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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Crustal Dynamics Data Information System (CDDIS) Contributions to GGOS

The Crustal Dynamics Data Information System (CDDIS) provides essential support for the Global Geodetic Observing System (GGOS) by operating a data and product archive for the main geodetic techniques. As GGOS matures and grows, the CDDIS adopts the latest data practices to strengthen its support for the community and ensure quality products are available in a timely manner. To this end, the CDDIS is continually refining its software backend, performing developments such as the 2023 implementation of a middleware processing system, which is successfully being used in operation to provide GNSS-based Upper Atmospheric Realtime Disaster Information and Alert Network (GUARDIAN) and Global Differential GPS System (GDGPS) products. In addition, the CDDIS has 1) released new data and products, 2) performed updates to facilitate navigation of the archive, and 3) made it easier to cite the data and products being added. This poster explores the breadth of work done at the CDDIS and provides highlights of the latest developments.

Justine Woo↗
NASA NTRSDate not supplied

Evaluating the Performance of GPM IMERG Products for Extreme Precipitation Estimation in Volta River Basin of Ghana

The Volta River basin in West Africa, covering a substantial area of Ghana, faces significant water management challenges due to highly variable rainfall and limited availability of high temporal resolution rain gauges. This study, developed under the 2024 Global Precipitation Measurement (GPM) Mission mentorship program, evaluates precipitation in the Volta River basin using high-resolution satellite-derived data from the Integrated Multi-satellite Retrievals for GPM (IMERG). In the absence of sub-daily rainfall data, comparisons were made between daily, monthly, and seasonal precipitation from local gauges and IMERG V06 and V07 (early and final) runs. Results indicated a very weak correlation between daily precipitation estimates from IMERG and gauge data, but a significantly improved correlation for monthly and seasonal estimates. Additionally, IMERG data were used to identify heavy rainfall events and drought periods, which were compared to known occurrences in the region. By addressing these objectives, this study contributes to more accurate extreme precipitation estimation in the Volta River basin, thereby enhancing disaster risk management and climate resilience in Ghana.

Jessica Sutton↗
NASA NTRS2024

Severe droughts reduce river navigability and isolate communities in the Brazilian Amazon

The Amazon basin is experiencing severe droughts that are expected to worsen with climate change. Riverine communities are especially vulnerable to these extreme events. This study investigates the experiences of Brazilian Amazonian communities during droughts occurring from 2000-2020. We assess the distribution of settlements at risk of prolonged isolation during extreme low-water periods, along with impacts reported in digital news outlets. Using historic time series of river levels from 90 gauges, we look at how long droughts lasted in regions with reported impacts. Results indicate that the droughts in 2005, 2010, and 2016 were the most severe, with over an additional month of low water levels in those years. Such drought events routinely disrupt inland water transport and isolate local populations, limiting access to essential goods (food, fuel, medicine) and basic services (healthcare, education). Given this new reality, Amazon countries must develop long-term strategies for mitigation, adaptation, and disaster response.

Geography↗
NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗
DOE OSTI2011

Community Assessment Tool for Public Health Emergencies Including Pandemic Influenza

The Community Assessment Tool (CAT) for Public Health Emergencies Including Pandemic Influenza (hereafter referred to as the CAT) was developed as a result of feedback received from several communities. These communities participated in workshops focused on influenza pandemic planning and response. The 2008 through 2011 workshops were sponsored by the Centers for Disease Control and Prevention (CDC). Feedback during those workshops indicated the need for a tool that a community can use to assess its readiness for a disaster - readiness from a total healthcare perspective, not just hospitals, but the whole healthcare system. The CAT intends to do just that - help strengthen existing preparedness plans by allowing the healthcare system and other agencies to work together during an influenza pandemic. It helps reveal each core agency partners (sectors) capabilities and resources, and highlights cases of the same vendors being used for resource supplies (e.g., personal protective equipment [PPE] and oxygen) by the partners (e.g., public health departments, clinics, or hospitals). The CAT also addresses gaps in the community's capabilities or potential shortages in resources. This tool has been reviewed by a variety of key subject matter experts from federal, state, and local agencies and organizations. It also has been piloted with various communities that consist of different population sizes, to include large urban to small rural communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2011

