Integrating drip fertigation and nitrification inhibitors for rhizosphere-scale control of nitrogen transformations

Reactive nitrogen (Nr) losses from fertilized agricultural soils remain one of the dominant drivers of groundwater nitrate contamination and nitrous oxide (N₂O) emissions, yet mitigation strategies are largely designed around input optimization rather than control of in-soil nitrogen transformations. Drip fertigation and nitrification inhibitors (NIs) have independently shown potential to improve nitrogen efficiency, however their integrated effects remain fragmented across irrigation and inhibitor-focused literature. Consequently, an integrated mechanistic framework explaining how drip irrigation-induced microenvironments regulate NI performance and nitrogen transformation is lacking. Here, we argue that the integration of drip fertigation with NIs, hereafter referred to as drip-NIs integration, is best understood as rhizosphere process control rather than input management: drip defines a bounded reaction-transport domain, and NIs slow down the conversion of ammonium (NH₄ ⁺) to nitrate (NO₃ ^-). This review aims to synthesize evidence across NI types, crops, and drip configurations to examine how localized wetting patterns govern ammonium-nitrate partitioning, microbial processes, and inhibitor fate within the root zone. The available evidence suggests that NI performance may depend on spatial and temporal overlap among oxygen recovery, NH₄ ⁺ availability, and active ammonia oxidizers within the wetted bulb, however direct spatial validation remains limited. Based on these insights, we propose the Designer Rhizosphere Model (DRM) as a conceptual, hypothesis-generating framework linking controllable design variables (emitter placement, irrigation waveform, fertigation chemistry, NI formulation) with the measurable state variables (oxygen availability, NH₄ ⁺/NO₃ ^- fields, inhibitor exposure), microbial process rates, and yield-scaled environmental outcomes. The DRM requires validation through spatially field experiments before practical application. The resulting framework suggests that drip-NIs integration may reduce nitrate leaching and greenhouse gas emissions while sustaining productivity, but outcomes are context-dependent and may be constrained by salinity accumulation, acidification, oxygen limitation, ammonium toxicity, and off-target effects. Future research should prioritize spatially resolved measurements, sensor-guided fertigation, drip-compatible inhibitor formulations, and process-based decision support models. Collectively, this review reframes nitrogen management from simple fertilizer placement to rhizosphere process control for improving agricultural sustainability.