Finding Resilient Networks: Measuring Resilience in Post-Extreme Event Reconstruction Missions

2014 ◽  
pp. 181-199 ◽  
Author(s):  
Steve Scheinert ◽  
Louise K. Comfort
Keyword(s):  
Extreme Event ◽  
Event Reconstruction ◽  
Resilient Networks

National coastal management challenges and needs

Shore & Beach ◽  
2020 ◽  
pp. 34-43
Author(s):  
Nicole Elko ◽  
Tiffany Roberts Briggs
Keyword(s):  
Coastal Management ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Local Community ◽  
Extreme Event ◽  
Technical Information ◽  
Interdisciplinary Approach ◽  
Beach Erosion ◽  
The U.S

In partnership with the U.S. Geological Survey Coastal and Marine Hazards and Resources Program (USGS CMHRP) and the U.S. Coastal Research Program (USCRP), the American Shore and Beach Preservation Association (ASBPA) has identified coastal stakeholders’ top coastal management challenges. Informed by two annual surveys, a multiple-choice online poll was conducted in 2019 to evaluate stakeholders’ most pressing problems and needs, including those they felt most ill-equipped to deal with in their day-to-day duties and which tools they most need to address these challenges. The survey also explored where users find technical information and what is missing. From these results, USGS CMHRP, USCRP, ASBPA, and other partners aim to identify research needs that will inform appropriate investments in useful science, tools, and resources to address today’s most pressing coastal challenges. The 15-question survey yielded 134 complete responses with an 80% completion rate from coastal stakeholders such as local community representatives and their industry consultants, state and federal agency representatives, and academics. Respondents from the East, Gulf, West, and Great Lakes coasts, as well as Alaska and Hawaii, were represented. Overall, the prioritized coastal management challenges identified by the survey were: Deteriorating ecosystems leading to reduced (environmental, recreational, economic, storm buffer) functionality, Increasing storminess due to climate change (i.e. more frequent and intense impacts), Coastal flooding, both Sea level rise and associated flooding (e.g. nuisance flooding, king tides), and Combined effects of rainfall and surge on urban flooding (i.e. episodic, short-term), Chronic beach erosion (i.e. high/increasing long-term erosion rates), and Coastal water quality, including harmful algal blooms (e.g. red tide, sargassum). A careful, systematic, and interdisciplinary approach should direct efforts to identify specific research needed to tackle these challenges. A notable shift in priorities from erosion to water-related challenges was recorded from respondents with organizations initially formed for beachfront management. In addition, affiliation-specific and regional responses varied, such as Floridians concern more with harmful algal blooms than any other human and ecosystem health related challenge. The most common need for additional coastal management tools and strategies related to adaptive coastal management to maintain community resilience and continuous storm barriers (dunes, structures), as the top long-term and extreme event needs, respectively. In response to questions about missing information that agencies can provide, respondents frequently mentioned up-to-date data on coastal systems and solutions to challenges as more important than additional tools.

Methods for Calculation of Annual and Extreme Overflow Events from Combined Sewer Systems

1984 ◽  
Vol 16 (8-9) ◽  
pp. 311-325 ◽  
Author(s):  
N B Johansen ◽  
P Harremoës ◽  
M Jensen
Keyword(s):  
Extreme Event ◽  
Short Term ◽  
Sewer Systems ◽  
Extreme Load ◽  
Combined Sewer ◽  
Receiving Waters ◽  
Water Problems ◽  
Source Of Pollution ◽  
Receiving Water

Overflow from combined systems constitute an increasing source of pollution of receiving waters, as compared to daily wastewater discharges which undergo treatment to a still higher extent. The receiving water problems from overflows are significant both in a long term scale (mean annual load) and in a short term scale (extreme event load). A method for computation of both annual and extreme load is presented. It is based on historical rain series and the use of a time-area model and simple pollutant mixing model in runoff calculation. Statistical calculations for both mean annual load and extreme events have been applied to the computed overflow series. Based on the computerized method simple manual calculations methods have been developed, resulting in graphs and tables for annual load and extreme load.

scholarly journals Evaluating the accuracy and uncertainty of atmospheric and wave model hindcasts during severe events using model ensembles

2021 ◽  
Author(s):  
Ali Abdolali ◽  
Andre van der Westhuysen ◽  
Zaizhong Ma ◽  
Avichal Mehra ◽  
Aron Roland ◽  
...  
Keyword(s):  
Extreme Event ◽  
Numerical Models ◽  
Model Performance ◽  
Ground Truth ◽  
Wave Model ◽  
Atmospheric Model ◽  
Stationary Source ◽  
Source Point ◽  
Spectral Wave Model ◽  
Model Ensembles

AbstractVarious uncertainties exist in a hindcast due to the inabilities of numerical models to resolve all the complicated atmosphere-sea interactions, and the lack of certain ground truth observations. Here, a comprehensive analysis of an atmospheric model performance in hindcast mode (Hurricane Weather and Research Forecasting model—HWRF) and its 40 ensembles during severe events is conducted, evaluating the model accuracy and uncertainty for hurricane track parameters, and wind speed collected along satellite altimeter tracks and at stationary source point observations. Subsequently, the downstream spectral wave model WAVEWATCH III is forced by two sets of wind field data, each includes 40 members. The first ones are randomly extracted from original HWRF simulations and the second ones are based on spread of best track parameters. The atmospheric model spread and wave model error along satellite altimeters tracks and at stationary source point observations are estimated. The study on Hurricane Irma reveals that wind and wave observations during this extreme event are within ensemble spreads. While both Models have wide spreads over areas with landmass, maximum uncertainty in the atmospheric model is at hurricane eye in contrast to the wave model.

