Rainfall variability presents an increasing challenge to agricultural sustainability in tropical regions, particularly in topographically complex basins such as the Brantas River Basin (BRB) in Indonesia. This study aimed to (1) characterize long-term rainfall patterns, (2) delineate homogeneous rainfall regions, and (3) assess the relationships between rainfall parameters and the yields of rice, maize, and vegetables. Using daily rainfall data from 193 stations (1996–2020), we derived 22 annual rainfall parameters encompassing magnitude, timing, frequency, variability, and trends. Principal Component Analysis (PCA) revealed that the first seven components explained 83 % of the total variance, with rainfall magnitude and frequency emerging as dominant factors. Hierarchical Clustering on Principal Components (HCPC) identified four distinct rainfall clusters across the BRB. Correlation analysis indicated that rice yields were positively associated with moderate rainfall and the number of rainy days (r > 0.70 in some areas), whereas maize and vegetable yields exhibited mixed responses to rainfall variability and extremes. In addition to commonly used metrics such as total annual rainfall, more specific indicators—such as the number of rainy days, wet spells, and dry spells—also contributed to yield variation. The spatial heterogeneity of correlation patterns underscores the geographic variability in long-term rainfall–yield relationships. These findings highlight the need for region-specific adaptation strategies to address the diverse climate risks faced by smallholder farming systems in the BRB.
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