Adaptation and risk management

Adaptation assessment methods are compatible with the international risk management standard ISO:31000. Risk management approaches are increasingly being recommended for adaptation assessments at both national and local levels. Two orientations to assessments can commonly be identified: top-down and bottom-up, and prescriptive and diagnostic. Combinations of these orientations favor different types of assessments. The choice of orientation can be related to uncertainties in prediction and taking action, in the type of adaptation and in the degree of system stress. Adopting multiple viewpoints is to be encouraged, especially in complex situations. The bulk of current guidance material is consistent with top-down and predictive approaches, thus is most suitable for risk scoping and identification. Abroad range ofmaterial fromwithin and beyond the climate change literature can be used to select methods to be used in assessing and implementing adaptation. The framing of risk, correct formulation of the questions being investigated and assessment methodology are critical aspects of the scoping phase. Only when these issues have been addressed should be issue of specific methods and tools be addressed. The reorientation of adaptation from an assessment focused solely on anthropogenic climate change to broader issues of vulnerability/resilience, sustainable development and disaster risk, especially through a risk management framework, can draw from existing policy and management understanding in communities, professions and agencies, incorporating existing agendas, knowledge, risks, and issues they already face.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2011

EDITORIAL HPJ SPECIAL ISSUE DEDICATION

This issue is dedicated to the heroes and professionals who helped protect the world from nuclear disasters and to those who were displaced by these catastrophes.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

A Gaussian Process Based Online Change Detection Algorithm for Monitoring Periodic Time Series

Online time series change detection is a critical component of many monitoring systems, such as space and air-borne remote sensing instruments, cardiac monitors, and network traffic profilers, which continuously analyze observations recorded by sensors. Data collected by such sensors typically has a periodic (seasonal) component. Most existing time series change detection methods are not directly applicable to handle such data, either because they are not designed to handle periodic time series or because they cannot operate in an online mode. We propose an online change detection algorithm which can handle periodic time series. The algorithm uses a Gaussian process based non-parametric time series prediction model and monitors the difference between the predictions and actual observations within a statistically principled control chart framework to identify changes. A key challenge in using Gaussian process in an online mode is the need to solve a large system of equations involving the associated covariance matrix which grows with every time step. The proposed algorithm exploits the special structure of the covariance matrix and can analyze a time series of length T in O(T^2) time while maintaining a O(T) memory footprint, compared to O(T^4) time and O(T^2) memory requirement of standard matrix manipulation methods. We experimentally demonstrate the superiority of the proposed algorithm over several existing time series change detection algorithms on a set of synthetic and real time series. Finally, we illustrate the effectiveness of the proposed algorithm for identifying land use land cover changes using Normalized Difference Vegetation Index (NDVI) data collected for an agricultural region in Iowa state, USA. Our algorithm is able to detect different types of changes in a NDVI validation data set (with ~80% accuracy) which occur due to crop type changes as well as disruptive changes (e.g., natural disasters).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Managing Critical Infrastructures C.I.M. Suite

See how a new software package developed by INL researchers could help protect infrastructure during natural disasters, terrorist attacks and electrical outages. For more information about INL research, visit http://www.facebook.com/idahonationallaboratory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2012

Predictive Fallout Composition Modeling: Improvements and Applications of the Defense Land Fallout Interpretive Code

This paper outlines several improvements to the Particle Activity Module of the Defense Land Fallout Interpretive Code (DELFIC). The modeling of each phase of the fallout process is discussed within DELFIC to demonstrate the capabilities and limitations with the code for modeling and simulation. Expansion of the DELFIC isotopic library to include actinides and light elements is shown. Several key features of the new library are demonstrated, including compliance with ENDF/B-VII standards, augmentation of hardwired activated soil and actinide decay calculations with exact Bateman calculations, and full physical and chemical fractionation of all material inventories. Improvements to the radionuclide source term are demonstrated, including the ability to specify heterogeneous fission types and the ability to import source terms from irradiation calculations using the Oak Ridge Isotope Generation (ORIGEN) code. Additionally, the dose, kerma, and effective dose conversion factors are revised. Finally, the application of DELFIC for consequence management planning and forensic analysis is presented. For consequence management, DELFIC is shown to provide disaster recovery teams with simulations of real-time events, including the location, composition, time of arrival, activity rates, and dose rates of fallout, accounting for site-specific atmospheric effects. The results from DELFIC are also demonstrated for use by nuclear forensics teams to plan collection routes (including the determination of optimal collection locations), estimate dose rates to collectors, and anticipate the composition of material at collection sites. These capabilities give mission planners the ability to maximize their effectiveness in the field while minimizing risk to their collectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

