Drought has significant impacts on human survival and social development, particularly on crop production. Agricultural drought is the most direct consequence of drought on crops. In this study, a Probabilistic Agricultural Drought Forecasting (PADF) framework was developed to employ the Ensemble Bayesian Least Square Support Vector Machine (EBLSSVM) method for bias correction in precipitation and temperature projections from multiple Regional Climate Models (RCMs). Vine Copula-Based Projection Model (VCPM) was then developed for accurate agricultural drought projections, providing deterministic results and valuable 90 % predictive intervals. The results indicate that the EBLSSVM method can generate better climate projections than the original outputs from RCMs and bias-corrected results from other bias-correction techniques. Based on the projection results from VCPM, the study found that drought will be a significant concern in Fujian province, especially in the southeast coastal region. Drought conditions are projected to be more severe in the 2050s than in the 2080s, under both RCP4.5 and RCP8.5. The average SSI values during months with a wet trend ranged from 0.1 to 0.3, whereas months with a drought trend predominantly exhibited average SSI values exceeding -0.5. Notably, SSI values as low as -2.0 were observed during wet trend months, underscoring the urgency of addressing future drought, particularly in coastal regions. However, even during wet periods, at least one extreme drought month is expected, suggesting that extreme drought conditions will become more severe in the future. CMIP5 and CMIP6 predictions showed good consistency in temporal and spatial dimensions, with CMIP6 indicating more significant and consistent future drought changes compared to CMIP5.

中文翻译：

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气候变化下概率农业干旱预报（PADF）框架的开发

干旱对人类生存和社会发展特别是农作物生产产生重大影响。农业干旱是干旱对农作物最直接的影响。在本研究中，开发了概率农业干旱预报 (PADF) 框架，采用集合贝叶斯最小二乘支持向量机 (EBLSSVM) 方法对多个区域气候模型 (RCM) 的降水和温度预测进行偏差校正。随后开发了基于 Vine Copula 的预测模型 (VCPM)，用于准确的农业干旱预测，提供确定性结果和有价值的 90% 预测区间。结果表明，与 RCM 的原始输出和其他偏差校正技术的偏差校正结果相比，EBLSSVM 方法可以生成更好的气候预测。根据VCPM的预测结果，研究发现干旱将成为福建省特别是东南沿海地区的重大问题。根据 RCP4.5 和 RCP8.5，预计 2050 年代的干旱状况将比 2080 年代更加严重。潮湿趋势月份的平均 SSI 值范围为 0.1 至 0.3，而干旱趋势月份的平均 SSI 值主要超过 -0.5。值得注意的是，在潮湿趋势月份，SSI 值低至 -2.0，这凸显了解决未来干旱问题的紧迫性，特别是在沿海地区。然而，即使在丰水期，预计至少有一个极端干旱月份，这表明未来极端干旱状况将变得更加严重。 CMIP5和CMIP6的预测在时间和空间维度上表现出良好的一致性，与CMIP5相比，CMIP6表明未来干旱变化更加显着和一致。