Twarakavi Navin K C, Kaluarachchi Jagath J
Civil and Environmental Engineering and Utah Water Research Laboratory, Utah State University, Logan, UT 84322-8200, USA.
J Environ Manage. 2006 Dec;81(4):405-19. doi: 10.1016/j.jenvman.2005.11.008. Epub 2006 Apr 4.
One of the major environmental issues of concern to policy-makers is the increased vulnerability of ground water quality (GWQ). Another issue of equal interest is the sustainability of natural resources for future generations. To understand the sustainability of the natural resources such as water in general, one needs to understand the impact of future land use changes on the natural resources. This work proposes a methodology to address sustainability of GWQ considering land use changes, aquifer vulnerability to multiple contaminants, and public health risks. The methodology was demonstrated for the Sumas-Blaine aquifer in Washington State. The land transformation model predicted that nearly 60 percent of the land use practices would change in the Sumas-Blaine Aquifer by the year 2015. The accuracy of the LTM model predictions increased to greater levels as the spatial resolution was decreased. Aquifer vulnerability analysis was performed for major contaminants using the binary logistic regression (LR) method. The LR model, along with the predicted future land use, was used to estimate the future GWQ using two indices-carcinogenic and non-carcinogenic ground water qualities. Sustainability of GWQ was then analyzed using the concept of 'strong' sustainability. The sustainability map of GWQ showed improvements in many areas where urbanization is expected to occur. The positive impact of urbanization on GWQ is an indication of the extensive damage caused by existing agricultural activities in the study area.
政策制定者关注的主要环境问题之一是地下水水质（GWQ）的脆弱性增加。另一个同样受关注的问题是自然资源对子孙后代的可持续性。要全面理解诸如水等自然资源的可持续性，就需要了解未来土地利用变化对自然资源的影响。这项工作提出了一种方法，用于考虑土地利用变化、含水层对多种污染物的脆弱性以及公共健康风险来解决地下水水质的可持续性问题。该方法在华盛顿州的苏马斯 - 布莱恩含水层进行了验证。土地转化模型预测，到2015年，苏马斯 - 布莱恩含水层近60%的土地利用方式将发生变化。随着空间分辨率降低，土地转化模型（LTM）预测的准确性提高到更高水平。使用二元逻辑回归（LR）方法对主要污染物进行了含水层脆弱性分析。LR模型与预测的未来土地利用一起，用于使用致癌和非致癌地下水水质两个指标来估计未来的地下水水质。然后使用“强”可持续性概念分析了地下水水质的可持续性。地下水水质可持续性地图显示，预计城市化将发生的许多地区有改善。城市化对地下水水质的积极影响表明了研究区域现有农业活动造成的广泛破坏。
