Global climate change has significantly altered extreme rainfall regimes in Australia. However, the spatiotemporal distribution of extreme dry and wet conditions, and their relationship with the El Nino-Southern Oscillation (ENSO), particularly within Australian broadacre zones (high rainfall, wheat-sheep, and pastoral zones), remains poorly understood. Hence, we analyzed the spatiotemporal variability of extreme dry and wet events with Standardized Precipitation Index (SPI) and quantified ENSO impacts on rainfall extremes over Australian broadacre zones. The results showed that high rainfall zone and wheat-sheep zone of eastern Australia became drier, while Western Australia (pastoral zone) became wetter from 1960 to 2020. In the past decade, the hotspot areas to extreme or severe dry and wet events constituted 6.5 % and 7.8 % of stations in Australia, demonstrating the widespread concurrence of extreme wet and dry conditions in the high rainfall and wheat-sheep zones. The hotspot areas of dry events shifted from the southeastern into central-eastern Australia, as well as dry conditions weakened in southwestern Australia and eastern Tasmania. In contrast, hotspot areas of wet events occurred more frequently in the southwest and east of continental Australia. The relationship between SPI and ENSO indexes identified that Nino 3.4 sea surface temperature anomaly (SSTA) Index, Nino 4 SSTA Index, cold-tongue ENSO Index and Southern Oscillation Index (SOI) in the preceding winter were robust precursors to summer extreme rainfall events over Australia. Spatially, the ENSO-rainfall relationship showed the eastern-western asymmetric pattern and eastern Australia was a key area affected by above four ENSO indexes. We further confirmed the northeast Australian rainfall was significantly affected by ENSO, but this robust relationship does not extend to the south of Great Dividing Range. Meanwhile, most of Great Artesian Basin and Murray-Darling Basin were significantly affected by 4 similar to 6 ENSO indexes, which was effective in predicting summer rainfall extremes based on pre-occurred ENSO signals. Our findings provide insights for drought early warning, which are crucial for enhancing water usage and shaping the agricultural system to better adapt to climate extremes in Australia.