Prototype Framework for Agricultural Drought Monitoring in Northern Thailand Using Satellite-Based Evaporative Stress Index
DOI:
https://doi.org/10.54386/jam.v28i1.3309Keywords:
Evaporative Stress Index, Northern Thailand, Agricultural drought, Drought monitoring, Remote sensing, Satellite-based assessmentAbstract
Agricultural drought threatens crop production in Northern Thailand, where complex terrain and limited meteorological stations restrict effective ground-based monitoring. This study developed a prototype framework for agricultural drought monitoring using the satellite-based Evaporative Stress Index (ESI). Bias-corrected reference evapotranspiration (ETo) from TerraClimate was combined with satellite-derived actual evapotranspiration (ETa) from SSEBop to calculate 10-day ESI values during 2012–2023. A classification system based on consecutive ESI patterns was developed to generate action-oriented maps for emergency response. Temporal analysis revealed persistent agricultural drought from late 2021 through early 2022. Spatial analysis identified significant heterogeneity across the region, revealing localized stress areas that regional averages failed to detect. The consecutive-period classification prioritized areas under constant stress requiring emergency intervention over those experiencing only temporary fluctuations. Overall, the proposed prototype framework provides decision-support capabilities that can be integrated with exposure and resistance factors to guide resource allocation in regions with sparse ground-based monitoring infrastructure.
References
Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., & Hegewisch, K. C. (2018). TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015. Scientific Data, 5, 1–12. https://doi.org/10.1038/sdata.2017.191
Amazirh, A., Chehbouni, A., Bouras, E. H., Benkirane, M., Ait Hssaine, B., & Entekhabi, D. (2023). Drought cascade lag time estimation across Africa based on remote sensing of hydrological cycle components. Advances in Water Resources, 182, 104586. https://doi.org/10.1016/j.advwatres.2023.104586
Anderson, M. C., Norman, J. M., Mecikalski, J. R., Otkin, J. A., & Kustas, W. P. (2007). A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 2. Surface moisture climatology. Journal of Geophysical Research Atmospheres, 112, D11112. https://doi.org/10.1029/2006JD007507
ASEAN Specialised Meteorological Centre. (2022). ASMC Bulletin (Issue 10). https://www.mss-int.sg/docs/default-source/rcc_bulletin_doc/asmc-bulletin-issue-no-10-sep-2022.pdf
Fang, G. H., Yang, J., Chen, Y. N., & Zammit, C. (2015). Comparing bias correction methods in downscaling meteorological variables for a hydrologic impact study in an arid area in China. Hydrology and Earth System Sciences, 19(6), 2547–2559. https://doi.org/10.5194/hess-19-2547-2015
Ha, T. V., Uereyen, S., & Kuenzer, C. (2023). Agricultural drought conditions over mainland Southeast Asia: Spatiotemporal characteristics revealed from MODIS-based vegetation time-series. International Journal of Applied Earth Observation and Geoinformation, 121, 103378. https://doi.org/10.1016/j.jag.2023.103378
Jeefoo, P. (2023). Thai Eastern Economic Corridor Drought Monitoring using Terra MODIS Satellite-based Data. Geographia Technica, 18(2), 123–131. https://doi.org/10.21163/GT
Jeong, H., Park, H. S., Chowdary, J. S., & Xie, S. P. (2023). Triple-Dip La Niña Contributes to Pakistan Flooding and Southern China Drought in Summer 2022. Bulletin of the American Meteorological Society, 104(9), E1570–E1586. https://doi.org/10.1175/BAMS-D-23-0002.1
Mergia, G. (2024). Spatiotemporal analysis of meteorological drought in El Niño years over Oromia region, Ethiopia. Journal of Agrometeorology, 26(1), 109–114. https://doi.org/10.54386/jam.v26i1.2329
Northern Meteorological Center. (2022). Chance of dry spells in Lampang Province using data from 2011 - 2020 (Technical Document No. 551.577.3-01-2022).
Nurdiati, S., Sopaheluwakan, A., & Septiawan, P. (2022). Joint Pattern Analysis of Forest Fire and Drought Indicators in Southeast Asia Associated with ENSO and IOD. Atmosphere, 13, 1198. https://doi.org/10.3390/atmos13081198
Otkin, J. A., Anderson, M. C., Hain, C., Mladenova, I. E., Basara, J. B., & Svoboda, M. (2013). Examining rapid onset drought development using the thermal infrared-based evaporative stress index. Journal of Hydrometeorology, 14(4), 1057–1074. https://doi.org/10.1175/JHM-D-12-0144.1
Pei, W., Fu, Q., Liu, D., Li, T. xiao, Cheng, K., & Cui, S. (2018). Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China. Theoretical and Applied Climatology, 133, 151–164. https://doi.org/10.1007/s00704-017-2182-x
Senay, G. B., Bohms, S., Singh, R. K., Gowda, P. H., Velpuri, N. M., Alemu, H., & Verdin, J. P. (2013). Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach. Journal of the American Water Resources Association, 49(3), 577–591. https://doi.org/10.1111/jawr.12057
Sreeparvathy, V., Debdut, S., & Mishra, A. (2025). A Review of Advances in Flash Drought Research: Challenges and Future Directions. Earth’s Future, 13(8), e2025EF006603. https://doi.org/10.1029/2025EF006603
Trisurat, Y., Alkemade, R., & Verburg, P. H. (2010). Projecting Land-Use Change and Its Consequences for Biodiversity in Northern Thailand. Environmental Management, 45(3), 626–639. https://doi.org/10.1007/s00267-010-9438-x
Wang, Q., Zeng, J., Qi, J., Zhang, X., Zeng, Y., Shui, W., Xu, Z., Zhang, R., Wu, X., & Cong, J. (2021). A multi-scale daily SPEI dataset for drought characterization at observation stations over mainland China from 1961 to 2018. Earth System Science Data, 13(2), 331–341. https://doi.org/10.5194/essd-13-331-2021
Yang, X., Shao, X., Mao, X., Li, X., & Li, R. (2019). An analysis of drought evolution characteristics based on standardized precipitation index : a case study in Southwest Guizhou Autonomous Prefecture , China. Journal of Agrometeorology, 21(3), 327–335. https://doi.org/10.54386/jam.v21i3.255
Yoon, D., Nam, W., Lee, H., Hong, E., Feng, S., Wardlow, B. D., Tadesse, T., Svoboda, M. D., Hayes, M. J., & Kim, D. (2020). Agricultural Drought Assessment in East Asia Using Satellite-Based Indices. Remote Sensing, 12, 444. https://doi.org/10.3390/rs12030444
Zaki, M. K., & Noda, K. (2022). A Systematic Review of Drought Indices in Tropical Southeast Asia. Atmosphere, 13, 833. https://doi.org/10.3390/atmos13050833
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2026 NOPNAPA BOONPIN, PHATCHAREEYA WAIPHARA, CHUPHAN CHOMPUCHAN
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is a human-readable summary of (and not a substitute for) the license. Disclaimer.
You are free to:
Share — copy and redistribute the material in any medium or format
Adapt — remix, transform, and build upon the material
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
