Identifying source and transformation of riverine nitrates in a karst watershed, North China: comprehensively using major ions, multiple isotopes and Bayesian model
Authors: Zhang Jie , Jin Menggui 
Published: March 2021

&lt;p&gt;The identification of nitrate (NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;-&lt;/sup&gt;) sources and biogeochemical transformations is critical for understanding and controlling diffuse pollution in surface water in drainage basins. This study&amp;#160;combines&amp;#160;water chemistry, environmental isotopes (&amp;#948;&lt;sup&gt;2&lt;/sup&gt;H&lt;sub&gt;H2O&lt;/sub&gt;, &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;H2O&lt;/sub&gt;, &amp;#948;&lt;sup&gt;15&lt;/sup&gt;N&lt;sub&gt;NO3&lt;/sub&gt;, and &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;NO3&lt;/sub&gt;), with land use data and a Bayesian isotope mixing model (Simmr), for reducing the uncertainty in estimating the contributions of different pollution sources in a Karst drainage basin of Jinan, North China. 64 samples were collected from&amp;#160;Yufu River (YFR) of Jinan city in September and December, 2019. The results revealed that the NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8722;&lt;/sup&gt;-N (4.41mg/L) was the predominant form of inorganic nitrogen in YFR watershed, accounting for about 58% of total nitrogen (8.06 mg/L). There were significant temporal and spatial variations in nitrate concentrations in the area. The nitrate concentration in time was low in December and high in September, while the process of first rising and then attenuating from upstream to downstream in space. Moreover, according to the surface water flow path, different biogeochemical transformations were observed throughout the study area: microbial nitrification was dominant in the upstream with elevated NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8722;&lt;/sup&gt;-N concentrations; in the middle stream a mixing of different transformations, such as nitrification, denitrification, and/or assimilation, were identified, associated to moderate NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8722;&lt;/sup&gt;-N concentrations; whereas in the downstream the main process affecting NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8722;&lt;/sup&gt;-N concentrations was assimilation, and/or denitrification, resulting in low NO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8722;&lt;/sup&gt;-N concentrations. Water chemical and dual isotope of &amp;#948;&lt;sup&gt;15&lt;/sup&gt;N&lt;sub&gt;NO3&lt;/sub&gt;&amp;#160;and &amp;#948;&lt;sup&gt;18&lt;/sup&gt;O&lt;sub&gt;NO3&amp;#160;&lt;/sub&gt;indicated that the river water was significantly affected by soil organic nitrogen and ammonium fertilizer inputs. Simmr mixing model outputs revealed that soil organic nitrogen (SON 55.5%) and ammonium fertilizer inputs(AF 29.5%) were the primary contributors of N pollution, whereas nitrate fertilizer(NF 7.1%), sewage &amp; manure (M&amp;S 3.6%), and atmospheric deposition (AP3.4%) played a less important role. The chemical fertilizer (AF and NF) and SON collectively mean contributing &gt; 50 % of nitrate both in September and December in the watershed. Therefore, reducing fertilizer application and adopting water-saving irrigationare key to control nitrate pollution in the area. The results provide scientific basis for the water quality protection and sustainable water management in the study area or similar areas.&lt;/p&gt;