Santhyami, Jumadi, Kuswaji Dwi Priyono, Triastuti Rahayu, Dewi Novita Sari, Murnira Othman, Rudiyanto

Hydrological drought is a climate-induced disaster that directly impacts the agricultural sector,
particularly rice production. This study aims to model drought in a spatial-temporal context and analyse
its impact on rice production in the Upper Bengawan Solo River Basin, Central Java, Indonesia, over
the period 2017–2024. The analysis was conducted using Geographic Information Systems (GIS) based
on Sentinel-2A satellite imagery, annual rainfall data, and rice production records. Drought severity
was quantified using the Normalised Difference Drought Index (NDDI). The results of the drought
modelling were validated through correlation and regression analyses with rainfall data and the extent
of drought-affected areas. Meanwhile, the impact of drought on rice production was assessed using
non-parametric analysis via the LOWESS method. The findings indicate that the spatial-temporal
approach is effective in identifying drought distribution and trends. Spatially, severe drought occurred
in Wonogiri Regency, covering up to 1,203,014.20 hectares, while temporally, the peak occurred in
2018 with a drought area of 571,438.60 hectares. Validation tests revealed a strong positive correlation
between NDDI values and drought extent (r = 0.84), and a negative correlation between NDDI and
rainfall (r = -0.74), indicating that higher NDDI values correspond with wider drought-affected areas
and lower rainfall. Linear regression analysis confirmed NDDI as a significant indicator for drought
monitoring, with a coefficient of determination R² = 0.706, suggesting that 70.6% of the variance in
drought area can be explained by NDDI, and a statistically significant p-value (p = 0.009, p < 0.05).
Moreover, LOWESS analysis showed a non-linear (U-shaped) relationship between NDDI and rice
production, with the highest yields at low NDDI values (2.42–2.44 million tons), declining at medium
NDDI levels (~2.20 million tons), and rising again at high NDDI values (2.35 million tons). This
pattern suggests that the impact of drought on rice production is not linear and is likely influenced by
additional factors such as irrigation infrastructure and crop management practices. Overall, this study
affirms that satellite-based spatial-temporal modelling is an effective approach for analysing
hydrological drought and understanding its implications for agricultural productivity.

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