This study aims to determine the crucial variables for predicting agricultural drought in various climates of Iran by employing feature selection methods. To achieve this, two databases were used, one consisting of ground-based measurements and the other containing six reanalysis products for temperature (T), root zone soil moisture (SM), potential evapotranspiration (PET), and precipitation (P) variables during the 1987–2019 period. The accuracy of the global database data was assessed using statistical criteria in both single- and multi-product approaches for the aforementioned four variables. In addition, five different feature selection methods were employed to select the best single condition indices (SCIs) as input for the support vector regression (SVR) model. The superior multi-products based on time series (SMT) showed increased accuracy for P, T, PET, and SM variables, with an average 47%, 41%, 42%, and 52% reduction in mean absolute error compared to SSP. In hyperarid climate regions, PET condition index was found to have high relative importance with 40% and 36% contributions to SPEI-3 and SPEI-6, respectively. This suggests that PET plays a key role in agricultural drought in hyperarid regions because of very low precipitation. Additionally, the accuracy results of different feature selection methods show that ReliefF outperformed other feature selection methods in agricultural drought modeling. The characteristics of agricultural drought indicate the occurrence of drought in 2017 and 2018 in various climates in Iran, particularly arid and semi-arid climates, with five instances and an average duration of 12 months of drought in humid climates.

本研究旨在通过采用特征选择方法来确定预测伊朗各种气候下农业干旱的关键变量。为了实现这一目标，使用了两个数据库，一个由地面测量组成，另一个包含六种再分析产品，包括温度 ( T )、根区土壤湿度 (SM)、潜在蒸散量 (PET) 和降水量 ( P ) 变量。 1987年至2019年期间。使用单产品和多产品方法中的统计标准对上述四个变量评估了全球数据库数据的准确性。此外，还采用五种不同的特征选择方法来选择最佳的单条件指数（SCI）作为支持向量回归（SVR）模型的输入。基于时间序列 (SMT) 的卓越多产品显示出P、T、PET 和 SM 变量的准确性更高，与 SSP 相比，平均绝对误差平均降低了 47%、41%、42% 和 52%。在极度干旱气候地区，PET 条件指数具有较高的相对重要性，对 SPEI-3 和 SPEI-6 的贡献分别为 40% 和 36%。这表明，由于降水量极少，PET 在极度干旱地区的农业干旱中发挥着关键作用。此外，不同特征选择方法的准确性结果表明，ReliefF在农业干旱建模中优于其他特征选择方法。农业干旱特点表明，2017年和2018年伊朗各种气候地区均出现干旱，特别是干旱和半干旱气候，其中湿润气候地区出现5次干旱，平均干旱持续时间为12个月。