Temporal Analysis of the Keetch-Byram Drought Index in Malaysia: Implications for Forest Fire Management

Ainuddin, N. A.; Ampun, J.

doi:10.3923/jas.2008.3991.3994

Cited by 19 publications

(13 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A near real time (NRT) mapping of KBDI has been developed and used operationally in the south‐eastern United States [ Johnson and Forthum , ]. KBDI has also been employed to study wildfire occurrence in the upper mid‐western U. S. [ Lorimer and Gough , ], Mediterranean regions [ Ganatsas et al ., ; Garcia‐Prats et al ., ], Hawaii [ Dolling et al ., ], Malaysia [ Ainuddin and Ampun , ], South Africa [ Verbesselt et al ., ] and Lebanon [ Mitri et al ., ]. KBDI has also been used to assess changes to global wildfire potential due to climate change [ Liu et al ., ].…”

Section: Methodsmentioning

confidence: 99%

Comparison of soil wetness from multiple models over Australia with observations

Vinodkumar

Dharssi

Bally

et al. 2017

Water Resources Research

View full text Add to dashboard Cite

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 60.02), 0.66 (0.33 60.07), 0.77 (0.20 60.03), 0.74 (0.22 60.03) and 0.83 (0.18 60.04) 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.KBDI and MSDI are simple water balance models that do not take into account the majority of physical factors which affect soil moisture dynamics such as soil type, vegetation type, terrain or aspect. They oversimplify the evapotranspiration and runoff processes, which are critical in calculating accurate soil moisture states, potentially leading to large errors. Recent progresses in the remote sensing of soil moisture, data assimilation techniques and physically based land surface models has led to the development of new soil Key Points:Simple water balance models have less skill than weather prediction system soil moisture analyses Weather prediction system soil moisture analyses are unbiased and capture the seasonal variations The remotely sensed ASCAT soil wetness product is of good qualitySupporting Information: Supporting Information S1

show abstract

Section: Methodsmentioning

confidence: 99%

Comparison of soil wetness from multiple models over Australia with observations

Vinodkumar

Dharssi

Bally

et al. 2017

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…Most studies in Southeast Asia use four fire danger classes (e.g. Buchholz and Weidemann, 2000;Murdiyarso et al, 2002;Ainuddin and Ampun, 2008). The daily outcome of all three drought indices, i.e.…”

Section: Model Setupmentioning

confidence: 98%

“…However, currently no model structure is available that integrates the higher annual rainfall and the water table into the drought index for use in tropical wetland ecosystem. We anticipate that integrating these aspects in the KBDI will improve applicability in Southeast Asia and progress on the studies by Murdiyarso et al (2002), Buchholz and Weidemann (2000) and Ainuddin and Ampun (2008). Therefore, the objective of this paper is: (i) to modify the fire drought index KBDI for climate, soil, and hydrological conditions representative for wetland areas in humid tropical climates, and (ii) to analyze the influence of the water table depth on the dynamics of the KBDI.…”

Section: Introductionmentioning

confidence: 96%

“…daily maximum air temperature and rainfall at a nearby standard meteorological station). Several studies have applied the KBDI in other areas than Florida State, such as Northern Eurasia (Groisman et al, 2007), Hawaii (Dolling et al, 2005), Australia (Boer et al, 2009;Finkele et al, 2006;Caccamo et al, 2012), Russia (Malevsky-Malevich et al, 2008), Mediterranean regions (Petros et al, 2011), in Southeast Asia, such as Indonesia (Murdiyarso et al, 2002;Buchholz and Weidemann, 2000) and Malaysia (Ainuddin and Ampun, 2008). Heim (2002) and Petros et al (2011) indicate that the KBDI is the most widely used and accepted index for forest fire monitoring and prediction.…”

Section: Introductionmentioning

confidence: 97%

See 1 more Smart Citation

Modification of a fire drought index for tropical wetland ecosystems by including water table depth

