Assessing Agricultural Yield Loss From Compound Extreme Events Using Three-Dimensional Vine Copulas: Evidence From Jiangsu Province

Why It Matters

The study reshapes how policymakers and insurers evaluate agricultural vulnerability, highlighting overlooked cold‑wet threats and enabling more precise risk‑based decisions in humid subtropical zones.

Key Takeaways

• Three‑dimensional vine copulas capture climate‑yield dependencies better
• Cold‑wet compound events cause 27.3% severe rice loss in Jiangsu
• Water stress (SPEI) outweighs temperature stress in yield impact
• Cold‑type events are twice as frequent as hot‑type events
• Framework offers region‑specific risk estimates for humid subtropical farms

Pulse Analysis

Traditional bivariate copula models often oversimplify the tangled relationships among temperature, precipitation, and crop performance. By extending to a three‑dimensional vine structure, the new framework preserves tail dependencies and nonlinear interactions, delivering a more realistic probabilistic portrait of how simultaneous climate stresses translate into yield outcomes. This methodological leap aligns with a growing demand for high‑resolution risk tools that can inform everything from farm‑level decision‑making to large‑scale commodity pricing models.

The empirical results from Jiangsu overturn a long‑standing assumption that hot‑dry spells dominate agricultural risk in subtropical regions. Cold‑wet events, though less dramatic in temperature terms, exhibited a 27.3% probability of severe rice loss, driven primarily by water deficits captured by SPEI. Moreover, cold‑type compound events occurred roughly twice as often as their hot counterparts, suggesting that adaptation strategies—such as altered planting dates or drought‑tolerant varieties—should prioritize moisture management even during cooler periods. The dominance of water stress over temperature underscores the need to integrate precipitation forecasts more tightly into agronomic planning.

Beyond Jiangsu, the vine‑copula approach offers a template for other humid subtropical belts—from the U.S. Gulf Coast to Southeast Asia—where climate variability manifests in complex, multi‑stress patterns. Insurers can leverage the probabilistic loss estimates to price index‑based crop insurance more accurately, while governments can target subsidies toward irrigation infrastructure and early‑warning systems. As climate change intensifies the frequency of compound extremes, tools that dissect their joint behavior will become essential for safeguarding food security and stabilizing agricultural markets worldwide.