Document Type : SPECIAL ISSUE


1 Limnology and Water Resources Research Center, Indonesian Agency for National Research and Innovation, Indonesia

2 Horticulture and Estate Crops Research Center, Indonesian Agency for National Research and Innovation, Indonesia

3 Research Center for Food Crops, Indonesian Agency for National Research and Innovation, Indonesia


BACKGROUND AND OBJECTIVES: To minimize the potential risk of land fires, climate monitoring and hydrology characterization are crucial factors in managing peatlands. Therefore, this study aimed to investigate the relation between climate variability and water dynamics to develop a peatland fire early warning model.
METHODS: This research was conducted in an oil palm plantation located in Pangkalan Pisang village, Koto Gasib subdistrict, Siak district, Riau province, Indonesia. Herein, the observed parameters were climate and dynamics of ground water level and soil moisture, which were monitored using data loggers installed on predefined representative locations and distributed over three blocks of 30 hectares in the palm oil plantation research site. Thus, the peat fire early warning model was developed based on the relation between peat water dynamics and the recorded history of peat fire events.
FINDINGS: Herein, a recession curve analysis of soil moisture and ground water level revealed the relation between soil water dynamics and local climate. Consequently, this study found that soil moisture was the suitable parameter to estimate peat fire risk owing to its predictability. Furthermore, this study has identified a threshold of low and high peat fire risk in the area with less than 104 percent and 129 percent dry weight of soil moisture content, respectively. Afterward, this soil moisture criterion was transferred into precipitation value to develop a peat fire early warning model for estimating the days left before a high peat fire risk status was attained based on the latest daily rainfall rates.
CONCLUSION: This study has developed a simple peat fire early warning model using daily precipitation data. The accurate estimation of countdown days to peat fire susceptibility status in an area would enhance fire mitigation strategies in peatlands.

Graphical Abstract

Modeling of peatland fire risk early warning based on water dynamics


  • In comparison to ground water level dynamic, soil moisture was proven to be more suitable to estimate peatland fire risks due to its higher predictability;
  • Analysis on the recorded peat water dynamics data showed a significant correlation between the previous day of antecedent precipitation index and soil moisture data;
  • An early warning model to estimate the time to anticipate risks of peatland fires based on the previous day rainfall intensity has been successfully developed.


Main Subjects


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