An Incident Management Preparedness and Coordination Toolkit

Although the use of Geographic Information Systems (GIS) by centrally-located operations staff is well established in the area of emergency response, utilization by first responders in the field is uneven. Cost, complexity, and connectivity are often the deciding factors preventing wider adoption. For the past several years, Oak Ridge National Laboratory (ORNL) has been developing a mobile GIS solution using free and open-source software targeting the needs of front-line personnel. Termed IMPACT, for Incident Management Preparedness and Coordination Toolkit, this ORNL application can complement existing GIS infrastructure and extend its power and capabilities to responders first on the scene of a natural or man-made disaster.

data fusion↗
DOE OSTI2013

Fukushima Media Involvement: Lessons Learned and Challenges

Only days after the Fukushima nuclear reactor disaster on March 11, 2011, the Department of Energy’s Pacific Northwest National Laboratory, or PNNL, found itself in a maelstrom of media attention following announcement of the detection of minute levels of radioactive material originating from the damaged reactors 4,500 miles away. Within days, PNNL had set up a technical team in support of the U.S. government’s efforts to assist the devastated country. While a vast amount of information began to flow from Japan, the situation rapidly evolved challenging PNNL scientists and engineers, as well as news media and the general public to deal with a complex and often conflicting information stream. Over the course of about three weeks, PNNL’s News & Media Relations staff and its scientists and engineers responded to more than one hundred requests for information, and engaged in dozens of personal interviews with international, national, regional and local media. While many of the interviews and resulting stories were accurate and well done, to say that all communication went flawless would be far from the truth. In the midst of chaos and confusion, which are part of any significant crisis, hiccoughs are sure to occur. Even when communications guidelines are established and agreed-to ahead of time, and spokespeople promise to stay on message and within their areas of expertise, there is no guarantee the ball will not be dropped on occasion. Addressed here is “the rest of the story.”

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

2012 Annual Report [WESTERN AREA POWER ADMINISTRATION]

Fiscal Year 2012 brought some tumultuous and uncertain times to Western. The utility industry and technology continued to evolve, and the demand for constant flow of power and transmission system reliability continued to increase. Western kept pace by continuing to deliver reliable, cost-based hydropower while reviewing and updating business practices that took into account how the energy industry is evolving. During this time of exponential change, Western tackled many challenges, including: Reviewing the Transmission Infrastructure Program processes and procedures; Responding to Secretary of Energy Steven Chu’s memorandum to create a modern, efficient and reliable transmission grid; Weathering record-breaking natural disasters in our service territory; Completing our role in TIP’s flagship project—the Montana Alberta Tie Ltd. transmission line; Incorporating new, far-reaching regulations and industry trends.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operation purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.

cloud computing↗
DOE OSTI2014

Design and Implementation of Real-Time Off-Grid Detection Tool Based on FNET/GridEye

Real-time situational awareness tools are of critical importance to power system operators, especially during emergencies. The availability of electric power has become a linchpin of most post disaster response efforts as it is the primary dependency for public and private sector services, as well as individuals. Knowledge of the scope and extent of facilities impacted, as well as the duration of their dependence on backup power, enables emergency response officials to plan for contingencies and provide better overall response. Based on real-time data acquired by Frequency Disturbance Recorders (FDRs) deployed in the North American power grid, a real-time detection method is proposed. This method monitors critical electrical loads and detects the transition of these loads from an on-grid state, where the loads are fed by the power grid to an off-grid state, where the loads are fed by an Uninterrupted Power Supply (UPS) or a backup generation system. The details of the proposed detection algorithm are presented, and some case studies and off-grid detection scenarios are also provided to verify the effectiveness and robustness. Meanwhile, the algorithm has already been implemented based on the Grid Solutions Framework (GSF) and has effectively detected several off-grid situations.

Guo, Jiahui↗
DOE OSTI2014

Development of an Updated Societal-Risk Goal for Nuclear Power Safety

This report briefly summarizes work done in FY 2013 on the subject LDRD. The working hypothesis is that societal disruption should be addressed in a safety goal. This is motivated by the point that the Fukushima disaster resulted in very little public dose, but enormous societal disruption; a goal that addressed societal disruption would fill a perceived gap in the US NRC safety goal structure. This year's work entailed analyzing the consequences of postulated accidents at various reactor sites in the US, specifically with a view to quantifying the number of people relocated and the duration of their relocation, to see whether this makes sense as a measure of societal disruption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