Taufik

Setiawan

Lanen

2015

Agricultural and Forest Meteorology

View full text Add to dashboard Cite

a b s t r a c tIn this paper, we discuss how an existing empirical drought index, i.e. the Keetch-Byram Drought Index (KBDI) that is commonly used for assessing forest fire danger, has been adjusted and modified for improved use in tropical wetland ecosystems. The improvement included: (i) adjustment of the drought factor to the local climate, and (ii) addition of the water table depth as a dynamic factor to control the drought index. We distinguished three different indices, the original Keetch-Byram Drought Index, the adjusted KBDI (KBDI adj ) that represents the original drought index, but including local climate information, and the modified KBDI (mKBDI) that considers both local climate information, and soil and hydrological characteristics. The mKBDI was developed and tested in a wetland forest of South Sumatra (Indonesia) from April 2009 to March 2011. During this period, hydrometeorological data were monitored and used to calculate the KBDI, KBDI adj , and mKBDI. First, mKBDI was calibrated using observed soil moisture that was converted to an observed drought index (DI obs ). The results indicate that performance of the mKBDI is encouraging based on the following: (i) its pattern followed the dynamics of DI obs , (ii) prediction of frequency of fire danger classes, and (iii) statistically criteria. The mKBDI clearly outperformed KBDI and KBDI adj . Furthermore, we found a critical water table depth when it reaches maximum fire danger (0.85 m for the wetland forest of South Sumatra) below which danger does not increase anymore. The mKBDI could be more widely applied, if pedotransfer functions are developed that link easily obtainable soil properties to the parameters of the water table factor. Our findings encourage land use planners, water managers and stakeholders (e.g. forest estate owners) to integrate local climate information, and soil and hydrological characteristics into the Keetch-Byram Drought Index to better predict fire danger, particularly in tropical wetland ecosystems.

show abstract

“…The risk of forest fire occurrences increases during the low rainfall season occurring during January to March and June to September (Ainuddin and Ampun, 2008). Land opening with burning method done by small scale farmers also causes fire spread to the adjacent forestland.…”

Section: Introductionmentioning

confidence: 99%

Leaves Calorific Values of Selected Species in Burnt Tropical Peat Swamp Forest in Selangor, Malaysia

Ulok¹,

Nuruddin²,

Go³

et al. 2016

American Journal of Environmental Sciences

View full text Add to dashboard Cite

Forest fire in Malaysia's peat swamp forest is a major concern since it is contributing to the country's haze episode. Forest fire in peat areas is difficult to be extinguished and may occur for days. Understanding fuel characteristics is the key to develop effective fuel management in peat swamp forest. The objectives of this study were to evaluate the common species coverage and calorific value of the common plants species in the burnt peat swamp forest. The study was conducted in the rehabilitated areas of Raja Musa Forest Reserved, Selangor, Malaysia. 9 plots were established along canal 6 in Compartment 100 of the Raja Musa Forest Reserved. Plants were surveyed in the 9 plots and based on the survey, 8 species (Imperata cylindrica, Macaranga pruinosa, Nephrolepis biserrata, Melastoma malabathricum, Lygodium flexuosum, Uncaria tomentosa, Scleria sumatrensis and Melicope latifolia) most higest coverage found in that area. Scleria sumatrensis had the highest coverage of 40% followed by Melastoma malabathricum of coverage of 21%. The data suggested that the 8 species covered most of the study area and have the potential to be forest fuel. Uncaria Tomentosa had the highest calorific value with 4832.8 cal/g while Nephrolepis biserrata had the lowest value of 3825.2 cal/g. The findings concluded that the Sceleria sumatrensis had the highest coverage and calorific values of the selected plants vary with species. These information provide insight on the species common in burnt tropical peat swamp forest and are helpful in formulating forest fire control programme.

show abstract

Temporal Analysis of the Keetch-Byram Drought Index in Malaysia: Implications for Forest Fire Management

Cited by 19 publications

References 12 publications

Comparison of soil wetness from multiple models over Australia with observations

Comparison of soil wetness from multiple models over Australia with observations

Modification of a fire drought index for tropical wetland ecosystems by including water table depth

Leaves Calorific Values of Selected Species in Burnt Tropical Peat Swamp Forest in Selangor, Malaysia

Contact Info

Product

Resources

About