Collaborative prediction: Allocating wildfire resources early
In recent decades, the threat to life and property from “fast fires” on the southern Great Plains has escalated, and wildfires have become a prominent natural hazard on the plains of Texas and Oklahoma. Southern Great Plains wildfire outbreaks (SGPWOs) are dangerous multifaceted phenomena characterized by dozens of wind-driven wildfires that burn tens, or even hundreds of thousands of acres.
These plains firestorms are triggered by an alignment of critical fire weather (low relative humidity and strong surface wind) and abundant dry vegetation. The impacts of SGPWOs can be devastating, and Texas A&M Forest Service (TAMFS) has coined them “a perfect storm for fire.”
Distinctive weather systems contribute to SGPWOs, typically a fast moving low pressure cyclone over Kansas. National Weather Service (NWS) meteorologists have developed conceptual models to increase their predictability. As a result, advance warnings have improved from an average of two days’ notice in 2011, when eight SGPWOs contributed to a record fire season in Texas, to six days before a devastating Oklahoma firestorm in March 2025. This lead time gives authorities more time to prepare.
To ready fire, land, and emergency management officials for such violent wildfire outbreaks, forecasts based on the atmospheric conceptual models are produced by a multidisciplinary working group of meteorologists and fire analysts via coordinated probabilistic wildfire predictions. This group was established following a multi-agency meeting at College Station, Texas, in late 2010 with the objective of applying newly emerging science to wildfire forecasts. Initially composed of only two NWS meteorologists and a single forestry analyst, the working group has since grown into a collaborative online community of nearly 300 forecasters and governmental fire experts across Texas, Oklahoma, Kansas, and beyond, who continuously monitor for conditions that may spawn wildfire outbreaks. In this partnered approach, meteorologists identify upcoming weather systems depicted by computer models that are similar to past firestorms. Typically, the parent storm produces intense wind patterns in the upper atmosphere that descend into hot and dry air near the ground. Once a candidate cyclone is identified in weather computer models, NWS meteorologists work hand in hand with fire analysts at state forestry agencies to determine if, when, and where the forecast weather features will align with fire-susceptible vegetation on the landscape.
Conventional predictions published by a single agency typically focus on exceedance of critical weather or vegetative-fuel dryness thresholds. In contrast, the multidisciplinary working group leverages wide-reaching expertise to forecast wildfire occurrence. As such, they communicate the probability that fires will exceed critical size thresholds and provide guidance that supports informed decision-making, as compared to traditional red flag warnings. This guidance has influenced mitigation efforts by state agencies prior to high-impact wildfires in the region for more than a decade, including pre-fire deployment of firefighting personnel and resources.
Methodology and limitations
This study uses TAMFS and Oklahoma Forestry Services (OFS) records that tracked movement of firefighting resources to help quantify the value of decision support provided by the interdisciplinary working group. Expenses related to pre-positioning ground- and air-based resources are compared to the value of at-risk housing units and structures and agricultural assets saved versus lost, to determine the net economic value (NEV) and return on investment (ROI) derived from the interagency partnership between 2022 and 2024.
NEV = Structures Saved – (Structures Lost + Agricultural Losses + Deployment Expenses)
Agency response for 48 dates on which predictions were provided by the working group were examined. Resources allocated within the lead time provided by the outlooks were considered to be influenced by the outlooks. For instance, if forecasts were made five days prior to a potential event, and firefighting resources were deployed to areas of higher probability of danger four days in advance, those expenses were deemed to be influenced by the information in the prediction’s threat messaging. A total of 18 working group forecasts were associated with mobilizations across the two states within the study period, including 16 mobilizations in Oklahoma. OFS is a first-response agency that enacted relatively small mobilizations at an average expense of $302,424, including days of low probability risks. On five dates analyzed by the working group, resources were moved in Texas, where TAMFS is a mutual aid organization that made larger deployments at an average cost of $2,762,106 in response to higher-probability threats.
OFS records included aggregated expenses for each event, as well as counts and values of primary (homes and businesses) and secondary (barns and outbuildings) structures saved and lost. TAMFS data included itemized lists of prepositioned firefighting resources (personnel and equipment) for each event, as well as counts and values of homes saved and lost, and expenses related to aircraft positioning. In some cases, reimbursement rates for firefighting vehicles were determined by Federal Emergency Management Administration standards. U.S. Census Bureau data were also used to corroborate reports of saved homes.
