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The Hawaiian Islands experience damaging wildfires on a yearly basis. Soil moisture or lack thereof influences the amount and flammability of vegetation. Incorporating daily maximum temperatures and daily rainfall amounts, the Keetch-Byram Drought Index (KBDI) estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall...
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... examines the annual and the long-term cycles of KBDI, the KBDI variation in an El Niño cycle, as well as the atmospheric circulation patterns and equa- torial sea surface temperatures (SSTs) for composites of extreme KBDI values. Finally, the Conclusions summarize the analysis of the results and its implications for fire management in Hawaii. Fig. 1 displays the study area, which encompasses eight islands. The Hawaiian Islands are part of a linear chain of volcanoes that extend for ∼6000 km from the central to the north-west Pacific. The north-western Hawaiian Islands are the oldest and many exist only as atolls due to processes such as erosion, catastrophic landslides, and ...
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... precipitation and temperature data from 27 stations as displayed in Fig. 1 are obtained from the Western Regional Climate Center in Reno, NV. Most stations have 35 years of reliable data. A few stations contain shorter records because of insufficient data. The daily temperature and precipitation data are then put through a program to compute the daily KBDI, so that a 35-year daily record of the index is made ...
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... the annual cycle in KBDI is very similar for the northernmost islands, they will be discussed as a group. These islands include Kauai, Oahu, Molokai, Lanai and Maui (Fig. ...
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... largest Hawaiian island, and the most interesting, is the island of Hawaii (Big Island). Two main peaks, Mauna Loa (4169 m, 13 677 feet) and Mauna Kea (4205 m, 13 796 feet), dominate the landscape. As displayed in Fig. 1, Hilo Airport, Kulani Camp, and Hawaii Volcanoes National Park are located on the windward side of the island (i.e. on the eastern slope of Mauna Kea). Much of the summer rainfall in this area results from thermally driven mountain-valley winds interacting with trade winds and reinforced by land-sea breezes (Chen and Nash 1994). There ...
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... has a strong annual cycle with 95.7% of the variance accounted for (Table 1). However, the peak phase has a 180 • shift relative to most other sites with the driest period on or around March. Located to the west of Mauna Loa (Fig. 1), the site is shielded from the winter precipitation that comes from the south- east. Therefore, it tends to be the driest during that time of year. During the summer months, when the trade winds are more per- sistent, air flows through the Humu'ula Saddle and interacts with diurnal circulations causing a summer rainfall maximum in the ...
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... schematic of the vertical structure of the spring and fall anoma- lous equatorial winds for the upper and lower quartiles of KBDI is displayed in Fig. 7a, b (refer also to Figs 8 and 10). For both quartiles of KBDI, the anomalous equatorial winds have an anomalous vertical baroclinic structure with what appears to be anomalous Walker circulations. ...
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... fall is the time of peak climatological KBDI for lee- ward stations (Table 1). Dry conditions during this time will influence the exact time at which the peak KBDI occurs for individual years. An extremely dry fall may lead to peak KBDI values later in the season. Table 2 contains the years used for the fall (September to November) composite. Fig. 10a displays the anomalous 200-hPa winds for the upper quartile of KBDI in fall. Similarly to the spring, the anoma- lous equatorial 200-hPa winds are westerly to the west of the Hawaiian Islands and easterly to the east of the islands. Com- pared with the anomalous surface winds in Fig. 10b, we find anomalous equatorial easterlies to the ...
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... years used for the fall (September to November) composite. Fig. 10a displays the anomalous 200-hPa winds for the upper quartile of KBDI in fall. Similarly to the spring, the anoma- lous equatorial 200-hPa winds are westerly to the west of the Hawaiian Islands and easterly to the east of the islands. Com- pared with the anomalous surface winds in Fig. 10b, we find anomalous equatorial easterlies to the west of the island chain and anomalous westerlies to the east of the islands. Again, it appears to be an anomalous baroclinic circulation with two Walker-type cells, one near the equator to the west and one cell to the east (Fig. 7a). The anomalous surface wind and divergence map for the ...
