Analysis of Areas at Risk of Fire in Khuan Kreng Peat Swamp Forest in South Thailand

Main Article Content

Uraiwun Wanthong
Panjit Musik
Somporn Ruang-on
Manit Pollar
Rattana Phetkhong
Phitchan Sricharoen
Nunticha Limchoowong

Abstract

Khuan Kreng Peat Swamp Forest is Thailand's second-largest peat swamp forest. It serves as the primary source of income for villagers in this area. In this study, we 1) created three-dimensional (3D) images with Mathematica using Digital Elevation Model (DEM), 2) analyzed the displacement of wildfire risk of this research with Google Earth Pro with the wildfire data of Thale Noi Forest Fire Control Station from 2010 to 2022, and 3) analyzed the duration of forest fire risk to monitor and open platform field trips with villagers. We found that the forest fires in the Khuan Kreng Peat Swamp Forest had an average displacement of 93.88 ± 6.61m from the road line and an average displacement of 92.28 ± 7.33 m from the canal line, with an area of 339.158 km2 under special surveillance. The forest fire risk area was dense in the UTM range of 617000 - 629000 E and 870000 - 890000 N. The cases of wildfire peaked between May and August annually. In the Kreng sub-district, the topography of a lowland alternating with Phangan (low hill) is covered with Krajood (Lepironia articulata (Retz.) Domin) and Samed (Melaleuca quinquenervia (Cav.) S.T. Blake). The fire-prone areas are located near the roaming path around the Krajood forest. The best method to prevent forest fires is to maintain water in the Khuan Kreng Peat Swamp Forest from drying up. Avoid deepening the main canal around the swamp area and provide oil palm plantation limits, and sustainable land use management.  In addition, awareness should be raised about the loss incurred from forest fires and a network should be created to monitor forest fires for villagers in risky areas and long-term monitoring.

Article Details

Section
Research Article
Author Biographies

Uraiwun Wanthong, Nakhon Si Thammarat Rajabhat University

Program in Creative Innovation in Science and Technology, Faculty of Science and Technology

Panjit Musik, Walailak University

Center of Excellence for Ecoinformatics, School of Science

Somporn Ruang-on, Nakhon Si Thammarat Rajabhat University

Program in Creative Innovation in Science and Technology, Faculty of Science and Technology

Manit Pollar

Program in Math, Faculty of Science and Technology, Nakhon Si Thammarat Rajabhat University

Rattana Phetkhong, Thale Noi Forrest Fire Control station Nakhon Si Thammarat Village No.4

 Nakhon Si Thammarat 

Phitchan Sricharoen, Bangkokthonburi University

Department of Chemistry, Faculty of Medicine

Nunticha Limchoowong, Bangkokthonburi University

Department of Premedical Science, Faculty of Medicine

References

Forest Fire Control and Operation Division Office of Conservation Area 5 (Nakhon Si Thammarat), Department of National Parks, Wildlife and Plant Conservation (2019).

Komolkongyook, S. (2018). Characteristics of fuel in Kuan Kreng Swamp Forest. In the area of Village No. 6, Ban Khuan Rap, Kreng Sub-district, Cha Uat District, Nakhon Si Thammarat Province (Research report), Nakhon Si Thammarat: Office of the Suppression and Prevention. and control forest fires Department of National Parks, Wildlife and Plant Conservation.

Ying, L., Han, J., Du, Y., & Shen, Z. (2018). Forest fire characteristics in China: Spatial patterns and determinants with thresholds. Forest ecology and management, 424, 345–354. https://doi.org/10.1016/j.foreco.2018.05.020

Abbas, A., Waseem, M., Ahmad, R., Khan, K. A., Zhao, C., & Zhu, J. (2022). Sensitivity analysis of greenhouse gas emissions at farm level: Case study of grain and cash crops. Environmental Science and Pollution Research, 29(54), 82559-82573. https://doi.org/10.1007/s11356-022-21560-9

Elahi, E., Khalid, Z., Tauni, M. Z., Zhang, H., & Lirong, X. (2022). Extreme weather events risk to crop-production and the adaptation of innovative management strategies to mitigate the risk: A retrospective survey of rural Punjab, Pakistan. Technovation, 117, 102255. https://doi.org/10.1016/j.technovation.2021.102255

Elahi, E., Khalid, Z., & Zhang, Z. (2022). Understanding farmers’ intention and willingness to install renewable energy technology: A solution to reduce the environmental emissions of agriculture. Applied Energy, 309, 118459. https://doi.org/10.1016/j.apenergy.2021.118459

Oris, F., Asselin, H., Ali, A. A., Finsinger, W., & Bergeron, Y. (2014). Effect of increased fire activity on global warming in the boreal forest. Environmental Reviews, 22(3), 206-219. https://doi.org/10.1139/er-2013-0062

Hohner, A. K., Rhoades, C. C., Wilkerson, P., & Rosario-Ortiz, F. L. (2019). Wildfires alter forest watersheds and threaten drinking water quality. Accounts of Chemical Research, 52(5), 1234-1244. https://doi.org/10.1021/acs.accounts.8b00670

Paveglio, T. B., Brenkert-Smith, H., Hall, T., & Smith, A. M. (2015). Understanding social impact from wildfires: Advancing means for assessment. International Journal of Wildland Fire, 24(2), 212-224. https://doi.org/10.1071/WF14091

Herawati, H., & Santoso, H. (2011). Tropical forest susceptibility to and risk of fire under changing climate: A review of fire nature, policy and institutions in Indonesia. Forest Policy and Economics, 13(4), 227–233.