An important limitation of this study is that the analysis was not conducted by economists. However, it is challenging to assign monetary costs to the loss of livelihoods and societal disruptions experienced during disasters, including the loss of human life and downstream impacts on human health and commerce. The intention of the study is to inspire professionals and provide a foundation for experts to appraise the value of science-based decision support services in the future.
Based on available data, it was sometimes difficult to attribute specific mitigation expenses directly to the working group’s outlooks. For instance, it is likely that some resources would have been mobilized and preparatory expenses incurred based solely on legacy forecasts, fire weather watches, and red flag warnings. However, key decision makers from both OFS and TAMFS have suggested that the predictions of wildfire outbreaks provided by the working group transformed fire operations from reactive to proactive and enabled the movement of equipment, firefighters, and other resources. Thus, by only accounting for resource movement that occurred during lead times of the working group’s outlooks, it is likely that the allocations were influenced by these decision support services.
The Eastland Complex fire
A destructive SGPWO burned 68,915 acres in central and northwestern Texas on March 17, 2022. The most notable fire, the Eastland Complex (Fig. 1), caused extensive damage in Carbon, Texas. Per TAMFS records, 164 structures worth $25,377,876 were destroyed. The fires killed a law enforcement officer and injured two other people. An additional $23,100,000 in agricultural losses were reported.
The interagency working group began to craft predictions that defined the threat on March 14. Their conclusions predicted a moderate probability of significant wildfires and a possible SGPWO (50% probability of ≥5,000-acre fires over West Central Texas) and informed decisions to strategically pre-stage vital firefighting resources. In all, officials in Texas moved 161 firefighters, 52 engines, 13 trucks, 6 rotor and 13 fixed-wing aircraft, including two large air tankers, into position up to three days prior to the outbreak at a cost of $2,267,047 (Fig. 2). These resources supplemented existing local and state firefighting infrastructure and provided mutual aid that assisted in suppression and protection efforts that saved 1,217 structures with an estimated value of $203,514,903, according to TAMFS datasets. A housing analysis suggests that 81% of the homes inside the Eastland Complex fire perimeter were saved. The NEV of firefighting efforts, including deployed resources, was calculated to be $152,769,980.
A holistic approach
The analysis summarized here and illustrated by the March 17, 2022, fires reveals that multidisciplinary wildfire predictions influenced pre-fire deployment of firefighting resources that contributed to a total of $800,710,450 (NEV) in property saved between 2022 and 2024. ROIs for 2022-2024 were 76.9% in Oklahoma and 31% in Texas. For each potential wildland fire episode that the working group predicted and agencies acted upon, combined average investments of $888,062 in preparatory expenditures resulted in average property savings of $48,965,591 for an average NEV of $38,129,069. Positive economic impacts were realized in 14 (66.7%) of the working group–influenced deployments. There were negative economic outcomes in 7 (33.3%) of the cases in which agencies invested in mitigative actions prior to fire outbreaks, because the value of saved structures did not exceed investments. No trackable resource mobilizations were identified for 30 of the 48 (63%) predicted potential fire events in the 2022-2024 study period. In such instances, resources were either previously in place or not deployed. Although constituting many more dates, the total value of property saved from fire in those instances was significantly less at $1,215,000. Future studies may refine this approach to include long-term, post-fire effects on commerce and health, which will likely reduce NEVs presented here.
Wildland fire is a natural phenomenon that requires a multidisciplinary response. To quote renowned fire scholar Stephen Pyne, “If an agency stays only within its jurisdictional boundaries, it will fail.” This sums up the complexities of wildfire response. Replicating similar collaborative science-based approaches in preparation for dangerous fire weather episodes is consistent with the agency’s objectives. Thus, NWS is adopting a more nimble and efficient face-to-face delivery of meteorological, impact-based decision support to core partner agencies. Unlike other purely atmospheric hazards within the scope of NWS operations, such as tornadoes or blizzards, those responsible to mitigate fire must “address how fire really exists, and not how select sciences can handle it,” as advocated by Pyne. This study demonstrates a paradigm in which meteorologists and fire analysts collaborate on forecasts of the holistic (weather and fuels) environment to contribute to local and state preparation for impending fire threats. It is “good government” and has proven to be a financial benefit to taxpayers through saved properties and has likely saved lives.