Guo et al. (2026) Diagnosing drought–flood vulnerability of rice systems across growth stages using Sentinel-1/2 and CHIRPS time series

Identification

• Journal: ISPRS Journal of Photogrammetry and Remote Sensing
• Year: 2026
• Date: 2026-10-17
• Authors: Shanchuan Guo, Bo Yuan, Sung‐Ching Lee, Pengfei Tang, Hongjun Su, Peijun Du
• DOI: 10.1016/j.isprsjprs.2026.10.010

Research Groups

• Jiangsu Provincial Key Laboratory for Advanced Remote Sensing and Geographic Information Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu, China
• Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, China
• Max Planck Institute for Biogeochemistry, Biogeochemical Integration, Jena, Germany
• Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, the Republic of Korea
• College of Geography and Remote Sensing, Hohai University, Nanjing, China

Short Summary

This study developed a Stage-resolved Drought–flood Rice Vulnerability (SDRV) framework using Sentinel-1/2 and CHIRPS time series to diagnose stage-specific vulnerability of single-season rice to drought-flood alternation in the middle and lower Yangtze River region, revealing that vulnerability is highly stage-dependent and amplified in specific growth stages (S2-S3).

Objective

• To characterize rice vulnerability by stage-specific exposure, sensitivity, and recovery, and to develop a Stage-resolved Drought–flood Rice Vulnerability (SDRV) framework to diagnose vulnerability formation in stable single-season rice across the middle and lower reaches of the Yangtze River (MLYR), China, under compound and rapidly alternating drought and flood events.

Study Configuration

• Spatial Scale: Middle and lower reaches of the Yangtze River (MLYR), China, including Anhui, Jiangsu, and adjoining parts of the middle Yangtze region.
• Temporal Scale: 2020–2025.

Methodology and Data

• Models used: Stage-resolved Drought–flood Rice Vulnerability (SDRV) framework, which integrates stage-specific percentile mapping for hydroclimatic and canopy observations.
• Data sources: CHIRPS precipitation time series, Sentinel-1 time series, Sentinel-2 time series.

Main Results

• Annual vulnerability ranked as 2022 > 2025 > 2023 > 2020 > 2021 > 2024.
• Drought-dominant and drought-involved pathways were associated with greater annual vulnerability compared to flood-dominant pathways.
• Vulnerability amplification was primarily concentrated in the tillering to jointing (S2) and booting/heading to grain filling (S3) growth stages.
• In 2022, persistent drought-dominant stress intensified vulnerability towards S3, resulting in the highest annual mean vulnerability (0.599) and the largest high-vulnerability fraction (50.4%).
• In 2025, alternating drought and flood conditions led to vulnerability concentrated in S2 and partially reduced in S3.
• Spatially, a corridor of high vulnerability repeatedly formed across the northern and central MLYR, particularly in Anhui, Jiangsu, and adjacent areas of the middle Yangtze region.
• A positive external-consistency relationship was observed between annual vulnerability and a yield-loss proxy after accounting for year effects.

Contributions

• Development of a novel Stage-resolved Drought–flood Rice Vulnerability (SDRV) framework that characterizes vulnerability through stage-specific exposure, sensitivity, and recovery.
• Provides a process-oriented approach for identifying the specific timing and locations where rice vulnerability intensifies within the growing season under compound drought-flood stress.
• Advances agricultural monitoring and risk assessment by moving beyond conventional single-hazard approaches to address the complexities of rapidly alternating hydroclimatic extremes.

Funding

• Funding information is not available in the provided paper text.

Citation

@article{Guo2026Diagnosing,
  author = {Guo, Shanchuan and Yuan, Bo and Lee, Sung‐Ching and Tang, Pengfei and Su, Hongjun and Du, Peijun},
  title = {Diagnosing drought–flood vulnerability of rice systems across growth stages using Sentinel-1/2 and CHIRPS time series},
  journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
  year = {2026},
  doi = {10.1016/j.isprsjprs.2026.10.010},
  url = {https://doi.org/10.1016/j.isprsjprs.2026.10.010}
}