Department of Geology and Geophysics, University of Hawaii at Manoa, 1680 East-West Road, POST 701, Honolulu, HI 96822, USA; Water Resources Research Center, University of Hawaii at Manoa, 2540 Dole Street, Holmes Hall 283, Honolulu, HI 96822, USA.
J Contam Hydrol. 2013 Oct;153:1-23. doi: 10.1016/j.jconhyd.2013.07.004. Epub 2013 Jul 23.
Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (>1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach.
目前，夏威夷采用捕获区分析结合主观敏感性指数来评估地下水饮用水源污染的脆弱性。在这项研究中，我们开发了一种替代的客观方法，将井的捕获区与多变量逻辑回归（LR）模型相结合，并将其应用于夏威夷瓦胡岛上高度利用的珍珠港和火奴鲁鲁含水层。LR 模型的输入利用了基于水文地质学、土地利用和井几何形状/位置的解释变量。该模型使用了该地区检测到的 11 种目标污染物，包括硝酸盐（>1mg/L）升高、四种氯化溶剂、四种农业熏蒸剂和两种农药，来开发模型。然后，我们测试了新方法准确分离低脆弱性和高脆弱性组井的能力，以及硝酸盐作为其他类型污染指标的适宜性。我们的结果产生了特定于污染物的 LR 模型，这些模型准确地识别了报告检测值最低/最高和硝酸盐浓度最低/最高的井组。当前和以前的农业用地被确定为 11 种目标污染物中的八种的重要解释变量，而硝酸盐升高是五种污染物的重要变量。该综合方法的实用性取决于为校准地下水和 LR 模型提供水文和化学监测数据的可用性。在具有足够数据的参考地点应用该方法可以帮助识别具有相似水文地质和土地利用但数据有限的地区的关键变量。此外，硝酸盐升高也可能是数据有限地区地下水污染的合适指标。本研究中开发的客观 LR 建模方法足够灵活，可以解决广泛的污染物问题，是当前主观方法的一个很好的补充。
