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Daniel, William Brent

Publications and source records attributed to Daniel, William Brent.

5 records
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DOE OSTI2023

Extremely rapid, Lagrangian modeling of 2D flooding: A rivulet-based approach

Estimates of potential flood inundation areas and depths are critical to informing the preparedness, response, and investment decisions of many government agencies and private sector organizations, especially under a changing climate. The standard modeling approaches, however, are often either computationally intensive or constrained in their accuracy or applicability. A novel, rivulet-based, 2D model of pluvial flooding is described in this article that is 10,000 to 10 million times less computationally complex than the full solution of the shallow water equations, yet achieves inundation area hit rates of between 0.8 and 0.9 and relative absolute mean errors of 10%-20% across a wide range of flow depths. This combination of accuracy and efficiency will enable real-time depth estimates during flood events, detailed sensitivity analyses, and the generation of large ensembles to support broad uncertainty analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Building a better framework for evaluating human well-being impacts in global change analysis: The example of energy security

Human well-being can be greatly impacted by the global environmental and socio-economic change captured in Integrated Models of Global Change (IMGCs). Though most IMGCs address some aspects of well-being, their underlying modeling approach and ‘philosophy’ differ widely, and some key elements – like energy security – are omitted. In this report, we describe a project in which we set out to a create a framework through which the well-being dimensions of the household are connected to key drivers of socio-economic and environmental change – and how the needed metrics, data and modeling methods can be brought to bear. We focus on the well-being dimensions of energy, and lay out the necessary elements to capturing household energy security – using household energy burden as the relevant metric. We begin by showing the conceptual linkage of energy burden to environmental drivers like temperature change, using a simple and straightforward conceptual framework. We then go further to use the example of GCAM-USA to show how some key analytical features of the model can provide insight into how energy security across different groups can change along alternative pathways to sustainability. We compare our preliminary assessment of household energy burden to existing data and suggest further steps to improve and refine this analysis in future research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

A Systematic Evaluation of Traditional and Non-Traditional Data Streams for Integrated Global Biosurveillance (Final Report)

Living in a closely connected and highly mobile world presents many new mechanisms for rapid disease spread and in recent years, global disease surveillance has become a high priority. In addition, much like the contribution of non-traditional medicine to curing diseases, non-traditional data streams are being considered of value in disease surveillance. Los Alamos National Laboratory (LANL) was tasked by the Defense Threat Reduction Agency (DTRA)-Joint Science and Technology Office (JSTO) to determine the relevance of data streams for an integrated global biosurveillance system through the use of defined metrics and methodologies. The long-term, broad objective of this project was to provide information and analysis that can be leveraged from existing and developing national and international disease surveillance systems and methodologies, to create a global disease monitoring system, ultimately providing decision makers with timely information to prepare for and mitigate the spread of disease. Specifically, this project evaluated data streams that are currently being used in surveillance systems and data streams that had the potential for being used in surveillance to enable early disease detection. LANL’s focus was on infectious disease surveillance and the term “biosurveillance” will be used to refer to this scope hereafter. Data stream evaluation was conducted using two different methods: Multi criteria decision analysis (MCDA) using a tool called Logical Decisions ® that assigns utility scores to data streams based on weighted metrics and assigned values specific to data stream categories; and a Surveillance Window concept developed at LANL that assigns a window or windows of time specific to a disease within which information coming from various data streams can be determined to have utility. A cross method analysis was performed between the surveillance window based evaluation and the MCDA-based evaluation to identify data stream categories that showed high utility for both methods. In addition, algorithms that can integrate useful data streams to facilitate early disease detection were also examined. This project provided an understanding of data streams relevant to early warning, early detection and monitoring of disease outbreaks. The report describes the results of LANL’s evaluation of 16 data stream categories using the two methods, and recommendations for next steps. The project evolved significantly over its course, and significant improvements in our approaches were made compared to the initial proposed processes. A key outcome of this effort was that LANL was able to bring together several diverse entities involved in disease surveillance and lay the foundation for new collaborations that straddled military and civilian health surveillance. The robust evaluation framework developed by LANL has generated significant interest and there is interest in adopting this framework for various applications both within disease surveillance as well as other public health initiatives. Finally, LANL developed the Biosurveillance Resource Directory (BRD), a relational database that underwent pilot testing by members of the human, plant and animal disease surveillance community. The BRD is intended to be a global resource to facilitate rapid information access.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2010

Predicting reaerosolization

Outdoor studies of the environmental persistence of bacteria have led to many interesting results. It turns out that the initial deposition of bacteria is not the end of the story. We examined both the ongoing daily deposition and aerosolization of bacteria for two weeks following an initial deposition event. Differences between samples collected in a clearing and those collected beneath a forest canopy were also examined. There were two important results: first, bacteria were still moving about in significant quantities after two weeks, though the local environment where they were most prevalent appeared to shift over time; second, we were able to develop a simple mathematical model that could fairly accurately estimate the average daily airborne concentration of bacteria over the duration of the experiment using readily available environmental information. The implication is that deposition patterns are very likely to shift over an extended period of time following a release, possibly quite significantly, but there is hope that we may be able to estimate these changes fairly accurately.

54 ENVIRONMENTAL SCIENCES↗