Determination of soil moisture reduction rate on peatlands in South Sumatera due to the 2019 extreme dry season

Irfan, Muhammad; Koriyanti, E; Awaluddin,; Ariani, Menik; Sulaiman, Albertus; Iskandar, Iskhaq

doi:10.1088/1755-1315/713/1/012025

Cited by 2 publications

(3 citation statements)

References 15 publications

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“…The practice of Manusul, involving land clearing, sometimes triggers unintentional fires beyond firebreaks during dry seasons [9]. Prolonged periods of arid conditions heighten the vulnerability to ignition, with climate phenomena such as the El Niño Southern Oscillation and the Indian Ocean Dipole serving as pivotal influencers of fire incidence [10,11]. These sudden events alter peatland distributions, necessitating vigilant monitoring of peatland change patterns.…”

Section: Introductionmentioning

confidence: 99%

Unveiling the Past: Deep-Learning-Based Estimation of Historical Peatland Distribution

Cha,

Lee,

Choi

et al. 2024

Land

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Acknowledging the critical role of accurate peatland distribution estimation, this paper underscores the significance of understanding and mapping these ecosystems for effective environmental management. Highlighting the importance of precision in estimating peatland distribution, the research aims to contribute valuable insights into ecological monitoring and conservation efforts. Prior studies lack robust validation, and while recent advancements propose machine learning for peatland estimation, challenges persist. This paper focuses on the integration of deep learning into peatland detection, underscoring the urgency of safeguarding these global carbon reservoirs. Results from convolutional neural networks (CNNs) reveal a decrease in the classified peatland area from 8226 km2 in 1999 to 5156 km2 in 2019, signifying a 37.32% transition. Shifts in land cover types are evident, with an increase in estate plantation and a decrease in swamp shrub. Human activities, climate, and wildfires significantly influenced these changes over two decades. Fire incidents, totaling 47,860 from 2000 to 2019, demonstrate a substantial peatland loss rate, indicating a correlation between fires and peatland loss. In 2020, wildfire hotspots were predominantly associated with agricultural activities, highlighting subsequent land cover changes post-fire. The CNNs consistently achieve validation accuracy exceeding 93% for the years 1999, 2009, and 2019. Extending beyond academic realms, these discoveries establish the foundation for enhanced land-use planning, intensified conservation initiatives, and effective ecosystem management—a necessity for ensuring sustainable environmental practices in Indonesian peatlands.

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Section: Introductionmentioning

confidence: 99%

Unveiling the Past: Deep-Learning-Based Estimation of Historical Peatland Distribution

Cha,

Lee,

Choi

et al. 2024

Land

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“…The most felt impact was the massive peatland fires that occurred in the Kalimantan Islands in 2019. The largest peatland fires in 2019 in Indonesia were in Central Kalimantan, which was 134,227 hectares, and West Kalimantan province covered 127,462 hectares [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…SESAME stations have been installed in several areas in Indonesia. The Kalimantan Islands have been installed in the Provinces of West Kalimantan and Central Kalimantan Provinces [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Rainfall and Temperature Dynamics in Peatlands During 2018-2021 Climate Change

Irfan¹

2022

GEOMATE

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In 2018-2021, several natural phenomena occurred that caused climate change in Indonesia. This climate change is estimated to have affected the dynamics of rainfall and temperature in Indonesia. This study aims to analyze the incidence of climate change, rainfall dynamics, and temperature dynamics, and find the correlation between rainfall versus temperature during the 2018-2021 dry season. The location of this research is on peatlands in Central Kalimantan and West Kalimantan where both locations have installed automatic measurement stations for rainfall and temperature. Peatlands were chosen because the dynamics of rainfall and temperature greatly affect the condition of peatlands that are prone to fires and floods. The results of this study indicate that very minimal rainfall occurs in the dry season in 2019, especially from July to September 2019. Rainfall in the 2019 dry season is much lower when compared to the dry season in 2018, 2020, and 2021. This happens because in 2019 two natural phenomena occurred simultaneously, namely: moderate IOD+ and weak El Niño. These two phenomena reinforce each other in reducing rainfall in Indonesia. The temperature during the dry season for 4 years did not show a significant difference, but in general, the temperature in Central Kalimantan was lower than the temperature in West Kalimantan. It was also found that there was a trend in the relationship between rainfall and temperature where the higher the rainfall, the lower the temperature. Based on the results of the statistical method of linear regression and t-test, it has been found that the correlation between rainfall and temperature is significant.

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Determination of soil moisture reduction rate on peatlands in South Sumatera due to the 2019 extreme dry season

Cited by 2 publications

References 15 publications

Unveiling the Past: Deep-Learning-Based Estimation of Historical Peatland Distribution

Unveiling the Past: Deep-Learning-Based Estimation of Historical Peatland Distribution

Analysis of Rainfall and Temperature Dynamics in Peatlands During 2018-2021 Climate Change

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