Hazard Prediction Assessment Research Articles

Educating the Public for the Nuclear Reality: Understanding Likely Behaviors in the Aftermath of a Nuclear Detonation

Introduction:Amid the escalating nuclear arms race in the latter half of the 20th century, civil defense preparedness drills, commonly known as “Duck-and-Cover” drills, were practiced throughout classrooms in the United States. Since then, education and preparedness measures have been largely replaced by fire evacuation and active shooter drills. This study endeavored to understand the likely actions that members of the public may take in the event of a nuclear detonation in the 21st century.Method:Scenarios for 5 kiloton and 100 kiloton near-surface nuclear detonations were modeled using the Hazard Prediction Assessment and Capability (HPAC) software. A video was created animating the models with a voiceover that explained the initial effects of a nuclear detonation. Using the Qualtrics platform, a survey was created in which the order of behavior-based questions and the video was randomized. Lucid distributed the survey to a representative sample of the American public.Results:Among 3,087 participants, only 921 (30%) indicated their confidence in knowing what to do in the event of a nuclear detonation in their city. Participants were most likely to listen to the radio, hide in an interior room, and seal windows or doors. Two thirds indicated they would “duck and cover” (n = 2034, 66%), an action that ranked below helping others (n = 2183, 71%) and wearing a mask (n = 2174, 70%). Study participants who indicated their likely behaviors after watching the video were significantly more likely to listen to the radio (p = 0.044) than those who answered such questions before watching the video.Conclusion:The results of this study suggest there remains a need for emergency preparedness education for members of the public in the United States. As the threat of a nuclear detonation grows, educational methods such as video explanations may increase the preparedness of the American public.

Simulation of Airborne Transport and Dispersion for Urban Waterside Releases

AbstractResults are presented from a tracer-release modeling study designed to examine atmospheric transport and dispersion (“T&D”) behavior surrounding the complex coastal–urban region of New York City, New York, where air–sea interaction and urban influences are prominent. The puff-based Hazard Prediction Assessment Capability (HPAC, version 5) model is run for idealized conditions, and it is also linked with the urbanized COAMPS (1 km) meteorological model and the NAM (12 km) meteorological model. Results are compared with “control” plumes utilizing surface meteorological input from 22 weather stations. In all configurations, nighttime conditions result in plume predictions that are more sensitive to small changes in wind direction. Plume overlap is reduced by up to 70% when plumes are transported during the night. An analysis of vertical plume cross sections and the nature of the underlying transport and the dispersion equations both suggest that heat flux gradients and boundary layer height gradients determine vertical transport of pollutants across land–sea boundaries in the T&D model. As a consequence, in both idealized and realistic meteorological configurations, waterfront releases generate greater plume discrepancies relative to plumes transported over land/urban surfaces. For transport over water (northwest winds), the higher-fidelity meteorological model (COAMPS) generated plumes with overlap reduced by about one-half when compared with that of the coarser-resolution NAM model (13% vs 24% during the daytime and 11% vs 18% during the nighttime). This study highlights the need for more sophisticated treatment of land–sea transition zones in T&D calculations covering waterside releases.

The use of probabilistic plume predictions for the consequence assessment of atmospheric releases of hazardous materials

Toxic load-based toxicity models have been increasingly applied to model the effects of atmospheric releases of hazardous materials. Although the majority of atmospheric transport and dispersion models predict only a ‘mean’ plume, real-world personnel are exposed to one of many possible individual realisations of a plume, and never to a ‘mean’ plume. Hazard prediction assessment capability (HPAC) model not only predicts the ensemble-mean dosage, but also the dosage variance, making it possible to construct a fully-probabilistic plume. We compare the ‘mean plume’ and ‘probabilistic plume’ approaches to dosage-based consequence assessment using HPAC simulations of a small-scale chemical artillery attack.

Water Body Extraction Methods Study Based on RS and GIS

Water body extraction by using remote sensing has been the most important method in the investigation of water resources, flood hazard prediction assessment and water planning with fast and accurate effectiveness. Multiple methods including unsupervised classification, supervised classification, single-band threshold, inter spectrum relation method and water index method (normalized difference water index, modified normalized difference water index, and new water index) are analyzed. Miyun reservoir and Miyun cit zone are selected as study area to find the most effective water extraction method with different usage in different time.

