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2026 Vol.68, Issue 5
An Integrated Agricultural Drought Index Incorporating Event Characteristics and Lagged Responses

가뭄의 빈도·지속기간·강도와 지수 간 시차를 반영한 농업가뭄 통합지수 개발

Young-Sik Muna
,
Won-Ho Namb†
,
Seokkyun Yuc
문 영식a
,
남 원호b†
,
유 석균c
aSenior Researcher, National Agricultural Water Research Center, Hankyong National University
bProfessor, School of Social Safety and Systems Engineering, Institute of Agricultural Environmental Science, National Agricultural Water Research Center, Hankyong National University
cDeputy Director, Water Management Supporting Department, Water Resources Management Office, Korea Rural Community Corporation (KRC)
† Corresponding author Tel.: +82-31-670-5137, Fax: +82-31-670-5139 E-mail: wonho.nam@hknu.ac.kr
30 September 2026. pp. 1-13
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Abstract

Agricultural drought arises from complex interactions among hydro-meteorological variables, making it difficult to characterize using a single drought index. This study develops an integrated agricultural drought index (IADI) that incorporates drought event characteristics and time-lag relationships among multiple indicators. Grid-based drought indices from 1996 to 2024 were analyzed using run theory to quantify key drought characteristics, including frequency, duration, and severity, which were used to construct a composite drought severity measure. The relative importance of individual indices was estimated using entropy, CRITIC, and principal component analysis (PCA), and further refined by incorporating time-lag effects between drought indices and agricultural drought responses. The proposed IADI was applied across South Korea, revealing consistently higher drought intensity in southern regions, particularly in Jeolla and Gyeongsang provinces, as well as in parts of northern Gyeonggi and Jeju Island. Despite differences in weighting schemes, the spatial patterns of IADI were highly consistent, with over 90% of grid cells exhibiting identical drought classifications. These results demonstrate that the proposed index provides a robust and reliable representation of agricultural drought conditions. The IADI offers a practical tool for drought monitoring and spatial risk assessment and establishes a scalable framework for integrating multi-source data and lag-aware modeling in future drought prediction systems. The IADI provides a lag-aware, multi-index framework for robust agricultural drought assessment under increasing hydro-climatic variability.

Keywords
Agricultural drought
drought severity
time-lag effects
multi-index integration
run theory
References
1

Dhawale, R., C. J. Schuster-Wallace, and A. Pietroniro, 2024. Assessing the multidimensional nature of flood and drought vulnerability index: A systematic review of literature. International Journal of Disaster Risk Reduction 112(1): 104764. doi:10.1016/j.ijdrr.2024.104764.

10.1016/j.ijdrr.2024.104764
2

Disasa, K. N., H. Yan, J. Zhang, G. Wang, C. Zhang, D. Zhang, B. Wang, and B. Hao, 2026. Comprehensive review of drought characteristics and intensification under climate change: Implications for agriculture and water resources. Journal of Hydrology 664: 134571. doi:10.1016/j.jhydrol.2025.134571.

10.1016/j.jhydrol.2025.134571
3

Feng, D., G. Cortese, and R. Baumgartner, 2017. A comparison of confidence/credible interval methods for the area under the ROC curve for continuous diagnostic tests with small sample size. Statistical Methods in Medical Research 26(4): 1755-1776. doi:10.1177/0962280215602040.

10.1177/0962280215602040
4

Hodasová, K., D. Krčmář, and I. Ondrejková, 2025. Satellite-based drought assessment: integrating AHP method and fuzzy logic for comprehensive vulnerability and risk analysis. Natural Hazards 121: 11609-11632. doi:10.1007/s11069-025-07254-8.

10.1007/s11069-025-07254-8
5

Hoque, M. A. A., B. Paradgan, and N. Ahmed, 2020. Assessing drought vulnerability using geospatial techniques in northwestern part of Bangladesh. Science of the Total Environment 705(25): 135957. doi:10.1016/j.scitotenv.2019.135957.

