scholarly journals Sea Level Rise Threatens Hundreds of Wastewater Treatment Plants

Eos ◽  
2018 ◽  
Vol 99 ◽  
Author(s):  
Emily Underwood

Untreated sewage could affect 5 times more people than direct flooding, a new study shows.

2021 ◽  
Vol 11 (15) ◽  
pp. 6694
Author(s):  
Qing Sun ◽  
Rouzbeh Nazari ◽  
Maryam Karimi ◽  
MD Golam Rabbani Fahad ◽  
Robert W. Peters

Wastewater treatment plants (WWTPs) in the City of New York, United States, are particularly vulnerable to frequent extreme weather events, including storm surges, high-intensity rainfall, and sea level rise, and are also affected by the cascade of these events. The complex structural configuration of WWTPs requires very fine-scale flood risk assessment, which current research has not pursued. We propose a robust technique to quantify the risk of inundations for the fourteen WWPTs through an automated sub-basin creation tool; 889 sub-basins were generated and merged with high-resolution building footprint data to create a comprehensive database for flood inundation analysis. The inundation depths and extents for the WWTPs and flood-prone regions were identified from hydrodynamic modeling of storm surge and sea level rise. The economic damage due to flooding for the WWTPs was also quantified using the HAZUS-MH model. Results indicated that the storm surges from various categories of hurricanes have the dominant impacts on flood depths around WWTPs, followed by high-intensity rainfall. Sea level rise was shown to have a relatively minor impact on flood depths. Results from economic damage analysis showed that the WWTPs are subjected to damage ranging from USD 60,000 to 720,000, depending on the size of the WWTP and the extremity of storm surge. The method of analyzing the inundation status of the research object through the sub-basin enables more accurate data to be obtained when calculating the runoff. It allows for a clearer view of the inundation status of the WWTPs when combined with the actual buildings. Using this database, predicting flood conditions of any extreme event or a cascade of extreme events can be conducted quickly and accurately.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Peter Hammond ◽  
Michael Suttie ◽  
Vaughan T. Lewis ◽  
Ashley P. Smith ◽  
Andrew C. Singer

AbstractMonitoring and regulating discharges of wastewater pollution in water bodies in England is the duty of the Environment Agency. Identification and reporting of pollution events from wastewater treatment plants is the duty of operators. Nevertheless, in 2018, over 400 sewage pollution incidents in England were reported by the public. We present novel pollution event reporting methodologies to identify likely untreated sewage spills from wastewater treatment plants. Daily effluent flow patterns at two wastewater treatment plants were supplemented by operator-reported incidents of untreated sewage discharges. Using machine learning, known spill events served as training data. The probability of correctly classifying a randomly selected pair of ‘spill’ and ‘no-spill’ effluent patterns was above 96%. Of 7160 days without operator-reported spills, 926 were classified as involving a ‘spill’. The analysis also suggests that both wastewater treatment plants made non-compliant discharges of untreated sewage between 2009 and 2020. This proof-of-principle use of machine learning to detect untreated wastewater discharges can help water companies identify malfunctioning treatment plants and inform agencies of unsatisfactory regulatory oversight. Real-time, open access flow and alarm data and analytical approaches will empower professional and citizen scientific scrutiny of the frequency and impact of untreated wastewater discharges, particularly those unreported by operators.


Eos ◽  
2017 ◽  
Author(s):  
Alex Fox

Cities typically build wastewater treatment facilities in low-lying areas. A new national study identifies which plants are most vulnerable to coastal flooding.


2018 ◽  
Vol 6 (4) ◽  
pp. 622-633 ◽  
Author(s):  
Michelle A. Hummel ◽  
Matthew S. Berry ◽  
Mark T. Stacey

Eos ◽  
2020 ◽  
Vol 101 ◽  
Author(s):  
Kate Wheeling

Researchers identify the main sources of uncertainty in projections of global glacier mass change, which is expected to add about 8–16 centimeters to sea level, through this century.


Sign in / Sign up

Export Citation Format

Share Document