Comparison of Observed, MM5 and WRF-NMM Model-Simulated, and HPAC-Assumed Boundary-Layer Meteorological Variables for 3 Days During the IHOP Field Experiment

The objective of the study is to evaluate operational mesoscale meteorological model atmospheric boundary-layer (ABL) outputs for use in the Hazard Prediction Assessment Capability (HPAC)/Second-Order Closure Integrated Puff (SCIPUFF) transport and dispersion model. HPAC uses the meteorological models’ routine simulations of surface buoyancy flux, winds, and mixing depth to derive the profiles of ABL turbulence. The Fifth-Generation Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecast-Nonhydrostatic Mesoscale Model (WRF-NMM) ABL outputs and the HPAC ABL parameterisations are compared with observations during the International H2O Project (IHOP). The meteorological models’ configurations are not specially designed research versions for this study but rather are intended to be representative of what may be used operationally and thus have relatively coarse lowest vertical layer thicknesses of 59 and 36 m, respectively. The meteorological models’ simulations of mixing depth are in good agreement (±20%) with observations on most afternoons. Wind speed errors of 1 or 2 ms−1 are found, typical of those found in other studies, with larger errors occurring when the simulated centre of a low-pressure system is misplaced in time or space. The hourly variation of turbulent kinetic energy (TKE) is well-simulated during the daytime, although there is a meteorological model underprediction bias of about 20–40%. At night, WRF-NMM shows fair agreement with observations, and MM5 sometimes produces a very small default TKE value because of the stable boundary-layer parameterisation that is used. The HPAC TKE parameterisation is usually a factor of 5–10 high at night, primarily due to the fact that the meteorological model wind-speed output is at a height of 30 m for MM5 and 18 m for WRF-NMM, which is often well above the stable mixing depth. It is concluded that, before meteorological model TKE fields can be confidently used by HPAC, it would help to improve vertical resolution near the surface, say to 10 m or less, and it would be good to improve the ABL parameterisations for shallow stable conditions.

Comparisons of Transport and Dispersion Model Predictions of the Joint Urban 2003 Field Experiment

Abstract For a hazardous material release in a city or densely populated area, effective mitigation requires an understanding of the transport and dispersion of these hazards in the complex urban environment. Improved characterization and understanding of urban transport and dispersion will allow for more robust modeling. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes features to address hazardous releases within an urban environment. During the summer of 2003, a series of tracer gas releases were carried out in Oklahoma City, Oklahoma, and extensive meteorological and tracer concentration measurements were collected in a field experiment known as Joint Urban 2003 (JU03). This analysis uses the observations of JU03 to evaluate “Urban HPAC.” Twenty sets of simulations, or “predictions,” using four Urban HPAC modes and five meteorological input options, were created and compared using a variety of metrics. Strong consistency was found between the conclusions of this study and those of two previously reported Urban HPAC evaluations. For example, improved predictions were associated with the inclusion of a simple empirically based urban dispersion model within HPAC, whereas improvements associated with the inclusion of a more computationally intensive urban wind module were not found. In this study, two new results are reported. First, there was a substantial difference in the performance of Urban HPAC as a function of release time—day or night—that was not discovered earlier because the previously examined urban field experiments focused on nighttime releases only. Daytime releases tended to be underpredicted and nighttime releases tended to be overpredicted. Second, and with respect to the under- and overpredictions described above, the inclusion of the new “Micro” Stationary Wind Fit and Turbulence (SWIFT) “SPRAY” (MSS) Urban HPAC mode typically led to less underprediction during the day and less overprediction at night than the other Urban HPAC modes. In addition, predictions that included MSS typically resulted in the least scatter between observations and predictions. These improvements warrant further investigation to determine whether this conclusion can be extended to other urban environments.

