2026-10-11T21:47:26Z https://www.scidb.cn/oai

10.57760/sciencedb.06850 2022-12-20T12:21:49Z

2022-12-20 Regional nitrogen and phosphorus leaching mitigation strategies based on nutrient losses vulnerable zones in China doi:10.57760/sciencedb.06850 en Agricultural non-point source pollution control research has primarily focused on field-level technology development rather than regional mitigation options, reducing their large-scale effectiveness. This study proposed the mitigation strategies based on nutrient-loss risk at the regional level to achieve full potential of mitigation technologies. Nutrient-loss vulnerable zones (NLVZ) in China were designed from water quality monitoring and nutrient flow data and natural condition spatial characteristics. Based on the NLVZ, hierarchical management according to regional vulnerabilities were adopted, zone-specific mitigation methods based on natural and socio-economic conditions were selected, and regional mitigation strategies and nitrogen (N) and phosphorus (P) leaching technique lists were developed. Furthermore, using the NUtrient flows in Food chains, Environment and Resources model (NUFER), the effects of regional mitigation strategies were evaluated. The results indicated that NLVZ and potential NLVZ covered 52% of Chinese croplands and were widely distributed in major agricultural production areas. Regional mitigation strategies reduced potential NLVZ by 51%, particularly in the Northeast and Southwest China and the middle and lower reaches of the Yangtze River. Regional mitigation strategies reduced leaching by approximately 40% in cultivated areas with high N leaching (>22.6 kg(N)·hm−2), from 3.1107 kg(N)·hm−2 to 1.9107kg(N)·hm−2. Designing regional mitigation strategies based on NLVZ reduced nonpoint source pollution, promoting ecological agricultural development in China. Nitrogen and phosphorus leaching; Agricultural non-point source pollution; Nutrient losses vulnerable zone; Agro-ecological zone; Regional mitigation strategies Jin Xinpeng Ma Lin PUBLIC https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset http://www.doi.org/10.13930/j.cnki.cjea.200792 Science Data Bank