National Council of Scientific and Technical Research (CONICET), National Route 36, Km 601, 5800, Río Cuarto, Córdoba, Argentina; National University of Río Cuarto, Department of Geology, National Route 36, Km 601, 5800, Río Cuarto, Córdoba, Argentina.
National University of Río Cuarto, Department of Geology, National Route 36, Km 601, 5800, Río Cuarto, Córdoba, Argentina.
Environ Res. 2024 Oct 15;259:119571. doi: 10.1016/j.envres.2024.119571. Epub 2024 Jul 5.
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 (NO) 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 NO concentrations exceeding the regional natural background level, confirming the impact of human activities on groundwater quality. The dual plot of δN versus δO values indicates that groundwater is affected by NO 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.
近年来，人类活动对氮循环的显著干扰已超越可接受的环境阈值，这一点已变得显而易见。在本研究中，我们结合化学和同位素示踪剂、数学质量平衡模型（EMMA）、PHREEQC 反混合模型以及统计分析，评估了一个受到大量人类活动影响的地区的地下水质量，特别关注通过潜在的水混合过程追踪硝酸盐（NO）的来源。该多技术方法应用于一个山间洼地（即阿根廷的“波乔平原”）中一个农业区下的无隔水层含水层。在这里，调查地下水中主要发生的地球化学过程包括碳酸盐盐的溶解、阳离子交换以及铝硅酸盐的水解，同时还包括从沉淀中吸收离子。研究表明，地下水的化学性质主要为碳酸氢钠型和硫酸盐型，这受研究区地质、降水补给以及来自周围山丘的溪流水渗透的控制。化学结果表明，60%的地下水样本的硝酸盐浓度超过了区域自然背景水平，这证实了人类活动对地下水质量的影响。δN 与 δO 值的双标图表明，地下水受到与有机肥/污水重叠的硝酸盐来源的影响，这些硝酸盐来源与富含有机物的土壤有关。EMMA 数学模型和 PHREEQC 反演模型表明，富含有机物的土壤是含水层中氮的重要来源。在该模型中，64%的样本主要由富含有机物的土壤与有机肥混合而成，而 36%的样本主要受有机肥和化肥的混合影响。本研究表明，在污染源同位素特征重叠的情况下，结合同位素示踪剂、数学模型和统计分析，可以更好地了解地下水质量恶化的情况。