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... equatorial easterlies to the west of the island chain and anomalous westerlies to the east of the islands. Again, it appears to be an anomalous baroclinic circulation with two Walker-type cells, one near the equator to the west and one cell to the east (Fig. 7a). The anomalous surface wind and divergence map for the upper quartile displayed in Fig. 10b shows a distinct anticyclone slightly north and west of the islands for the upper quartile, placing them in an area of increased surface divergence. The anomalous 500-hPa vertical velocities (not shown) over the island chain are ∼0.01 Pa s −1 , inferring anomalous descent. This should lead to drier conditions and higher KBDI numbers. ...
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Citations
... For instance, KBDI was first developed to communicate fire potential in the Southeastern United States (Littell et al. 2016;Keetch and Byram 1968), but it has since been applied in other locations, including portions of the contiguous USA (Lorimer and Gough 1988;Carlson et al. 2002), Hawaii (Dolling et al. 2009), Australia (Hatton et al. 1988), Turkey (Varol and Ertuğrul 2016;Fujioka et al. 2008), the Mediterranean (Garcia-Prats et al. 2015), and Malaysia (Livingston 1974). FWI is widely used operationally across the globe (Vitolo et al. 2020) and has been applied in locations including Portugal (Carvalho et al. 2008), Greece (Dimitrakopoulos et al. 2011), China (Tian et al. 2011), the UK (Jong et al. 2016), Argentina (Cardenas et al. 2013), andPeru (SENAMHI 2018). ...
Background
Fire danger indexes (FDIs) are used as proxies for fire potential and are often developed for specific locations. For practical purposes, the extrapolation of the underlying calculations into novel locations is common, but it is generally uncertain if the relationships between FDIs and fire potential observed in the environment in which the index was developed are equally relevant in others. For example, although a topographically, ecologically, and climatologically complex country, f ire danger forecasts in Peru use a standard set of nationwide thresholds applied to the Fire Weather Index. In this study, we validate the underlying assumption that weather-fire relationships are spatially uniform within Peru by (1) making cross-regional comparisons of the statistical distributions of four FDIs—Burning Index, Energy Release Component, Fire Weather Index, and Keetch-Byram Drought Index, and (2) making cross-regional comparisons of the expected daily MODIS hotspot count percentiles conditioned on FDI values.
Results
Significant regional differences in the distributions of daily FDI values were observed in every pair of regions within Peru, and with the exception of a pair of regions within the Amazon, little data (<90 days) were necessary to detect these differences. After controlling for FDI values and seasonal and annual effects with regressions, differences in predicted hotspot percentiles were common, differing by as much as 47 percentage points. Across the pairs of regions, the magnitude of these differences tended to decrease as climatic similarity increased, but some counterexamples were also apparent.
Conclusions
The noticeable differences in the distributions of daily FDI values suggest that a standard set of breakpoints may produce unreliable inferences regarding fire potential. We also find that even if the climatic conditions were similar across Peru, the same FDI values in two locations can produce substantially differing predictions of wildfire activity. This suggests that other factors besides FDI values can strongly mediate wildfire activity and that better fire potential predictions could be produced if these factors are accounted for.
... Ecological drought in Hawai'i commonly drives an increase in wildland fire occurrence [93][94][95]. Wildland fires in Hawai'i are most extensive in dry and mesic nonnative grasslands and shrublands, which cover 24% of the total land area in the state and account for approximately 80% of annual area burned [96], although, under severe drought conditions, wildfires have affected native wet forests [97,98]. During drought, wildfire risk in grasslands increases rapidly, making drought an important contributor to the invasive grass-wildfire cycle [95,99]. ...
Drought is a prominent feature of Hawaiʻi’s climate. However, it has been over 30 years since the last comprehensive meteorological drought analysis, and recent drying trends have emphasized the need to better understand drought dynamics and multi-sector effects in Hawaiʻi. Here, we provide a comprehensive synthesis of past drought effects in Hawaiʻi that we integrate with geospatial analysis of drought characteristics using a newly developed 100-year (1920–2019) gridded Standardized Precipitation Index (SPI) dataset. The synthesis examines past droughts classified into five categories: Meteorological, agricultural, hydrological, ecological, and socioeconomic drought. Results show that drought duration and magnitude have increased significantly, consistent with trends found in other Pacific Islands. We found that most droughts were associated with El Niño events, and the two worst droughts of the past century were multi-year events occurring in 1998–2002 and 2007–2014. The former event was most severe on the islands of O’ahu and Kaua’i while the latter event was most severe on Hawaiʻi Island. Within islands, we found different spatial patterns depending on leeward versus windward contrasts. Droughts have resulted in over $80 million in agricultural relief since 1996 and have increased wildfire risk, especially during El Niño years. In addition to providing the historical context needed to better understand future drought projections and to develop effective policies and management strategies to protect natural, cultural, hydrological, and agricultural resources, this work provides a framework for conducting drought analyses in other tropical island systems, especially those with a complex topography and strong climatic gradients.
