7.6 Importance of Soil Moisture in Understanding and Predicting Fire Danger: A Review of Some Recent Research

Wednesday, 3 May 2023: 2:45 PM
Scandinavian Ballroom Salon 4 (Royal Sonesta Minneapolis Downtown )
J. D. Carlson, Oklahoma State Univ., Stillwater, OK; and E. S. Krueger, T. E. Ochsner, D. M. Engle, D. Twidwell, S. D. Fuhlendorf, S. Sharma, and M. R. Levi

The increasing availability of soil moisture information represents an opportunity to better understand the relationship of soil moisture to wildland fire danger. Surrogates based on simple models, such as the Keetch-Byram Drought Index (KBDI), have been and still continue to be used as a way to estimate soil moisture. However, sources of soil moisture information from in-situ soil moisture monitoring networks (e.g., Oklahoma Mesonet), remote sensing from satellites, and more sophisticated models provide an opportunity to use soil moisture on a broader scale to assess and predict fire danger than in the past (Krueger et al., 2022, Int. J. Wildland Fire). Use of such information, whether directly measured, remotely sensed, or modeled, could be integrated into existing or future fire danger prediction systems for more effective fire management.

This presentation will review some of the work related to soil moisture that was conducted by our research group at Oklahoma State University (and others associated with us) over the past decade and which is described in six journal articles published from 2015 through 2022. The research shows the potential for using soil moisture information in the following areas: (1) as a supplement or replacement for drought and dryness indices, (2) for estimation of live fuel moisture, (3) for estimation of herbaceous fuel curing, and (4) for the estimation of fuel loads, particularly in grasslands.

A number of our past studies have provided strong indirect evidence of the importance of soil moisture to large growing-season wildfires (“large” defined as >= 1000 acres and “growing season” as May through October in Oklahoma). In one study (Krueger et al., 2015, Soil Science Society of America J.) over 38,000 Oklahoma wildfires from 2000-2012 were grouped according to five fire size classes and analyzed with respect to soil moisture data obtained from the Oklahoma Mesonet, the state’s automated weather station network of 120 sites. Soil moisture was represented here and elsewhere as “fraction of plant available water” (FAW) in the top 16” of soil, a value typically ranging from 0 (no plant available water) to 1 (soil column saturated). The most noteworthy finding was that 100% of large growing-season wildfires (>= 1000 acres) occurred at FAW < 0.5 with 87% of them occurring at FAW < 0.2. Thus, low values of FAW are seen as good predictors of large growing-season wildfires. A second study (Krueger et al., 2016, Int. J. Wildland Fire) provided further evidence for this conclusion. Using a different database of Oklahoma wildfires from 2000-2012, 501 large fires (>= 1000 acres) were studied with respect to soil moisture. Scatter plots for both number of growing season fires and total acres burned during the growing season showed highest values of each associated with FAW < 0.2.

In another study (Krueger et al., 2017, Soil Science Society J. of America) involving the same 501 large fires (>= 1000 acres), we analyzed the performance of KBDI versus FAW as indicators of fire danger. Neither KBDI nor FAW accurately represented dormant-season wildfire danger, but during the growing season, a greater percentage of large wildfires occurred under extreme levels of FAW (0-0.25) than under equivalent levels of KBDI (600-800). Furthermore, while FAW represented soil moisture in near real-time, KBDI responded more slowly to drying and recharge. FAW provided an average of about 10 days earlier warning of extreme wildfire potential for the 10 largest growing season wildfires in the study (and in some cases, up to two months earlier warning). These findings indicate that the link to wildfire danger is stronger for FAW (directly measured soil moisture) than soil moisture surrogates like KBDI.

While the past research cited provides indirect evidence for the relationship of high fire danger to low values of soil moisture during the growing season, a study addressing the physical mechanisms for this relationship is now described. This study (Sharma et al., 2021, Int. J. Wildland Fire) involved direct measurements and calculations of fuel moisture and fuel loads from an intensive field study in Oklahoma grasslands we conducted using biweekly sampling during 2012-2013. While dead fuel moisture itself was unrelated to FAW during the study period, the fuel moisture of the mixed fuel bed (dead + live) decreased linearly as FAW values dropped below 0.59, with no change in fuel moisture above that value. The curing rate (transition of live to dead fuel) increased linearly as FAW dropped below 0.30, with no curing taking place at higher values. At FAW values around 0.20, the recommended threshold for extreme fire danger in our grassland studies, the transition from live to dead fuel reached daily rates greater than 10 grams per square meter. In the future, estimating mixed (or live) fuel moisture and curing rates for herbaceous fuels could contribute to better dynamic representations of fuel bed parameters in fire danger models in similar grassland ecosystems.

In another study (Krueger et al., 2021, Agronomy J.), yields of wild hay across Oklahoma were linearly related to FAW values during the critical period for hay yield (June and July), with higher FAW values corresponding to higher yields. This study suggests that fuel loads in herbaceous fuel models could be dynamically adjusted based on soil moisture values.

The presentation will conclude with a brief discussion of how soil moisture information might be integrated into fire danger rating systems, using NFDRS2016 as an example.

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