Teklitz Allen, Nietch Christopher, Riasi M Sadegh, Yeghiazarian Lilit
Department of Chemical and Environmental Engineering, University of Cincinnati, OH, USA.
United States Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
J Hydrol (Amst). 2021 May;596. doi: 10.1016/j.jhydrol.2020.125711.
Microbial surface water contamination can disrupt critical ecosystem services such as recreation and drinking water supply. Prediction of water contamination and assessment of sustainability of water resources in the context of water quality are needed but are difficult to achieve - with challenges arising from the complexity of environmental systems, and stochastic variability of processes that drive contaminant fate and transport. In this paper we use reliability theory as a framework to address these issues. We define failure as exceedance of regulatory water contamination limits, and system components as reaches in the surface water network. We then methodically study the reliability of each component in the context of water quality, as well as the impact of individual components on overall water quality and sustainability. We obtain spatially distributed probability- and physics-based sustainability measures of reliability, vulnerability, resilience and the sustainability index. Finally, we use GIS as a platform to present these measures as geospatial products in an effort to foster public acceptance of probability-based methods in contaminant hydrology.
微生物对地表水的污染会扰乱诸如娱乐和饮用水供应等关键的生态系统服务。需要对水污染进行预测,并在水质背景下评估水资源的可持续性,但这很难实现——环境系统的复杂性以及驱动污染物归宿和迁移过程的随机变异性带来了挑战。在本文中,我们使用可靠性理论作为框架来解决这些问题。我们将失效定义为超过监管的水污染限值,将系统组件定义为地表水网络中的河段。然后,我们系统地研究了每个组件在水质方面的可靠性,以及各个组件对整体水质和可持续性的影响。我们获得了基于概率和物理的可靠性、脆弱性、恢复力和可持续性指数的空间分布度量。最后,我们使用地理信息系统(GIS)作为平台,将这些度量呈现为地理空间产品,以促进公众接受污染物水文学中基于概率的方法。