Observing the Dynamics of Wildland Grass Fires: FireFlux—A Field Validation Experiment

2007 ◽  
Vol 88 (9) ◽  
pp. 1369-1382 ◽  
Author(s):  
Craig B. Clements ◽  
Shiyuan Zhong ◽  
Scott Goodrick ◽  
Ju Li ◽  
Brian E. Potter ◽  
...  

Grass fires, although not as intense as forest fires, present a major threat to life and property during periods of drought in the Great Plains of the United States. Recently, major wildland grass fires in Texas burned nearly 1.6 million acres and destroyed over 730 homes and 1320 other buildings. The fires resulted in the death of 19 people, an estimated loss of 10,000 head of livestock, and more than $628 million in damage, making the 2005/06 fire season the worst on record for the state of Texas. As an aid to fire management, various models have been developed to describe fire behavior. However, these models strongly emphasize fuels and fail to adequately consider the role of convective dynamics within the atmosphere and its interaction with the fire due to the lack of observational data. To fill this gap, an intensive field measurement campaign called FireFlux was conducted during February 2006 near Houston, Texas. The campaign employed a variety of instrument platforms to collect turbulence data at multiple levels within and immediately downwind of a 155 acre tall-grass prairie burn unit. This paper presents some first-time observations of atmospheric turbulent structures/fluxes associated with intense grass fires and provides a basis to further our understanding of the dynamics of grass fires and their interactions with the atmosphere.

2020 ◽  
Author(s):  
Anasuya Barik ◽  
Somnath Baidya Roy

<p>Meteorology has a strong impact on forest fires. Meteorological parameters such as temperature, relative humidity, wind speed and precipitation alter the fuel loading in forests, control the changes in spatial distribution, intensity and frequency of forest fires and changes in forest fire season. Hence, it is important to understand the relationship between forest fires and meteorological factors and build models that can simulate these relationships.</p><p>The Canadian Forest Fire Danger Rating System (CFFDRS) has been used globally to assess and predict the fire behavior in various forest ecosystems. The Fire Weather Index (FWI) of CFFDRS models the relationship between meteorology and forest fires. In this study we calibrate the FWI over Indian forests using percentile analysis and logistic regression technique and test the performance using satellite-derived (MODIS daily fire data from 2003-2018) fire count and Fire Radiative Power (FRP). As the Indian forest landscape is highly heterogeneous, we calibrate the FWI over 4 FWI zones namely Himalayan, Deciduous, Western Ghats and Thorn forests based on IGBP forest classification and Koppen climatic zones.  Five fire danger classes having thresholds of 99<sup>th</sup>, 95<sup>th</sup>, 90<sup>th</sup>, 80<sup>th</sup> and 70<sup>th</sup>of FWI percentiles have been defined with decreasing severity. Results show that the calibrated FWI is capable of simulating the forest fire behavior over India. Sensitivity studies show that temperature and relative humidity are the key controlling factors of forest fires over India.</p><p>This study is one of the first attempts to use fire models to simulate fire behavior over India. It can serve as a launchpad for further work on fire hazard prediction and effects of climate change on fire hazard in India.</p><p> </p>


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
R. Libonati ◽  
J. M. C. Pereira ◽  
C. C. Da Camara ◽  
L. F. Peres ◽  
D. Oom ◽  
...  

AbstractBiomass burning in the Brazilian Amazon is modulated by climate factors, such as droughts, and by human factors, such as deforestation, and land management activities. The increase in forest fires during drought years has led to the hypothesis that fire activity decoupled from deforestation during the twenty-first century. However, assessment of the hypothesis relied on an incorrect active fire dataset, which led to an underestimation of the decreasing trend in fire activity and to an inflated rank for year 2015 in terms of active fire counts. The recent correction of that database warrants a reassessment of the relationships between deforestation and fire. Contrasting with earlier findings, we show that the exacerbating effect of drought on fire season severity did not increase from 2003 to 2015 and that the record-breaking dry conditions of 2015 had the least impact on fire season of all twenty-first century severe droughts. Overall, our results for the same period used in the study that originated the fire-deforestation decoupling hypothesis (2003–2015) show that decoupling was clearly weaker than initially proposed. Extension of the study period up to 2019, and novel analysis of trends in fire types and fire intensity strengthened this conclusion. Therefore, the role of deforestation as a driver of fire activity in the region should not be underestimated and must be taken into account when implementing measures to protect the Amazon forest.


2021 ◽  
Vol 13 (12) ◽  
pp. 2386
Author(s):  
Aqil Tariq ◽  
Hong Shu ◽  
Qingting Li ◽  
Orhan Altan ◽  
Mobushir Riaz Khan ◽  
...  

