.