Evaluation of Dispersion Forecasts Driven by Atmospheric Model Output at Coarse and Fine Resolution

Abstract Lagrangian parcel models are often used to predict the fate of airborne hazardous material releases. The atmospheric input for these integrations is typically supplied by surrounding surface and upper-air observations. However, situations may arise in which observations are unavailable and numerical model forecasts may be the only source of atmospheric data. In this study, the quality of the atmospheric forecasts for use in dispersion applications is investigated as a function of the horizontal grid spacing of the atmospheric model. The Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) was used to generate atmospheric forecasts for 14 separate Dipole Pride 26 trials. The simulations consisted of four telescoping one-way nested grids with horizontal spacings of 27, 9, 3, and 1 km, respectively. The 27- and 1-km forecasts were then used as input for dispersion forecasts using the Hazard Prediction Assessment Capability (HPAC) modeling system. The resulting atmospheric and dispersion forecasts were then compared with meteorological and gas-dosage observations collected during Dipole Pride 26. Although the 1-km COAMPS forecasts displayed considerably more detail than those on the 27-km grid, the RMS and bias statistics associated with the atmospheric observations were similar. However, statistics from the HPAC forecasts showed the 1-km atmospheric forcing produced more accurate trajectories than the 27-km output when compared with the dosage measurements.

Comparisons of Transport and Dispersion Model Predictions of the Mock Urban Setting Test Field Experiment

Abstract The potential effects of a terrorist attack involving the atmospheric release of chemical, biological, radiological, nuclear, or other hazardous materials continue to be of concern to the United States. The Defense Threat Reduction Agency has developed a Hazard Prediction Assessment Capability (HPAC) that includes initial features to address hazardous releases within an urban environment. Improved characterization and understanding of urban transport and dispersion are required to allow for more robust modeling. In 2001, a scaled urban setting was created in the desert of Utah using shipping containers, and tracer gases were released. This atmospheric tracer and meteorological study is known as the Mock Urban Setting Test (MUST). This paper describes the creation of sets of HPAC predictions and comparisons with the MUST field experiment. Strong consistency between the conclusions of this study and a previously reported HPAC evaluation that relied on urban tracer observations within the downtown area of Salt Lake City was found. For example, in both cases, improved predictions were associated with the inclusion of a simple empirically based urban dispersion model within HPAC, whereas improvements associated with the inclusion of a more computationally intensive wind field module were not found. The use of meteorological observations closest to the array and well above the obstacle array—the sonic anemometer measurements 16 m above ground level—resulted in predictions with the best fit to the observed tracer concentrations. The authors speculate that including meteorological observations or vertical wind profiles above or upwind of an urban region might be a sufficient input to create reasonable HPAC hazard-area predictions.

Use of Salt Lake City URBAN 2000 Field Data to Evaluate the Urban Hazard Prediction Assessment Capability (HPAC) Dispersion Model

Abstract After the terrorist incidents on 11 September 2001, there is a greatly heightened concern about the potential impacts of acts of terrorism involving the atmospheric release of chemical, biological, radiological, and nuclear (CBRN) materials in urban areas. In response to the need for an urban CBRN model, the Urban Hazard Prediction Assessment Capability (Urban HPAC) transport and dispersion model has been developed. Because HPAC is widely used by the Department of Defense community for planning, training, and operational and tactical purposes, it is of great importance that the new model be adequately evaluated with urban datasets to demonstrate its accuracy. This paper describes evaluations of Urban HPAC using the “URBAN 2000” urban tracer and meteorological field experiment data from Salt Lake City, Utah. Four Urban HPAC model configuration options and five plausible meteorological input data options—ranging from data-sparse to data-rich scenarios—were considered in the study, thus leading to a total of 20 possible model combinations. For the maximum concentrations along each sampling arc for each intensive operating period (IOP), the 20 Urban HPAC model combinations gave consistent mean overpredictions of about 50%, with a range over the 20 model combinations from no overprediction to a factor-of-4 overprediction in the mean. The median of the random scatter for the 20 model combinations was about a factor of 3 of the mean, with a range over the 20 model combinations between a factor of about 2 and 9. These performance measures satisfy previously established acceptance criteria for dispersion models.