... For example, since 1990, it has been practiced in certain Mediterranean settings of Greece (Dimitrakopoulos and Bemmerzouk 2003). The KBDI is one of the pointers that are used for tracking fire potential in Hawaii, for categorizing fire-season intensity by the Florida Division of Forestry and by the fire managers in Texas for monitoring the fire possibility (Dolling et al. 2009). ...
The Canadian Forest Fire Danger Rating System (CFFDRS) and the National Forest Fire Danger Rating System (NFFDRS) were exercised under the Mediterranean forest type conditions of Crete Island, Greece in 2008–2009. The CFFDRS shows a high association between the assessed values of the duff moisture content on one hand and the Fine Fuel Moisture Code and the Duff Moisture Code on the other hand. During the designated fire seasons, there was an insignificant association between the Fire Weather Index and the wild forest fires which are contrary associated with wildfire occurrences. Meanwhile, the NFFDRS showed monitoring capabilities but with the insufficient prediction of the daily fire danger in the Mediterranean forests. During the tested forest fire seasons, there was an unstable association between the burnt area and the fire occurrences. Consequently, there was no significant correlation between the CFFDRS and the litter soil content. Although, CFFDRS has a higher prediction accuracy of moisture content of some shallow roots annual plants within the studied area. The findings of the current research emphasized that there is no single system that is adequate enough for both soil moisture content and the annuals moisture content simultaneously.
... Drought provides favorable conditions for forest fires 12 as lack of soil moisture is one among the major drivers influencing the flammability of forests 13 . KBDI is one of the significant indicators that fire managers use for assessing the fire risk potential in their areas 14 . There are many studies that have attempted to relate KBDI with forest fire activity. ...
Limited fore-knowledge of the impending ignition potential is one of the main causes of not-so-effective forest-fire management in India. The present study is an approach to link forest fire trends and the Keetch–Byram Drought Index (KBDI) for assessing forest fire forewarning. Fire trends were analyzed based on forest fire incidents detected by MODIS remotely-sensed data in the Shivalik forest tracts of Uttarakhand State of India over a period of 16 years to identify the vulnerable window of most-prone weeks. The study further uses KBDI to calculate the drought build-up in an area based on which the severity of impending forest fires can be predicted. This is one-of the first attempts for the inclusion of KBDI in understanding forest fire regime in Indian conditions. Based on the weekly-trends obtained from forest fire points during 2001-2016 affirm the most vulnerable time period for the occurrence of forest fire in the study region is from week 14 to week 22. The performance of KBDI proved to be a valid parameter in forecasting the severity of forest fire as its pattern over three years of study period (2014-2016) showed the same dynamics. The minimum value of KBDI i.e. the ‘dip’ value is significant for its use as a predictor to the severity of the fire season in the ensuing summer a full 10 weeks in advance. The findings of the present study pave the path for identifying the high-risk areas and severity of possible fires in the following fire season by correlating remote sensing and GIS techniques with Fire trends, peak period and Keetch Byram Drought Index. This study has a potential for adoption in countries like India for modern forest fire preparedness and management in a cost-effective manner.
... Moreover, it was employed to study wildfire occurrence in the upper mid-west of United States. (Lorimer and Gough 1988), Mediterranean regions (Ganatsas et al. 2011;Garcia-Prats et al. 2015), Hawaii (Dolling et al. 2009), Malaysia (Ainuddin and Ampun 2008), Lebanon (Bayissa et al. 2018) and to assess the impact of climate change on global wildfire potentials (Liu et al. 2010). ...
