Mun et al. (2026) Lag-aware integrated agricultural drought index using satellite precipitation products

Identification

• Journal: Agricultural Water Management
• Year: 2026
• Date: 2026-08-10
• Authors: Young-Sik Mun, Won‐Ho Nam
• DOI: 10.1016/j.agwat.2026.110689

Research Groups

• National Agricultural Water Research Center, Hankyong National University, Anseong, Republic of Korea
• School of Social Safety and Systems Engineering, Hankyong National University, Anseong, Republic of Korea

Short Summary

This study proposes the integrated agricultural drought index (IADI), a lag-aware framework for spatially continuous agricultural drought assessment using satellite-based precipitation data over South Korea. The IADI combines drought event characteristics derived from run theory, objective weighting methods, and the quantified time-lag relationship between drought indices and observed agricultural drought occurrences.

Objective

• To develop a lag-aware integrated agricultural drought index (IADI) framework that incorporates drought propagation dynamics, time-lag effects, and objective weighting schemes for spatially continuous agricultural drought assessment using satellite-based precipitation data over South Korea.

Study Configuration

• Spatial Scale: Grid cells covering the South Korean mainland at a spatial resolution of 0.05°.
• Temporal Scale: Monthly temporal scale from January 1996 to December 2024.

Methodology and Data

• Models used: Run theory, entropy weight method (EWM), criteria importance through intercriteria correlation (CRITIC), principal component analysis (PCA).
• Data sources: Satellite-based precipitation products (CHIRPS v2.0, CHIRPS v3.0, PERSIANN-CDR, PERSIANN-CCS, CMORPH), TerraClimate dataset for potential evapotranspiration and root-zone soil moisture data.

Main Results

• The study evaluated the performance of five satellite-based precipitation products (CHIRPS v2.0, CHIRPS v3.0, PERSIANN-CDR, PERSIANN-CCS, CMORPH) against ground-based observations from 56 ASOS stations in South Korea.
• CHIRPS v3.0 achieved the best overall performance and was selected as the precipitation input for the IADI framework.
• The study quantified the time-lag relationship between drought indices (SPEI and SMI) and observed agricultural drought occurrences, classifying grid cells into leading, concurrent, or lagging response categories.
• The IADI framework combined drought event characteristics derived from run theory with objective weighting methods (EWM, CRITIC, PCA) and the quantified time-lag relationship between drought indices and observed agricultural drought occurrences.

Contributions

• This study provides a lag-aware integrated agricultural drought index (IADI) framework that incorporates drought propagation dynamics, time-lag effects, and objective weighting schemes for spatially continuous agricultural drought assessment using satellite-based precipitation data over South Korea.
• The IADI framework enhances the representation of drought evolution processes and improves the reliability of agricultural drought assessments.

Funding

• This research was funded by [project name], [program name], [reference code].

Citation

@article{Mun2026Lagaware,
  author = {Mun, Young-Sik and Nam, Won‐Ho},
  title = {Lag-aware integrated agricultural drought index using satellite precipitation products},
  journal = {Agricultural Water Management},
  year = {2026},
  doi = {10.1016/j.agwat.2026.110689},
  url = {https://doi.org/10.1016/j.agwat.2026.110689}
}