Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal

Chelesile Sibanda, Y.A. Hussin, M.C. Weir, Hammad Gilani

Research output: Contribution to conferencePaperAcademicpeer-review

Abstract

Forest fires have become intense and more frequent in the last few decades all over the world. The profound impacts of forest fires have on atmospheric chemistry, biogeochemical cycling and ecosystem structure have led to the need to understand their behavior. Forest conditions, topography and weather greatly influence forest fire behavior and thus determine fire severity and consequently carbon emission. The estimation of carbon emission from forest fires is crucial for improving our understanding of the carbon cycle dynamics in order to develop strategies to curb the global warming - climate change problem. Previous studies have shown that modeling forest fire behavior can accurately give a good estimate of carbon emissions. The concentration of forest fire emissions varies spatially from one fire event to another as these emissions are a function of fire intensity, amount of biomass burned, and prevailing weather conditions. Therefore, this study is aiming at modeling forest fire behavior, and developing a method to estimate carbon emission in the rugged terrain of Nepal using 3 fire events that occurred in April 2008. A state of the art fire behavior model, FARSITE was used to simulate fire behavior in a spatially and temporally explicit manner taking into account the fuel, topography and prevailing weather in the Ludikhola watershed situated in the Gorkha district of Nepal. A WindNinja model was used to derive local winds influenced by vegetation and topography in the area. A combined approach involving a FARSITE model output parameter i.e. fire line intensity and a carbon emission estimation model developed in this research. The model was used to estimate fire induced carbon emission. The simulations were validated with the real mapped fire scar. The simulations using both uniform and spatially varying wind data, estimated the size of the real burned area with accuracies ranging between 78% and 96% for the three fire events were analysed.

Original languageEnglish
Pages881-886
Number of pages6
Publication statusPublished - 1 Dec 2011
Event32nd Asian Conference on Remote Sensing, ACRS 2011: Sensing for Green Asia - Taipei, Taiwan, Province of China
Duration: 3 Oct 20117 Oct 2011
Conference number: 32

Conference

Conference32nd Asian Conference on Remote Sensing, ACRS 2011
Abbreviated titleACRS
CountryTaiwan, Province of China
CityTaipei
Period3/10/117/10/11

Fingerprint

Watersheds
Fires
Carbon
Topography
Atmospheric chemistry
Curbs
Global warming
Climate change
Ecosystems

Keywords

  • Above ground biomass
  • Carbon emission
  • FARSITE
  • Forest fire behavior
  • Wind Ninja

Cite this

Sibanda, C., Hussin, Y. A., Weir, M. C., & Gilani, H. (2011). Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal. 881-886. Paper presented at 32nd Asian Conference on Remote Sensing, ACRS 2011, Taipei, Taiwan, Province of China.
Sibanda, Chelesile ; Hussin, Y.A. ; Weir, M.C. ; Gilani, Hammad. / Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal. Paper presented at 32nd Asian Conference on Remote Sensing, ACRS 2011, Taipei, Taiwan, Province of China.6 p.
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Sibanda, C, Hussin, YA, Weir, MC & Gilani, H 2011, 'Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal' Paper presented at 32nd Asian Conference on Remote Sensing, ACRS 2011, Taipei, Taiwan, Province of China, 3/10/11 - 7/10/11, pp. 881-886.

Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal. / Sibanda, Chelesile; Hussin, Y.A.; Weir, M.C.; Gilani, Hammad.

2011. 881-886 Paper presented at 32nd Asian Conference on Remote Sensing, ACRS 2011, Taipei, Taiwan, Province of China.

Research output: Contribution to conferencePaperAcademicpeer-review

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T1 - Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal

AU - Sibanda, Chelesile

AU - Hussin, Y.A.

AU - Weir, M.C.

AU - Gilani, Hammad

PY - 2011/12/1

Y1 - 2011/12/1

N2 - Forest fires have become intense and more frequent in the last few decades all over the world. The profound impacts of forest fires have on atmospheric chemistry, biogeochemical cycling and ecosystem structure have led to the need to understand their behavior. Forest conditions, topography and weather greatly influence forest fire behavior and thus determine fire severity and consequently carbon emission. The estimation of carbon emission from forest fires is crucial for improving our understanding of the carbon cycle dynamics in order to develop strategies to curb the global warming - climate change problem. Previous studies have shown that modeling forest fire behavior can accurately give a good estimate of carbon emissions. The concentration of forest fire emissions varies spatially from one fire event to another as these emissions are a function of fire intensity, amount of biomass burned, and prevailing weather conditions. Therefore, this study is aiming at modeling forest fire behavior, and developing a method to estimate carbon emission in the rugged terrain of Nepal using 3 fire events that occurred in April 2008. A state of the art fire behavior model, FARSITE was used to simulate fire behavior in a spatially and temporally explicit manner taking into account the fuel, topography and prevailing weather in the Ludikhola watershed situated in the Gorkha district of Nepal. A WindNinja model was used to derive local winds influenced by vegetation and topography in the area. A combined approach involving a FARSITE model output parameter i.e. fire line intensity and a carbon emission estimation model developed in this research. The model was used to estimate fire induced carbon emission. The simulations were validated with the real mapped fire scar. The simulations using both uniform and spatially varying wind data, estimated the size of the real burned area with accuracies ranging between 78% and 96% for the three fire events were analysed.

AB - Forest fires have become intense and more frequent in the last few decades all over the world. The profound impacts of forest fires have on atmospheric chemistry, biogeochemical cycling and ecosystem structure have led to the need to understand their behavior. Forest conditions, topography and weather greatly influence forest fire behavior and thus determine fire severity and consequently carbon emission. The estimation of carbon emission from forest fires is crucial for improving our understanding of the carbon cycle dynamics in order to develop strategies to curb the global warming - climate change problem. Previous studies have shown that modeling forest fire behavior can accurately give a good estimate of carbon emissions. The concentration of forest fire emissions varies spatially from one fire event to another as these emissions are a function of fire intensity, amount of biomass burned, and prevailing weather conditions. Therefore, this study is aiming at modeling forest fire behavior, and developing a method to estimate carbon emission in the rugged terrain of Nepal using 3 fire events that occurred in April 2008. A state of the art fire behavior model, FARSITE was used to simulate fire behavior in a spatially and temporally explicit manner taking into account the fuel, topography and prevailing weather in the Ludikhola watershed situated in the Gorkha district of Nepal. A WindNinja model was used to derive local winds influenced by vegetation and topography in the area. A combined approach involving a FARSITE model output parameter i.e. fire line intensity and a carbon emission estimation model developed in this research. The model was used to estimate fire induced carbon emission. The simulations were validated with the real mapped fire scar. The simulations using both uniform and spatially varying wind data, estimated the size of the real burned area with accuracies ranging between 78% and 96% for the three fire events were analysed.

KW - Above ground biomass

KW - Carbon emission

KW - FARSITE

KW - Forest fire behavior

KW - Wind Ninja

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M3 - Paper

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ER -

Sibanda C, Hussin YA, Weir MC, Gilani H. Modelling forest fire behaviour and mapping carbon emission in the Ludikhola watershed, Gorkha district, Nepal. 2011. Paper presented at 32nd Asian Conference on Remote Sensing, ACRS 2011, Taipei, Taiwan, Province of China.