A SOFTWARE FRAMEWORK FOR ASSESSING THE RESILIENCE OF DRINKING WATER SYSTEMS TO DISASTERS WITH AN EXAMPLE EARTHQUAKE CASE STUDY.

Water utilities are vulnerable to a wide variety of human-caused and natural disasters. The Water Network Tool for Resilience (WNTR) is a new open source Python™ package designed to help water utilities investigate resilience of water distribution systems to hazards and evaluate resilience-enhancing actions. In this paper, the WNTR modeling framework is presented and a case study is described that uses WNTR to simulate the effects of an earthquake on a water distribution system. The case study illustrates that the severity of damage is not only a function of system integrity and earthquake magnitude, but also of the available resources and repair strategies used to return the system to normal operating conditions. While earthquakes are particularly concerning since buried water distribution pipelines are highly susceptible to damage, the software framework can be applied to other types of hazards, including power outages and contamination incidents.

Resilience Analysis of Potable Water Service after Power Outages in the U.S. Virgin Islands.

The two Category-5 hurricanes that impacted the United States Virgin Islands in 2017 exposed critical infrastructure vulnerabilities that must be addressed. While the drinking water utility has first-hand knowledge about how the hurricanes affected their systems, the use of modeling and simulation tools can provide additional insight to aid investment planning and preparedness. This paper provides a case study on resilience analysis for the island's potable water systems subject to long term power outages. Power outage scenarios help quantify differences in water delivery, water quality, and water quantity during and after the disruption. The analysis helps illustrate important differences in system operations and recovery time across the islands. Results from this case study can be used to better understand how the system might behave during future disruptions, provide justification for investment, and provide recommendations to increase resilience of the system. The analysis framework can also be used by other utilities to explore vulnerability to long term power outages.

Prioritizing vaccination based on analysis of community networks.

Many countries that had early access to COVID-19 vaccines implemented vaccination strategies that prioritized health care workers and the elderly. As barriers to access eased, vaccine prioritization strategies have been relaxed. However, these strategies are still an important tool for decision makers to manage new variants, plan for future booster shots, or stage mass vaccinations. This paper explores the impact of vaccine prioritization strategies using networks that represent communities with different demographics and connectivity. The impact of vaccination is compared to non-medical intervention to reduce transmission. Several sources of uncertainty are considered, including vaccine willingness and mask effectiveness. This paper finds that while prioritization strategies can have a large impact on reducing deaths and peak hospitalization, selecting the best strategy depends on community characteristics and the desired objective. Additionally, in some cases random vaccination performs as well as more targeted prioritization strategies. Understanding these trade-offs is important when planning vaccine distribution.

Performance and Resilience Analysis of a New York Drinking Water System to Localized and System-Wide Emergencies.

Drinking water utilities are vulnerable to both human-caused and natural disasters that can impact the system infrastructure and the delivery of potable water to consumers. Analyzing system performance and resilience can help utilities identify areas of high risk or concern, understand the impacts on consumers, and evaluate response actions during disasters. In this case study, the Water Network Tool for Resilience (WNTR) was used to investigate the performance and resilience of a drinking water system in New York during increased demands due to firefighting, pipe damage, and loss of the source water emergencies. This case study introduced a new combined performance index (CPI) resilience metric, which served to quantify system resilience as a ratio of system performance during an emergency to normal operations. The results revealed that this drinking water system was able to maintain service to most of the consumers during these emergencies due to high redundancy within the system, and conservation efforts extended water service for an additional 20 h. The analysis in this paper can be used by other drinking water utilities to understand their vulnerabilities and evaluate resilience-improving actions in similar disaster scenarios.

Analysis of mobility data to build contact networks for COVID-19.

As social distancing policies and recommendations went into effect in response to COVID-19, people made rapid changes to the places they visit. These changes are clearly seen in mobility data, which records foot traffic using location trackers in cell phones. While mobility data is often used to extract the number of customers that visit a particular business or business type, it is the frequency and duration of concurrent occupancy at those sites that governs transmission. Understanding the way people interact at different locations can help target policies and inform contact tracing and prevention strategies. This paper outlines methods to extract interactions from mobility data and build networks that can be used in epidemiological models. Several measures of interaction are extracted: interactions between people, the cumulative interactions for a single person, and cumulative interactions that occur at particular businesses. Network metrics are computed to identify structural trends which show clear changes based on the timing of stay-at-home orders. Measures of interaction and structural trends in the resulting networks can be used to better understand potential spreading events, the percent of interactions that can be classified as close contacts, and the impact of policy choices to control transmission.

Evaluating Manual Sampling Locations for Regulatory and Emergency Response.

Drinking water systems commonly use manual or grab sampling to monitor water quality, identify or confirm issues, and verify that corrective or emergency response actions have been effective. In this paper, the effectiveness of regulatory sampling locations for emergency response is explored. An optimization formulation based on the literature was used to identify manual sampling locations to maximize overall nodal coverage of the system. Results showed that sampling locations could be effective in confirming incidents for which they were not designed. When evaluating sampling locations optimized for emergency response against regulatory scenarios, the average performance was reduced by 3%-4%, while using optimized regulatory sampling locations for emergency response reduced performance by 7%-10%. Secondary constraints were also included in the formulation to ensure geographical and water age diversity with minimal impact on the performance. This work highlighted that regulatory sampling locations provide value in responding to an emergency for these networks.

Quantifying hydraulic and water quality uncertainty to inform sampling of drinking water distribution systems.

Sampling of drinking water distribution systems is performed to ensure good water quality and protect public health. Sampling also satisfies regulatory requirements and is done to respond to customer complaints or emergency situations. Water distribution system modeling techniques can be used to plan and inform sampling strategies. However, a high degree of accuracy and confidence in the hydraulic and water quality models is required to support real-time response. One source of error in these models is related to uncertainty in model input parameters. Effective characterization of these uncertainties and their effect on contaminant transport during a contamination incident is critical for providing confidence estimates in model-based design and evaluation of different sampling strategies. In this paper, the effects of uncertainty in customer demand, isolation valve status, bulk reaction rate coefficient, contaminant injection location, start time, duration and rate on the size and location of the contaminant plume are quantified for two example water distribution systems. Results show that the most important parameter was the injection location. The size of the plume was also affected by the reaction rate coefficient, injection rate and the injection duration, while the the exact location of the plume was additionally affected by the isolation valve status. Uncertainty quantification provides a more complete picture of how contaminants move within a water distribution system and provides more information when using modeling results to select sampling locations.

Applications of fractured continuum model to enhanced geothermal system heat extraction problems.

This paper describes the applications of the fractured continuum model to the different enhanced geothermal systems reservoir conditions. The capability of the fractured continuum model to generate fracture characteristics expected in enhanced geothermal systems reservoir environments are demonstrated for single and multiple sets of fractures. Fracture characteristics are defined by fracture strike, dip, spacing, and aperture. The paper demonstrates how the fractured continuum model can be extended to represent continuous fractured features, such as long fractures, and the conditions in which the fracture density varies within the different depth intervals. Simulations of heat transport using different fracture settings were compared with regard to their heat extraction effectiveness. The best heat extraction was obtained in the case when fractures were horizontal. A conventional heat extraction scheme with vertical wells was compared to an alternative scheme with horizontal wells. The heat extraction with the horizontal wells was significantly better than with the vertical wells when the injector was at the bottom.