RESUMEN
Illicit discharges in surface waters are a major concern in urban environments and can impact ecosystem and human health by introducing pollutants (e.g., petroleum-based chemicals, metals, nutrients) into natural water bodies. Early detection of pollutants, especially those with regulatory limits, could aid in timely management of sources or other responses. Various monitoring techniques (e.g., sensor-based, automated sampling) could help alert decision makers about illicit discharges. In this study, a multi-parameter sensor-driven environmental monitoring effort to detect or identify suspected illicit spills or dumping events in an urban watershed was supported with a real-time event detection software, CANARY. CANARY was selected because it is able to automatically analyze data and detect events from a range of sensors and sensor types. The objective of the monitoring project was to detect illicit events in baseline flow. CANARY was compared to a manual illicit event identification method, where CANARY found > 90% of the manually identified illicit events but also found additional unidentified events that matched manual event identification criteria. Rainfall events were automatically filtered out to reduce false alarms. Further, CANARY results were used to trigger an automatic sampler for more thorough analyses. CANARY was found to reduce the burden of manually monitoring these watersheds and offer near real-time event detection data that could support automated sampling, making it a valuable component of the monitoring effort.
RESUMEN
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.
RESUMEN
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.
RESUMEN
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.
RESUMEN
Water distribution systems are vulnerable to hazards that threaten water delivery, water quality, and physical and cybernetic infrastructure. Water utilities and managers are responsible for assessing and preparing for these hazards, and researchers have developed a range of computational frameworks to explore and identify strategies for what-if scenarios. This manuscript conducts a review of the literature to report on the state of the art in modeling methodologies that have been developed to support the security of water distribution systems. First, the major activities outlined in the emergency management framework are reviewed; the activities include risk assessment, mitigation, emergency preparedness, response, and recovery. Simulation approaches and prototype software tools are reviewed that have been developed by government agencies and researchers for assessing and mitigating four threat modes, including contamination events, physical destruction, interconnected infrastructure cascading failures, and cybernetic attacks. Modeling tools are mapped to emergency management activities, and an analysis of the research is conducted to group studies based on methodologies that are used and developed to support emergency management activities. Recommendations are made for research needs that will contribute to the enhancement of the security of water distribution systems.
RESUMEN
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.