Declines in nutrient losses from China’s rice paddies jointly driven by fertilizer application and extreme rainfall

Agriculture, Ecosystems & Environment(2023)

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摘要
Rice production consumes large amounts of fertilizer and irrigation water and contributes to the non-point source pollution (NPSP) by delivering nitrogen (N) and phosphorus (P) through surface and subsurface fluxes. However, due to the lack of spatially detailed datasets we barely understand the temporal variations of nutrient fluxes or what the key drivers are. Here, we developed a data-driven model and a rice-specific dataset of fertilizer and irrigation schemes to quantify N and P loss fluxes from China’s rice paddies across 2320 counties during 1979–2018. Both of the surface and subsurface fluxes decreased, ∼16 % for N and ∼28 % for P over the past four decades. Instead of a steady decrease, the N surface and subsurface fluxes slightly increase at first, until decrease since 1999 at rates of − 1.2 and − 4.7 kiloton N yr−2, respectively. Similarly, the P surface and subsurface fluxes decline rates jumped to − 0.4 and − 0.2 kiloton P yr−2, respectively. N loss via subsurface flux was slightly prevailing compared with surface runoff, their trends were mainly driven by fertilizer application and extreme rainfall, respectively. P was primarily exported via surface runoff, with its trends jointly driven by extreme rainfall and fertilizer application, while the trends of subsurface P fluxes were largely driven by the latter. Consequently, N and P require different mitigation strategies, with N focusing on optimized fertilizer application and P on optimized water scheme. The combination of mitigation strategies on 20 % of the national rice sowing area accounted for 48 % of N and 70 % of P mitigation potentials under future warming. These findings suggest that we should implement regional specific policy interventions for critical regions and pathways, to effectively alleviate the national NPSP.
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关键词
nutrient losses,rice paddies,fertilizer application,rainfall
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