Climate change influences spreading and occurrence of forest fire. Forest fire modeling is one of the most important tasks to fight forest fires. Climate data of current (1980–2010) was projected to near (2010–2039), mid (2040–2069) and end-term (2070–2099) using Representative Concentration Pathway (RCP4.5 and 8.5) of an ensemble of twenty General Circulation Models using R-software. Current and projected climate data were used to determine the impact of climate change on current and future forest fire using Keetch-Byram Drought Index. Current and future forest fire-vulnerable areas were mapped and weighed using Inverse Distance Weighting. The result indicates that, while no forest fire occurrence in the current, there might be a high forest fire risk in near-term. It might be become very high in mid and end-term. The size of forest fire-vulnerable areas might be increased to 12.85, 18.8, 17.1 and 46.26% in Mid-RCP4.5, Mid-RCP8.5, End-RCP4.5 and End-term-RCP8.5 respectively. Fire may occurred in winter and spring seasons. The risk might be move to higher elevation of the forest. This directs increase of forest fire occurrence and spread due to climate change. The study recommends that forest fire management should be applied before fire happened to sustain the forest and its products.
... For example, since 1990, it has been practiced in certain Mediterranean settings of Greece (Dimitrakopoulos and Bemmerzouk 2003). The KBDI is one of the pointers that are used for tracking fire potential in Hawaii, for categorizing fire-season intensity by the Florida Division of Forestry and by the fire managers in Texas for monitoring the fire possibility (Dolling et al. 2009). ...
The Fire Weather Index (FWI) module of the Canadian Forest Fire Danger Rating System (CFFDRS) was tested under the Mediterranean- type conditions of Crete (Greece) for the two fire seasons 2008-2009. High correlations were found between the Fine Fuel Moisture Code (FFMC) and the Duff Moisture Code (DMC. The Drought Code (DC) was poorly correlated with the soil moisture content. No significant correlation was found between the area burned by wildfires and any component of the FWI system during the studied period, unlike fire occurrence with which most of the components were highly correlated. Meanwhile, the Keetch-Byram Drought Index (KBDI) of the American Forest Fire Danger Rating System (NFFDRS) was also
evaluated under the same conditions. It provided a useful means of monitoring general wetting and drying cycles, but is inadequate for indicating daily fire danger throughout the fire season in our region. Weak correlations between the KBDI- the fire occurrence and the area burned were found for the two fire seasons studied-2008-2009. Correlations between the KBDI and litter, duff and soil did not give statistically sound results. On the contrary, the KBDI seemed to predict with high accuracy the moisture
content of three annual plants.
... A near real time (NRT) mapping of KBDI has been developed and used operationally in the south-eastern United States [Johnson and Forthum, 2001]. KBDI has also been employed to study wildfire occurrence in the upper mid-western U. S. [Lorimer and Gough, 1988], Mediterranean regions [Ganatsas et al., 2011;Garcia-Prats et al., 2015], Hawaii [Dolling et al., 2009], Malaysia [Ainuddin and Ampun, 2008], South Africa [Verbesselt et al., 2006] and Lebanon [Mitri et al., 2015]. KBDI has also been used to assess changes to global wildfire potential due to climate change . ...
The McArthur Forest Fire Danger Index used in Australia for operational fire warnings has a component representing fuel availability called the Drought Factor (DF). The DF is partly based on soil moisture deficit, calculated as either the Keetch-Byram Drought Index (KBDI) or Mount's Soil Dryness Index (MSDI). The KBDI and MSDI are simplified water balance models driven by observation based daily rainfall and temperature. In this work, gridded KBDI and MSDI analyses are computed at a horizontal resolution of 5 km and are verified against in-situ soil moisture observations. Also verified is another simple model called the Antecedent Precipitation Index (API). Soil moisture analyses from the Australian Community Climate and Earth System Simulator (ACCESS) global Numerical Weather Prediction (NWP) system as well as remotely sensed soil wetness retrievals from the Advanced Scatterometer (ASCAT) are also verified. The verification shows that the NWP soil wetness analyses have greater skill and smaller biases than the KBDI, MSDI and API analyses. This is despite the NWP system having a coarse horizontal resolution and not using observed precipitation. The average temporal correlations (root mean square difference) between cosmic ray soil moisture monitoring facility observations and modeled or remotely sensed soil wetness are 0.82 (0.15 ±0.02), 0.66 (0.33 ±0.07), 0.77 (0.20 ±0.03), 0.74 (0.22 ±0.03) and 0.83 (0.18 ±0.04) for NWP, KBDI, MSDI, API and ASCAT. The results from this study suggests that analyses of soil moisture can be greatly improved by using physically based land surface models, remote sensing measurements and data assimilation.
