Stochastic reliability-based risk evaluation and mapping for watershed systems and sustainability (STREAMS)

Reliability theory for microbial water quality and sustainability assessment

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.