Prescribed burning is a common strategy for minimizing forest fire risk. Fire is introduced under specific environmental conditions, with explicit duration, intensity, and rate of spread. Such conditions deviate from those encountered during the fire season. Prescribed burns mostly affect surface fuels and understory vegetation, an outcome markedly different when compared to wildfires. Data on prescribed burning are crucial for evaluating whether land management targets have been reached. This research developed a methodology to quantify the effects of prescribed burns using multi-temporal Sentinel-1 Synthetic Aperture Radar (SAR) imagery in the forests of southeastern Australia. C-band SAR datasets were specifically used to statistically explore changes in radar backscatter coefficients with the intensity of prescribed burns. Two modeling approaches based on pre- and post-fire ratios were applied for evaluating prescribed burn impacts. The effects of prescribed burns were documented with an overall accuracy of 82.3% using cross-polarized backscatter (VH) SAR data under dry conditions. The VV polarization indicated some potential to detect burned areas under wet conditions. The findings in this study indicate that the C-band SAR backscatter coefficient has the potential to evaluate the effectiveness of prescribed burns due to its sensitivity to changes in vegetation structure.


Author(s):  
Anthony DeAngelis ◽  
Francina Dominguez ◽  
Ying Fan ◽  
Alan Robock ◽  
M. Deniz Kustu ◽  
...  

1977 ◽  
Vol 57 (3) ◽  
pp. 729-733 ◽  
Author(s):  
L. C. DARLINGTON ◽  
D. E. MATHRE ◽  
R. H. JOHNSTON

Isolates of Claviceps purpurea (Fr.) Tul. originally isolated from many different grass hosts in the northern Great Plains and several other areas in the United States and England were tested for their pathogenicity to selected cultivars or lines of male-sterile wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). While there was a great range in the level of virulence, no clear-cut evidence of specific races was obtained. A few isolates were weakly virulent on two cultivars of male-sterile spring wheat but were highly virulent on the other two cultivars tested. Wheat and barley breeders are advised to use a mixture of isolates in screening germ plasm for resistance to ergot.


2005 ◽  
Vol 137 (4) ◽  
pp. 497-500 ◽  
Author(s):  
Tuilo B. Macedo ◽  
Paula A. Macedo ◽  
Robert K.D. Peterson ◽  
David K. Weaver ◽  
Wendell L. Morrill

The wheat stem sawfly, Cephus cinctus Norton (Hymenoptera: Cephidae), is an insect pest in dryland wheat cropping systems in the southern Canadian Prairies and the northern Great Plains of the United States (Morrill 1997). Yield losses caused by C. cinctus are due to reduced head weight (Holmes 1977; Morrill et al. 1992) and lodging, which decreases harvest efficiency. Estimates of yield losses in Montana alone are about US$25 million per year.


Author(s):  
Sarah L. Jackson ◽  
Sahar Derakhshan ◽  
Leah Blackwood ◽  
Logan Lee ◽  
Qian Huang ◽  
...  

This paper examines the spatial and temporal trends in county-level COVID-19 cases and fatalities in the United States during the first year of the pandemic (January 2020–January 2021). Statistical and geospatial analyses highlight greater impacts in the Great Plains, Southwestern and Southern regions based on cases and fatalities per 100,000 population. Significant case and fatality spatial clusters were most prevalent between November 2020 and January 2021. Distinct urban–rural differences in COVID-19 experiences uncovered higher rural cases and fatalities per 100,000 population and fewer government mitigation actions enacted in rural counties. High levels of social vulnerability and the absence of mitigation policies were significantly associated with higher fatalities, while existing community resilience had more influential spatial explanatory power. Using differences in percentage unemployment changes between 2019 and 2020 as a proxy for pre-emergent recovery revealed urban counties were hit harder in the early months of the pandemic, corresponding with imposed government mitigation policies. This longitudinal, place-based study confirms some early urban–rural patterns initially observed in the pandemic, as well as the disparate COVID-19 experiences among socially vulnerable populations. The results are critical in identifying geographic disparities in COVID-19 exposures and outcomes and providing the evidentiary basis for targeting pandemic recovery.


Plant Disease ◽  
2015 ◽  
Vol 99 (9) ◽  
pp. 1261-1267 ◽  
Author(s):  
J. A. Kolmer ◽  
M. E. Hughes

Collections of Puccinia triticina were obtained from rust-infected leaves provided by cooperators throughout the United States and from wheat fields and breeding plots by USDA-ARS personnel and cooperators in the Great Plains, Ohio River Valley, and southeastern states in order to determine the virulence of the wheat leaf rust population in 2013. Single uredinial isolates (490 total) were derived from the collections and tested for virulence phenotype on 20 lines of Thatcher wheat that are near-isogenic for leaf rust resistance genes. In 2013, 79 virulence phenotypes were described in the United States. Virulence phenotypes MBTNB, TNBGJ, and MCTNB were the three most common phenotypes. Phenotypes MBTNB and MCTNB are both virulent to Lr11, and MCTNB is virulent to Lr26. MBTNB and MCTNB were most common in the soft red winter wheat region of the southeastern states and Ohio Valley. Phenotype TNBGJ is virulent to Lr39/41 and was widely distributed throughout the hard red winter wheat region of the Great Plains. Isolates with virulence to Lr11, Lr18, and Lr26 were common in the southeastern states and Ohio Valley region. Isolates with virulence to Lr21, Lr24, and Lr39/41 were frequent in the hard red wheat region of the southern and northern Great Plains.


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