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June 22, 2011 (San Diego) -- Wildfires are increasing in both absolute number and severity in the American southwest and this trend is predicted to continue over decades to come. Wildfire prevention has now become a major priority, and scientists at the University of California, San Diego have received federal funding to devise descriptive and predictive simulation tools to help prevent or suppress wildfires. 

With a one-year grant* from the National Science Foundation (NSF) Office of Cyberinfrastructure, effective June 1, the UC San Diego researchers have opened a new phase for their SDFireSight project. They will develop a technical framework and computer models that will simulate the conditions that can spark a wildfire in San Diego’s ‘backcountry’. 

“The goal is to create tools that not only help in preventing wildfires, but which would also help first responders to suppress wildfires when they occur,” said Larry Smarr, principal investigator on the new NSF grant and director of the California Institute for Telecommunications and Information Technology (Calit2). “Wildfires are a nearly constant threat in large parts of San Diego, and we have made a substantial commitment to finding ways to mitigate the damage they cause.”

The simulation tools will be based on a vast amount of data collected through the existing, NSF-funded High-Performance Wireless Research and Education Network (HPWREN). In particular, computer scientists and seismologists will focus on an unburned area of the Santa Margarita Ecological Reserve, which straddles San Diego and Imperial Counties. 

“Santa Margarita is an ideal site for rapid prototyping and validation for the project,” said HPWREN Director Hans-Werner Braun, a research scientist in the San Diego Supercomputer Center (SDSC). SDSC and Calit2 are Organized Research Units of UC San Diego. “The ecological reserve is prone to the strong Santa Ana
wind events that the researchers want to study and, together with our project partners, we have deployed
wireless ground sensors across much of the territory, which are accessible via HPWREN.” 


The wireless ground sensors provide real-time data on a continuous basis through HPWREN to computer scientists in their labs on the UCSD campus at Calit2 and SDSC, and beyond. 
With $262,000 in NSF funding, the researchers will build a technical framework for integrating three-dimensional landscape models, real-time environmental data, a suite of simulation codes, and wildfire management protocols. 

This research will involve determining how best to merge elevation and ground classification datasets, couple fire propagation, atmospheric, and hydrologic simulation codes, and verify the accuracy of the coupled computations against historical wildfire data. 

Key components in the development of the technical framework include:

  • Identifying and obtaining access permissions to the wide variety of data sets needed to create the high-resolution digital model of the topography and landscape of San Diego County; and

  • Investigating how these datasets can be seamlessly "sewn together" using geographic information system (GIS) software.

“The goal here is to develop a technical framework for integrating research with decision support for public policy,” said computer scientist Smarr. “There can be no technology solution to the threat that wildfires pose, unless our researchers can work closely with emergency officials and first responders, as well as local and county-wide officials who must ultimately trust that the simulation tools we create will help rather than hinder future management of San Diego County resources.” 

The NSF award was approved as part of the Early-concept Grants for Exploratory Research (EAGER) program. The funding mechanism supports exploratory work in its early stages on untested but potentially transformative research ideas or approaches.

“EAGER awards are generally considered to be for ‘high risk, high reward’ projects,” added HPWREN’s Braun. “It is unusual for computer scientists to be asked to create computer models and simulation tools could radically improve how emergency agencies handle a wildfire, or how local officials make decisions that could prevent a wildfire in the first place. If we’re successful, the rewards could be tremendous – in saved lives and reduced property losses.”

*NSF Award #1126615: EAGER: Wildfire Modeling and Prevention Initiative: Developing a Technical Framework for Integrating Research with Public Policy Decision Support


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