10.1016/j.scitotenv.2019.135957
6

Irawan, A. N. R., D. Komori, and V. S. A. Hendrawan, 2023. Correlation analysis of agricultural drought risk on wet farming crop and meteorological drought index in the tropical-humid region. Theoretical and Applied Climatology 153: 227-240. doi:10.1007/s00704-023-04461-w.

10.1007/s00704-023-04461-w
7

Jamalzi, A. R., G. Rahman, F. Akhtar, Q. D. Ikram, and H. H. Kwon, 2025. Spatiotemporal assessment and trend analysis of meteorological drought in Afghanistan (1974–2023) using SPI and SPEI indices. Journal of Hydrology: Regional Studies 61: 102711. doi:10.1016/j.ejrh.2025.102711.

10.1016/j.ejrh.2025.102711
8

Jang, H. W., H. W. Cho, T. W. Kim, and J. H. Lee, 2016. Quantitative characterization of historical drought events in Korea - Focusing on outlier analysis of precipitation -. Journal of Korea Water Resources Association 49(2): 145-153 (in Korean). doi:10.3741/JKWRA.2016.49.2.145.

10.3741/JKWRA.2016.49.2.145
9

Kim, H. J., K. W. Kim, and H. H. Kwon, 2021. Development of a surrogate model based on temperature for estimation of evapotranspiration and its use for drought index applicability assessment. Journal of Korea Water Resources Association 54(11): 969-983 (in Korean). doi:10.3741/JKWRA.2021.54.11.969.

10.3741/JKWRA.2021.54.11.969
10

Kim, J. E., J. Y. Yoo, H. H. Kwon, and T. W. Kim, 2023. Comprehensive drought risk assessment using structural equation modeling and objective weighting methods. Journal of Hydrology: Regional Studies 50: 101538. doi:10.1016/j.ejrh.2023.101538.

10.1016/j.ejrh.2023.101538
11

Lee, J. W., S. S. Jang, S. R. Ann, K. W. Park, and S. J. Kim, 2016. Evaluation of the relationship between meteorological, agricultural and in-situ big data droughts. Journal of the Korean Association of Geographic Information Studies 19(1): 64-79 (in Korean). doi:10.11108/kagis.2016.19.1.064.

10.11108/kagis.2016.19.1.064
12

Lee, S. H., S. H. Yoo, J. Y. Choi, and S. J. Bae, 2017. Assessment of the impact of climate change on drought characteristics in the Hwanghae plain, North Korea using time series SPI and SPEI: 1981-2100. Water 9(8): 579. doi:10.3390/w9080579.

10.3390/w9080579
13

Ma, Q., Y. Li, F. Liu, H. Feng, A. Biswas, and Q. Zhang, 2023. SPEI and multi-threshold run theory based drought analysis using multi-source products in China. Journal of Hydrology 616: 128737. doi:10.1016/j.jhydrol.2022.128737.

10.1016/j.jhydrol.2022.128737
14

Ma, Y., X. Yu, M. Li, J. Huang, H. Li, and T. Zhong, 2025. Comprehensive drought detection, spatiotemporal variations, and attribution across different agricultural climate zones in Eastern China using a copula-based drought index. Agricultural Water Management 321: 109902. doi:10.1016/j.agwat.2025.109902.

10.1016/j.agwat.2025.109902
15

Mohammed, S., K. Alsafadi, G. O. Enaruvbe, B. Bashir, A. Elbeltagi, A. Széles, A. Alsalman, and E. Harsanyi, 2022. Assessing the impacts of agricultural drought (SPI/SPEI) on maize and wheat yields across Hungary. Scientific Reports 12: 12375. doi:10.1038/s41598-022-12799-w.

10.1038/s41598-022-12799-w35614172PMC9132936
16

Mun, Y. S., W. H. Nam, and S. Yu, 2026. Characterizing agricultural drought onset and lag using gridded climate and hydrological data. Journal of the Korean Society of Agricultural Engineers 68(4): 75-88 (in Korean). doi:10.5389/KSAE.2026.68.4.075.

