Spatial Heterogeneity of Rice Production Responses to ENSO Anomalies in Banten Province, Indonesia - Tian Mulyaqin; Rita Nurmalina; Nunung Kusnadi; Bambang Hendro Trisasongko (Journal of Applied Agricultural Science and Technology, 2026)
El Niño–Southern Oscillation (ENSO) anomalies are significant drivers of climate variability affecting agricultural production, although their impacts exhibit high spatial and temporal complexity. This study investigates rice production responses to ENSO phases in four districts of Banten Province, Indonesia—Pandeglang, Serang, Lebak, and Tangerang—during the 2000–2024 period. Utilizing descriptive statistics, OLS regression, and comparative time-series models (linear, quadratic, exponential, and moving average), the study evaluates how climatic signals are translated into production outcomes. Results reveal significant spatial heterogeneity. Although El Niño generally suppressed yields, regression analysis identifies Tangerang as the only district with a statistically significant vulnerability to drought-induced losses (β= -33,371 t/year). Conversely, the study identifies a "Triple-Dip" La Niña anomaly (2020–2023) where excessive rainfall reduced production in flood-prone districts such as Pandeglang, challenging the assumption that La Niña universally benefits rice yields. Methodologically, second- and third-order moving average models (MA(2) and MA(3)) consistently outperformed alternative specifications in capturing stochastic fluctuations. These findings underscore the localized nature of ENSO impacts and the inadequacy of generalized policies. The study therefore advocates spatially differentiated adaptation strategies, including localized early warning systems and improved drainage infrastructure, to mitigate drought and flood risks in Banten’s rice systems.