scholarly journals Medico-Legal Opinion Based on Autopsy Findings of a Victim of an Explosion Involving Mass Fatality

2020 ◽  
Vol 10 (3-4) ◽  
pp. 158-165
Author(s):  
Yalini Thivaharan ◽  
Indira Deepthi Gamage Kitulwatte
Keyword(s):  
Legal Issues ◽  
Temporal Region ◽  
Skull Fractures ◽  
Autopsy Findings ◽  
Parietal Lobes ◽  
Event Reconstruction ◽  
Police Personnel ◽  
Autopsy Examination ◽  
Mass Fatality ◽  
The Brain

Introduction: Investigation into explosions is one of the major areas in forensic medicine and pathology. Medico legal issues associated with these deaths are diverse and forensic experts are often expected to make clarifications. Assistance of a methodical scientific investigation of such a death in evaluation of unanswered medico legal issues, of an autopsy of one of the victims of Easter Sunday explosions is discussed. Case history: The deceased was a 15-year-old girl who was participating in the Easter mass at St. Sebastian’s Church - Kattuwapaitya, Negombo, Sri Lanka when a suicide bomber blew himself up. The mother of the deceased noticed the deceased being rushed to the hospital. However, she was pronounced dead on admission. Pre-autopsy radiology revealed spherical shrapnel in the temporal region. At autopsy, the fatal injury was found on the head and a detailed study revealed skull fractures associated with penetration by 3 shrapnels. There was a keyhole lesion among the penetrations. Internal examination revealed an extensive dural tear underlying the compound fracture. The brain was grossly edematous with lacerations on the frontal and parietal lobes associated with localized subarachnoid hemorrhage. There were multiple underlying contusions on bilateral frontal white matter. Small subarachnoid haemorrhage was noted on the basal aspect of the brain. Discussion: Careful evaluation of the autopsy findings assisted in formulating the opinion scientifically on event reconstruction including the proximity of the victim to the epicenter of explosion and nature of explosive device, period of survival, mechanism of causation of skull fractures and the mechanism of death in addition to the cause of death. Conclusion: A forensic pathologist following a meticulous autopsy examination, along with a team of ballistic experts and specially trained police personnel play a pivotal task in analyzing a scene of explosion and an autopsy of a victim, in concluding the case and in bringing justice to all the victims and survivors of the catastrophe.

scholarly journals Combine and conquer: event reconstruction with Bayesian Ensemble Neural Networks

2021 ◽  
Vol 2021 (4) ◽  
Author(s):  
Jack Y. Araz ◽  
Michael Spannowsky
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Top Quark ◽  
Feature Space ◽  
Training Sample ◽  
Bayesian Techniques ◽  
Training Sample Size ◽  
Event Reconstruction ◽  
Neural Network Classifiers ◽  
Quark Jets

Abstract Ensemble learning is a technique where multiple component learners are combined through a protocol. We propose an Ensemble Neural Network (ENN) that uses the combined latent-feature space of multiple neural network classifiers to improve the representation of the network hypothesis. We apply this approach to construct an ENN from Convolutional and Recurrent Neural Networks to discriminate top-quark jets from QCD jets. Such ENN provides the flexibility to improve the classification beyond simple prediction combining methods by linking different sources of error correlations, hence improving the representation between data and hypothesis. In combination with Bayesian techniques, we show that it can reduce epistemic uncertainties and the entropy of the hypothesis by simultaneously exploiting various kinematic correlations of the system, which also makes the network less susceptible to a limitation in training sample size.

scholarly journals Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1727
Author(s):  
Valerio Capecchi ◽  
Andrea Antonini ◽  
Riccardo Benedetti ◽  
Luca Fibbi ◽  
Samantha Melani ◽  
...  
Keyword(s):  
Extreme Event ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Radar Data ◽  
Flash Floods ◽  
Precipitation Event ◽  
Weather Research And Forecasting ◽  
Limited Area ◽  
Heavy Precipitation Event ◽  
The Town

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts.

Characteristics of 2020 stock market crash: The COVID-19 induced extreme event

2021 ◽  
Vol 31 (5) ◽  
pp. 053115
Author(s):  
Ajit Mahata ◽  
Anish Rai ◽  
Md. Nurujjaman ◽  
Om Prakash ◽  
Debi Prasad Bal
Keyword(s):  
Stock Market ◽  
Extreme Event ◽  
Stock Market Crash

Investigating extreme event loading on coastal bridges using wireless sensor technology

2017 ◽  
Author(s):  
Douglas A. Gelineau ◽  
Justin R. Davis ◽  
Jennifer A. Rice
Keyword(s):  
Extreme Event ◽  
Wireless Sensor ◽  
Sensor Technology ◽  
Coastal Bridges

scholarly journals Stochastic event reconstruction of atmospheric contaminant dispersion using Bayesian inference

2008 ◽  
Vol 42 (33) ◽  
pp. 7718-7727 ◽  
Author(s):  
Inanc Senocak ◽  
Nicolas W. Hengartner ◽  
Margaret B. Short ◽  
W. Brent Daniel
Keyword(s):  
Bayesian Inference ◽  
Contaminant Dispersion ◽  
Event Reconstruction ◽  
Stochastic Event
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