Shu Wang, Wang Peng, Zhao Jun, Ding Minjun, Zhang Hua, Nie Minghua, Huang Gaoxiang
School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, Jiangxi, China; Sino-Danish College of University of Chinese Academy of Sciences, Beijing 101408, China; Sino-Danish Centre for Education and Research, Beijing 101408, China.
School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, Jiangxi, China.
Sci Total Environ. 2022 Dec 15;852:158216. doi: 10.1016/j.scitotenv.2022.158216. Epub 2022 Aug 24.
Rapid land use change has significantly increased nitrate (NO) loading to rivers, leading to eutrophication, and posing water security problems. Determining the sources of NO to waters and the underlying influential factors is critical for effectively reducing pollution and better managing water resources. Here, we identified the sources and influencing mechanisms of NO in a mixed land-use watershed by integrating stable isotopes (δN-NO and δO-NO), molecular biology, water chemistry, and landscape metrics measurements. Weak transformation processes of NO were identified in the river, as evinced by water chemistry, isotopes, species compositions, and predicted microbial genes related to nitrogen metabolism. NO concentrations were primarily influenced by exogenous inputs (i.e., from soil nitrogen (NS), nitrogen fertilizer (NF), and manure & sewage (MS)). The proportions of NO sources seasonally varied. In the wet season, the source contributions followed the order of NS (38.6 %) > NF (31.4 %) > atmospheric deposition (ND, 16.2 %) > MS (13.8 %). In the dry season, the contributions were in the order of MS (39.2 %) > NS (29.2 %) > NF (29 %) > ND (2.6 %). Farmland and construction land were the original factors influencing the spatial distribution of NO in the wet and dry seasons, respectively, while slope, basin relief (HD), hypsometric integral (HI), and COHESION, HD were the primary indicators associated with NO transport in the wet and dry seasons, respectively. Additionally, spatial scale differences were observed for the effects of landscape structure on NO concentrations, with the greatest effect at the 1000-m buffer zone scale in the wet season and at the sub-basin scale in the dry season. This study overcomes the limitation of isotopes in identifying nitrate sources by combining multiple approaches and provides new research perspectives for the determination of nitrate sources and migration in other watersheds.
快速的土地利用变化显著增加了河流中的硝酸盐（NO）负荷，导致富营养化，并引发水安全问题。确定水体中NO的来源及其潜在影响因素对于有效减少污染和更好地管理水资源至关重要。在此，我们通过整合稳定同位素（δN-NO和δO-NO）、分子生物学、水化学和景观指标测量，确定了混合土地利用流域中NO的来源和影响机制。通过水化学、同位素、物种组成以及与氮代谢相关的预测微生物基因表明，河流中NO的转化过程较弱。NO浓度主要受外源输入（即来自土壤氮（NS）、氮肥（NF）以及粪便和污水（MS））的影响。NO源的比例随季节变化。在雨季，源贡献顺序为NS（38.6%）>NF（31.4%）>大气沉降（ND，16.2%）>MS（13.8%）。在旱季，贡献顺序为MS（39.2%）>NS（29.2%）>NF（29%）>ND（2.6%）。农田和建设用地分别是影响雨季和旱季NO空间分布的原始因素，而坡度、流域起伏度（HD）、地形起伏度积分（HI）以及凝聚度、HD分别是雨季和旱季与NO迁移相关的主要指标。此外，观察到景观结构对NO浓度的影响存在空间尺度差异，在雨季1000米缓冲区尺度影响最大，在旱季子流域尺度影响最大。本研究通过多种方法结合克服了同位素在识别硝酸盐来源方面的局限性，并为其他流域硝酸盐来源和迁移的确定提供了新的研究视角。
