Cao et al. (2025) Standardized compound drought and heatwave index: A new compound drought and heatwave events monitoring index considering evapotranspiration effects

Identification

• Journal: International Journal of Applied Earth Observation and Geoinformation
• Year: 2025
• Date: 2025-12-11
• Authors: Shengpeng Cao, Lei Li, Chunyang He, Tao Qi
• DOI: 10.1016/j.jag.2025.105023

Research Groups

• Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing, China
• State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University, Beijing, China
• Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing, China
• Faculty of Geographical Science, Beijing Normal University, Beijing, China
• Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining, China

Short Summary

This study developed the Standardized Compound Drought and Heatwave Index (SCDHI) by integrating the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Temperature Index (STI) using Gaussian copula modeling. The SCDHI significantly improved the monitoring accuracy and capability for compound drought and heatwave events (CDHEs), particularly in assessing vegetation responses, compared to existing indices.

Objective

• To develop a new standardized compound drought and heatwave index (SCDHI) that explicitly incorporates evapotranspiration effects, by combining the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Temperature Index (STI) using Gaussian copula modeling.
• To evaluate the reliability and superiority of the SCDHI compared to existing methods (e.g., SCEI) in monitoring CDHEs, particularly in assessing vegetation responses.
• To analyze the spatiotemporal changes of CDHEs across China during the summer period from 1990 to 2022 using the SCDHI.

Study Configuration

• Spatial Scale: Mainland China (latitudes 3°N–53°N and longitudes 73°E–135°E), divided into eight geographically distinct regions. All datasets were resampled to a 5 km spatial resolution.
• Temporal Scale: Monthly data from 1990 to 2022, with a focus on summer periods. The study utilized 1-month SPEI (SPEI-1) and 1-month STI (STI-1) as optimal indicators.

Methodology and Data

• Models used:
  • Standardized Compound Drought and Heatwave Index (SCDHI) developed using Gaussian copula probability distribution modeling, integrating SPEI-1 and STI-1.
  • Standardized Precipitation Evapotranspiration Index (SPEI)
  • Standardized Temperature Index (STI)
  • Standardized Compound Event Index (SCEI) for comparative analysis.
  • Gaussian copula, Frank copula, and t-copula for joint distribution function evaluation.
  • Mann-Kendall (MK) test for trend analysis.
  • Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Root Mean Square Error (RMSE) for model goodness-of-fit.
  • Gringorten plotting position for empirical frequency estimation.
  • Linear detrending method for time series data.
  • Two-sample t-test for statistical significance.
• Data sources:
  • Monthly SPEI data (1990–2022) from Gebrechorkos et al. (2023), with a 5 km spatial resolution.
  • Monthly temperature and precipitation data (1990–2022) from the Qinghai–Tibet Plateau Scientific Data Center, with a 1 km spatial resolution.
  • Global Normalized Difference Vegetation Index (NDVI) datasets (1990–2022) from Li et al. (2023), with a 1/12° spatial resolution and 16-day temporal resolution.
  • Geographic auxiliary data from the Data Center for Resources and Environmental Sciences and the Chinese Academy of Sciences.
  • China Meteorological Disaster Yearbook (2023) for identifying typical CDHE cases.

Main Results

• The SCDHI demonstrated significantly improved monitoring accuracy and capability for CDHEs, particularly in assessing vegetation responses, compared to existing indices like the SCEI.
• The SCDHI effectively corrected the underestimation of CDHE spatial extent and severity in vegetation areas by explicitly incorporating evapotranspiration effects.
• The SCDHI exhibited high reliability and consistency with the SCEI in monitoring CDHE characteristics (frequency, severity, intensity, and duration). For example, in Southwest China (SW), both indices showed comparable average frequencies (SCDHI: 2.1 events per decade; SCEI: 1.9 events per decade) and durations (both 1.3 months).
• From 1990 to 2022, CDHEs in China increased significantly, with SCDHI values decreasing across 74.80% of regions at an average rate of -0.09 per decade (P < 0.05).
• Regionally, North China (NC) experienced the most pronounced reduction in SCDHI (-0.21 per decade), followed by the Middle and Lower Reaches of the Yangtze River (MLYR) (-0.19 per decade). The Qinghai–Tibet Plateau (QTP) showed an increasing trend (+0.10 per decade).
• The mean SCDHI decreased from +0.03 during 1990–2005 to -0.12 during 2006–2022, indicating an overall increase in CDHEs.
• The spatial coverage of CDHEs in China expanded significantly across all severity grades between 1990-2005 and 2006-2022 (slight: 16.68% to 20.05%; moderate: 3.29% to 4.77%; severe: 0.15% to 0.32%). NC, MLYR, and Inner Mongolia (IM) showed the most pronounced increases in affected areas.
• The SCDHI was significantly lower (indicating more severe conditions) than the SCEI in vegetation areas (P < 0.05), with the difference increasing with higher NDVI values, highlighting SCDHI's superior ability to capture vegetation stress.

Contributions

• Developed a novel Standardized Compound Drought and Heatwave Index (SCDHI) that explicitly incorporates evapotranspiration (ET) effects, addressing a critical limitation of traditional indices that rely solely on precipitation and temperature.
• Demonstrated that the inclusion of ET significantly enhances the accuracy of CDHE monitoring, particularly in assessing vegetation responses and correcting the systematic underestimation of event severity in vegetated regions.
• Provided a robust and effective tool for multiscale monitoring of CDHEs, thereby improving assessments of their environmental and societal impacts and supporting the development of early warning systems.
• Offered a comprehensive spatiotemporal analysis of CDHE trends in China from 1990 to 2022, revealing significant increases in their frequency, severity, intensity, and duration across most regions.

Funding

• Ministry of Science and Technology of the People’s Republic of China (The National Key Research and Development Program of China, grant No. 2024YFF1307000)
• National Natural Science Foundation of China (grant No. 42371296)
• Key Laboratory of Environmental Change and Natural Disaster, MOE (grant No. 2023-KF-01)

Citation

@article{Cao2025Standardized,
  author = {Cao, Shengpeng and Li, Lei and He, Chunyang and Qi, Tao},
  title = {Standardized compound drought and heatwave index: A new compound drought and heatwave events monitoring index considering evapotranspiration effects},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  year = {2025},
  doi = {10.1016/j.jag.2025.105023},
  url = {https://doi.org/10.1016/j.jag.2025.105023}
}