A Spatiotemporal Analysis of Drought Conditions Framework in Vast Paddy Cultivation Areas of Thung Kula Ronghai, Thailand
บทความในวารสาร
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Pariwate Varnakovida, Nathapat Punturasan, Usa Humphries, Anisara Tibkaew and Sornkitja Boonprong
ผู้เผยแพร่: Elsevier
ปีที่เผยแพร่ (ค.ศ.): 2025
Volume number: 15
Issue number: 14
หน้าแรก: 1
หน้าสุดท้าย: 27
จำนวนหน้า: 27
นอก: 0167-8809
eISSN: 1873-2305
URL: https://www.mdpi.com/2077-0472/15/14/1503
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
This study presents an integrated spatiotemporal assessment of drought conditions in the Thung Kula Ronghai region of Northeastern Thailand from 2001 to 2023. Multiple satellite-derived drought indices, including SPI, SPEI, RDI, and AI, together with NDVI anomalies, were used to detect seasonal and long-term drought dynamics affecting rainfed Hom Mali rice production. The results show that dry season droughts now affect up to 17 percent of the region’s agricultural land in some years, while severe drought zones persist across more than 2.5 million hectares over the 20-year period. In the most recent 5 years, approximately 50 percent of cultivated areas experienced moderate to severe drought conditions. The RDI showed the strongest correlation with NDVI anomalies (r = 0.22), indicating its relative value for assessing vegetation response to moisture deficits. The combined index approach delineated high-risk sub-regions, particularly in central Thung Kula Ronghai and lower Surin, where drought frequency and severity have intensified. These findings underscore the region’s increasing exposure to dry-season water stress and highlight the need for site-specific irrigation development and adaptive cropping strategies. The methodological framework demonstrated here provides a practical basis for improving drought monitoring and early warning systems to support the resilience of Thailand’s high-value rice production under changing climate conditions
คำสำคัญ
agricultural drought, drought index, NDVI anomaly, satellite remote sensing, Thung Kula Ronghai