Nitrate contamination in groundwater was evaluated using the concept of integrated aquifer assessment by combining groundwater characterization and risk analysis with tiered approaches for land and surface runoff contamination by soil chemicals and leaching of contamination to groundwater in the Upper White River Watershed (UWRW) in Indiana. Integrated aquifer vulnerability assessment was conducted using an integration of a distributed watershed model (Soil and Water Assessment Tool [SWAT]) and a machine learning technique (Geospatial-Artificial Neural Network [Geo-ANN]). The results indicate that integrated aquifer vulnerability assessment performed well based on the model performance (NSE/R²/PBIAS = 0.66/0.70/0.07). Thus, the overall assessment of aquifer vulnerability can be performed using the integrated aquifer vulnerability assessment technique provided in this study. Moreover, this approach provides an efficient guide for managing groundwater resources for policy makers and groundwater-related researchers.

地下水中的硝酸盐污染是采用综合含水层评估的概念进行评估的，该方法结合了地下水特征和风险分析与土壤化学物质对土地和地面径流污染以及印第安纳州上游白河流域（UWRW）淋溶至地下水的分层方法。集成的含水层脆弱性评估是使用分布式分水岭模型（土壤和水评估工具[SWAT]）和机器学习技术（地理空间人工神经网络[Geo-ANN]）进行的。结果表明，基于模型性能（NSE / R ²/ PBIAS = 0.66 / 0.70 / 0.07）。因此，可以使用本研究中提供的综合含水层脆弱性评估技术对含水层脆弱性进行整体评估。而且，这种方法为决策者和与地下水有关的研究人员提供了管理地下水资源的有效指南。