Kwon et al. (2025) Introducing a novel Standardized Precipitation Evaporation Differential Index (SPEDI) for improved flash drought detection and assessment: a case study in South Korea

Identification

• Journal: Stochastic Environmental Research and Risk Assessment
• Year: 2025
• Date: 2025-09-09
• Authors: Hyun‐Han Kwon, Ho-Jun Kim, Joo‐Heon Lee, Hyeon-Cheol Yoon
• DOI: 10.1007/s00477-025-03092-z

Research Groups

• Department of Civil and Environmental Engineering, Sejong University, Seoul, Republic of Korea
• Office of Water & Soil Environmental Technology, Korea Environmental Industry & Technology Institute, Seoul, Republic of Korea
• Department of Civil Engineering, Joongbu University, Goyang, Republic of Korea
• National Integrated Drought Center, National Disaster Management Research Institute, Ulsan, Republic of Korea

Short Summary

This study introduces the Standardized Precipitation Evaporation Differential Index (SPEDI), a new composite drought index designed to better capture flash drought conditions by accounting for both precipitation deficits and evaporative demand. SPEDI demonstrated superior performance in detecting flash droughts and aligning with agricultural damage records across South Korea compared to established indices.

Objective

• To introduce the Standardized Precipitation Evaporation Differential Index (SPEDI) as a novel composite drought index for improved flash drought detection and assessment.
• To compare the performance of SPEDI with established indices (Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Evaporative Demand Drought Index (EDDI)) in detecting and characterizing flash droughts across South Korea.
• To analyze the spatiotemporal patterns of flash droughts and evaluate the effectiveness of the indices in capturing seasonal differences in flash drought behavior.
• To identify key meteorological drivers influencing seasonal and regional variations of flash droughts, aiming to improve early detection and management.

Study Configuration

• Spatial Scale: South Korea (approximately 100,364 km²), with analysis at the administrative district level. Meteorological data from 59 Automated Synoptic Observing Service (ASOS) stations, spatially interpolated using Thiessen polygons, covering an average area with a diameter of approximately 40.05 km.
• Temporal Scale: Daily meteorological data from 1980 to 2022 for primary drought analysis. A subset of data from 2017 to 2022 was used for validation against agricultural damage records. Drought indices were computed with a one-month accumulation period and daily temporal resolution. Flash drought events were defined as a rapid decline in drought index values (from above 50th percentile to below 20th percentile) within a 14-day span.

Methodology and Data

• Models used:
  • Standardized Precipitation Evaporation Differential Index (SPEDI): A novel composite index defined as the standardized sum of SPI and sign-reversed EDDI (TWD = SPI + EDDI, then SPEDI = (TWD - µTWD) / σTWD).
  • Standardized Precipitation Index (SPI): Computed by fitting accumulated precipitation data to a gamma distribution and transforming to standardized scores.
  • Standardized Precipitation Evapotranspiration Index (SPEI): Computed using the climatic water balance (precipitation minus reference evapotranspiration), fitted to a three-parameter log-logistic distribution.
  • Evaporative Demand Drought Index (EDDI): Computed by fitting accumulated reference evapotranspiration (ET₀) data to a gamma distribution and transforming to standardized scores (sign inverted for consistency).
  • Reference Evapotranspiration (ET₀) estimation: Utilized the FAO56 Penman-Monteith equation and a multi-scale surrogate model based on the Hargreaves-Samani equation, with parameters recalibrated using a Bayesian approach.
• Data sources:
  • Meteorological data: Daily records from 59 Automated Synoptic Observing Service (ASOS) stations (1980–2022) operated by the Korea Meteorological Administration, including precipitation, solar radiation, and air temperature.
  • Validation data: Officially reported agricultural damage to field crops (in hectares) from the Ministry of Agriculture, Food, and Rural Affairs for the summer season (June to August) in 2017, 2018, 2019, and 2022, aggregated by administrative district.

Main Results

• SPEDI demonstrated superior performance in detecting flash drought events, providing early warnings in 12 out of 14 events and accurate timing in 10 out of 14 cases, based on agricultural damage records.
• Traditional indices like SPI and SPEI often failed to capture the rapid onset and intensity of flash droughts, while EDDI and SPEDI more reliably reflected observed impacts and delineated drought-affected areas.
• SPEDI offered a more comprehensive and extensive representation of flash drought-affected areas compared to other indices, particularly in regions where SPI and SPEI showed limitations.
• Correlation analysis revealed that SPEI correlated more closely with SPI than with EDDI, suggesting it may not fully account for evaporative demand dynamics. SPEDI, by independently standardizing and combining precipitation and evaporative demand signals, provided a more balanced and responsive measure.
• In a simplified water balance model, SPEDI accurately reflected neutral conditions during transitional states and effectively captured instances of extreme drought (State 4), where SPEI tended to underestimate severity.

Contributions

• Introduction of the Standardized Precipitation Evaporation Differential Index (SPEDI), a novel composite drought index that effectively integrates precipitation deficits and evaporative demand for improved flash drought detection.
• Comprehensive comparative analysis of SPEDI against established drought indices (SPI, SPEI, EDDI) specifically tailored for flash drought conditions in South Korea.
• Empirical validation of SPEDI's superior performance in early warning and accurate timing of flash droughts, using real-world agricultural damage data.
• Elucidation of the limitations of existing indices, particularly SPEI's potential underestimation of evaporative demand under certain conditions, and how SPEDI addresses these shortcomings.
• Development of a practical tool with clear potential for integration into operational early warning systems and drought risk management, particularly for agricultural flash droughts.

Funding

• Cooperative Research Method and Safety Management Technology in National Disaster (Grant: 2022-MOIS63-001(RS-2022-ND641011)) funded by the Ministry of the Interior and Safety (MOIS, Korea).

Citation

@article{Kwon2025Introducing,
  author = {Kwon, Hyun‐Han and Kim, Ho-Jun and Lee, Joo‐Heon and Yoon, Hyeon-Cheol and Kwon, Hyun‐Han},
  title = {Introducing a novel Standardized Precipitation Evaporation Differential Index (SPEDI) for improved flash drought detection and assessment: a case study in South Korea},
  journal = {Stochastic Environmental Research and Risk Assessment},
  year = {2025},
  doi = {10.1007/s00477-025-03092-z},
  url = {https://doi.org/10.1007/s00477-025-03092-z}
}