... Many efforts can be found in the literature on assessing the behavior of KBDI in different regions and climates, and modified versions adapted to local meteorological conditions have been widely proposed. Dolling et al. (2005Dolling et al. ( , 2009,) analyzed the natural variability of the index in the Hawaiian Islands conditions, paying especial attention to El Niño conditions. Following this approach, Brolley et al. (2007) studied the forecast probabilities of exceeding KBDI thresholds and the El Niño Southern oscillation (ENSO) impact using a weather generator. ...
The present work aims to take a closer look at the behavior of two releases of the Keetch–Byram droughtindex (KBDI) under different forest management strategies in Mediterranean conditions. Since theseversions of the index were demonstrated to be insensitive to the changes in water balance caused bydifferent thinning treatments, a new KBDI-based index sensitive to silviculture operations was developed.This new approach enabled us to simulate the benefits achieved from a thinning operation in terms offorest fire risk reduction. Abatements of 22.5% and 26.4% in KBDI were obtained for the 2009 and 2010high-risk forest fire periods, respectively, due to thinning. The reductions observed in the short-term didnot disappear in a long term. A plot thinned 10 years ago showed KBDI reductions of 12.5% and 6.7% withrespect to a non-managed plot (control treatment) in the same period. Finally, in order to make possibleapplication of the new index to other stands, coefficients of the index were based on well-known andeasy to get tree-related and physiological variables.
... Kondisi tersebut menyebabkan nilai DI meningkat mencapai intensitas maksimum pada bulan Oktober 2009. Perilaku indeks kekeringan tersebut mirip dengan perilaku indeks kekeringan KBDI yang terlalu sensitif terhadap ketiadaan hujan dalam jangka tertentu (Dolling et al. 2009). Jika dalam beberapa hari berturutan tidak ada hujan maka nilai indeks KBDI akan meningkat tajam. ...
Forest fire research is very important for tropical regions as the current available models on forest fire predictions and control were developed based on studies conducted in dry sub-tropical forest areas. The use of dryness index (DI) based on actual soil water content for assessing fire danger in wetland ecosystem was proposed in this paper. The study site was located in South Sumatera, Indonesia and study was conducted from April 1 st 2009 to March 15 th 2011. Fire danger was categorized into 4 levels; low, medium, dry, and extreme with its margin level was determined based on soil water retention curve analysis. All DI categories occurred in 2009, however only 2 categories (low and medium) were observed in 2010 and 2011. DI reached its maximum intensity in September 2009 with an onset rate of 1.4 per day based on analysis of time intensity curve. Information of onset rate is importance for forest fire management such as for estimating when the extreme category would be reached. Therefore anticipation and prevention efforts might be prepared prior to reaching certain danger level. Information on DI might be useful for water management planning in forest plantation areas as many of them are located in wetland ecosystem.
Keywords: dryness index, soil water content, wetland, onset rate, danger level
... For the entire field season, data on relative humidity, precipitation, temperature, and Keetch-Byram Drought Index, which estimates the amount of soil moisture by tracking daily maximum temperatures and rainfall (Dolling 2009), were obtained from the Georgia Automated Environmental Monitoring Network weather station on Ichauway property (listed as the Newton station at www.georgiaweather.net). Average temperature and relative humidity were calculated for the following time periods preceding each mosquito sampling date: 1 d, 1 wk, and 2 wk. ...
Understanding the ecology of mosquitoes is important for implementing control measures and explaining mosquito-borne disease prevalence. I compared mosquito population dynamics to selected weather variables and land use/ cover in a longleaf pine dominated landscape on the Gulf Coastal Plain of Georgia. Important factors for determining mosquito presence/ absence were precipitation, temperature, humidity, and drought index. Aedes albopictus and Culex spp. mosquitoes were associated with sites that had the most anthropogenic influence, while Coquillettidia perturbans and Psorophora ferox were associated with natural land cover such as wetlands and forested land. Arbovirus testing yielded one isolation of West Nile virus and three isolations of Potosi virus. This low arbovirus prevalence is likely due to the diversity of the wildlife in the area or factors related to the bird community, which typically serves as a reservoir for arboviruses. Examination of mosquito host-feeding patterns showed the mosquitoes collected predominantly fed on white-tailed deer.