Department of National Parks, Wildlife and Plant Conservation. Available at: https://www.dnp.go.th/forestfire/web/frame/lesson7.html]. Accessed on 2 January 2020.

Office of Natural Resources and Environmental Policy and Planning. Khuan Kreng Swamp Forest, from http://wetland.onep.go.th/2551-17-Prukuankreng.html, accessed on 25-09-2020

OK Nation. Available at: https://tna.mcot.net/tna321772. Accessed on 25 July 2020.

Wolfram. 2013. USGSDEM (.dem). Available at:

http://reference.wolfram.com/language/ref/format/USGSDEM.html. 2013. Accessed on 7 August 2013.

Cirbus, J.; Podhoranyi, M. (2013). Cellular automata for the flow simulations on the earth

surface, optimization computation process, Applied Mathematics & Information Sciences, Vol 7, No.6: 2149–2158. https://dx.doi.org/10.12785/amis/070605

Barnes, R.; Lehman, C.; Mulla, D. (2016). Distributed parallel d8 up-slope area calculation in digital elevation models, Proceedings of the 5th International Conference on Parallel and Distributed Processing Techniques and Applications, 833–838. https://doi.org/10.48550/arXiv.1605.05773

Kelly, B. F. J.; Giambastiani, B. M. S. (2009). Functional Programming Algorithms for

Constructing 3D Geological Models, Proceeding of the 10th International Conference on GeoComputation, The University of New South Wales, Sydney

Dyckman, C. (2020). Planners’ presence in planning for water quality and availability, Transportation, Land Use, and Environmental Planning, Elsevier. https://doi.org/10.1016/B978-0-12-815167-9.00017-7Get rights and content

Kelly, B.; Giambastiani, B.; Andersen, M., McCallum, A.; Greve, A.; Acworth, I. (2010). Development of a 3D Geological Mapping and Database Interface to Support Interconnected Groundwater and Surface Water Management.

Google Earth Pro, [Online]. Available : https://developers.google.com/ maps/. [Accessed: November 16, 2021].

Parajuli, A., Gautam, A. P., Sharma, S. P., Bhujel, K. B., Sharma, G., Thapa, P. B., ... & Poudel, S. (2020). Forest fire risk mapping using GIS and remote sensing in two major landscapes of Nepal. Geomatics, Natural Hazards and Risk, 11(1), 2569–2586. https://doi.org/10.1080/19475705.2020.1853251

Princess Sirindhorn Peat Swamp Forest Research Center, Pikulthong Royal Development Study Project (Forest Section) (2002). Published Technical Paper, “Forest fire… Princess Sirindhorn Peat Swamp Forest., Nov. 2002.

Nuthammachot, N., & Stratoulias, D. (2021). Multi-criteria decision analysis for forest fire risk assessment by coupling AHP and GIS: Method and case study. Environment, Development and Sustainability, 1-16. https://doi.org/10.1007/s10668-021-01394-0

David Lee, T.Y. Chee and F. Parish (2003). Smart Partnership in Fire Prevention and Peat Forest Restoration: a Case Study, Proceeding of the 7th World Forestry Congress, Quebec City, Canada.

Kanabkaew, T., Rattanarat, J., & Petcharoen, S. (2014). Development of a GIS-based forest fire risk map: case of Kuan Kreng swamp forest, Southern Thailand.

Sun, Q., Miao, C., Hanel, M., Borthwick, A. G., Duan, Q., Ji, D., & Li, H. (2019). Global heat stress on health, wildfires, and agricultural crops under different levels of climate warming. Environment international, 128, 125-136.

Zhou, Q., Zhang, H., & Wu, Z. (2022). Effects of Forest Fire Prevention Policies on Probability and Drivers of Forest Fires in the Boreal Forests of China during Different Periods. Remote Sensing, 14(22), 5724. https://doi.org/10.3390/rs14225724

Khampeera, A., Yongsathitsak, T., Phuekmongkolyongchalermchai, P., & Kerdkurang, K.. (2021). Analysis of fire prone areas during drought in Khuan Kret peat swamps. Nakorn Si Thammarat province by using AHP analysis and geographic information system. Thai Journal of Science and Technology, 10(2).

Princess Sirindhorn Peat Swamp Forest Research Center, Pikulthong Royal Development Study Project (Forest Section) (2002). Published Technical Paper, “Forest fire… Princess Sirindhorn Peat Swamp Forest., Nov. 2002.

Mohammadi, F., Bavaghar, M. P., & Shabanian, N. (2014). Forest fire risk zone modeling using logistic regression and GIS: an Iranian case study. Small-scale Forestry, 13, 117–125. https://doi.org/10.1007/s11842-013-9244-4

Gigović, L., Jakovljević, G., Sekulović, D., & Regodić, M. (2018). GIS multi-criteria analysis for identifying and mapping forest fire hazard: Nevesinje, Bosnia and Herzegovina. Tehnički vjesnik, 25(3), 891–897. https://doi.org/10.17559/TV-20151230211722