10.5389/KSAE.2026.68.4.075
17

Mun, Y. S., W. H. Nam, M. G. Jeon, N. K. Bang, and T. G. Kim, 2020. Assessment of vulnerability to drought disaster in agricultural reservoirs in South Korea. Atmosphere 11(11): 1244. doi:10.3390/atmos11111244.

10.3390/atmos11111244
18

Nam, W. H., J. Y. Choi, M. W. Jang, and E. M. Hong, 2013. Agricultural drought risk assessment using reservoir drought index. Journal of the Korean Society of Agricultural Engineers 55(3): 41-49 (in Korean). doi:10.5389/KSAE.2013.55.3.041.

10.5389/KSAE.2013.55.3.041
19

Ryu, J. H., J. J. Kim, and K. D. Lee, 2019. Development of Hydroclimate Drought Index (HCDI) and evaluation of drought prediction in South Korea. Journal of the Korean Society of Agricultural Engineers 61(1): 31-44 (in Korean). doi:10.5389/KSAE.2019.61.1.031.

10.5389/KSAE.2019.61.1.031
20

Satapathy, T., J. Dietrich, and M. Ramadas, 2024. Agricultural drought monitoring and early warning at the regional scale using a remote sensing-based combined index. Environmental Monitoring and Assessment 196: 1132. doi:10.1007/s10661-024-13265-y.

10.1007/s10661-024-13265-y39476296PMC11525277
21

Song, Y. S., J. J. Gul, H. Y. Kim, S. M. Jeong, and M. J. Park, 2020. A study on establishment of drought index for agricultural disaster prediction. Journal of the Korean Society of Hazard Mitigation 20(6): 333-341 (in Korean). doi:10.9798/KOSHAM.2020.20.6.333.

10.9798/KOSHAM.2020.20.6.333
22

Suo, X., Y. Jiang, G. Chen, J. Li, Y. Lai, L. Li, M. Lu, X. Wang, B. Fu, and B. Li, 2025. Spatial and temporal patterns of precipitation concentration and their associated risks. Scientific Reports 15: 33152. doi:10.1038/s41598-025-18721-4.

10.1038/s41598-025-18721-441006813PMC12474944
23

Tian, L., S. Yuan, and S. M. Quiring, 2018. Evaluation of six indices for monitoring agricultural drought in the southcentral United States. Agricultural and Forest Meteorology 249: 107-119. doi:10.1016/j.agrformet.2017.11.024.

10.1016/j.agrformet.2017.11.024
24

Tian, Q., J. Lu, and X. Chen, 2022. A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China. CATENA 209: 105804. doi:10.1016/j.catena.2021.105804.

10.1016/j.catena.2021.105804
25

Vicente-Serrano, S. M., S. Begueria, and J. I. Lopez-Moreno, 2010. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. Journal of Climate 23(7): 1696-1718. doi:10.1175/2009JCLI2909.1.

10.1175/2009JCLI2909.1
26

Wang, Q., R. Zhang, J. Qi, J. Zeng, J. Wu, W. Shui, X. Wu, and J. Li, 2022. An improved daily standardized precipitation index dataset for mainland China from 1961 to 2018. Scientific Data 9: 124. doi:10.1038/s41597-022-01201-z.

10.1038/s41597-022-01201-z35354842PMC8967823
27

Wilhite, D. A., and M. H. Glantz, 1985. Understanding: The Drought phenomenon: The role of definitions. Water International 10(3): 111-120. doi:10.1080/02508068508686328.

10.1080/02508068508686328
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 68
  • No :5
  • Pages :1-13
  • Received Date : 2026-04-15
  • Revised Date : 2026-05-06
  • Accepted Date : 2026-05-19
  • DOI :https://doi.org/10.5389/KSAE.2026.68.5.001
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