Abstract：
In recent years, it has become evident that human activities have significantly disrupted the nitrogen cycle surpassing acceptable environmental thresholds. In this study, chemical and isotopic tracers were combined with a mathematical mass balance model (EMMA), PHREEQC inverse mixing model, and statistical analyses to evaluate groundwater quality, across an area experiencing substantial human activities, with a specific focus on tracing the origin of nitrate (NO3-) with potential water mixing processes. This multi-technique approach was applied to an unconfined aquifer underlying an agricultural area setting in an inter-mountain depression (i.e., the \"Pampa de Pocho Plain\" in Argentina). Here, the primary identified geochemical processes occurring in the investigated groundwater system include the dissolution of carbonate salts, cation exchange, and hydrolysis of alumino-silicates along with incorporating ions from precipitation. It was observed that the chemistry of groundwater, predominantly of sodium bicarbonate with sulfate water types, is controlled by the area\'s geology, recharge from precipitation, and stream water infiltration originating from the surrounding hills. Chemical results reveal that 60% of groundwater samples have NO3- concentrations exceeding the regional natural background level, confirming the impact of human activities on groundwater quality. The dual plot of δ15NNO3 versus δ18ONO3 values indicates that groundwater is affected by NO3- sources overlapping manure/sewage with organic-rich soil. The mathematical EMMA model and PHREEQC inverse modeling, suggest organic-rich soil as an important source of nitrogen in the aquifer. Here, 64 % of samples exhibit a main mixture of organic-rich soil with manure, whereas 36 % of samples are affected mainly by a mixture of manure and fertilizer. This study demonstrates the utility of combining isotope tracers with mathematical modeling and statistical analyses for a better understanding of groundwater quality deterioration in situations where isotopic signatures of contamination sources overlap.
摘要：
近年来,很明显，人类活动已经大大破坏了氮循环，超过了可接受的环境阈值。在这项研究中,化学和同位素示踪剂与数学质量平衡模型(EMMA)相结合，PHREEQC逆混合模型，和统计分析，以评估地下水质量，在经历大量人类活动的地区，特别关注用潜在的水混合过程追踪硝酸盐(NO3-)的来源。这种多技术方法适用于山间洼地农业区下的无限制含水层（即，阿根廷的“波乔平原”)。这里,在调查的地下水系统中发生的主要确定的地球化学过程包括碳酸盐的溶解，阳离子交换，和铝硅酸盐的水解以及从沉淀中掺入离子。据观察，地下水的化学性质，主要是碳酸氢钠与硫酸盐水类型，受该地区的地质控制，从降水中补给，和来自周围山丘的溪水渗透。化学结果表明，60％的地下水样品中的NO3-浓度超过了区域自然背景水平。确认人类活动对地下水质量的影响。δ15NNO3与δ18ONO3值的双重图表明，地下水受NO3-源与有机质丰富的土壤重叠的粪肥/污水的影响。数学EMMA模型和PHREEQC逆建模，建议富含有机物的土壤是含水层中氮的重要来源。这里,64%的样品表现出富含有机物的土壤与粪便的主要混合物，而36％的样品主要受肥料和肥料混合物的影响。这项研究证明了将同位素示踪剂与数学建模和统计分析相结合的实用性，可以更好地了解污染源同位素特征重叠的情况下的地下水质量恶化。
