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Drought is a severe natural hazard all over the world, resulting in enormous losses in many aspects, especially in agriculture. It is essential to analyze the spatio-temporal variation of drought and its relationships with the El Niño-Southern Oscillation under a background of global climate change for better drought prevention. The Songhua River Basin (SHRB), which is an important food base in northeastern China that suffered a severe drought in 2020, was chosen as the research site. The standardized precipitation evapotranspiration index (SPEI) was chosen as the drought index to analyze the spatio-temporal variation of droughts in the SHRB by linear regression analysis and T-test using the meteorological data from 1960 to 2019. The cross-wavelet analysis was adopted to reveal the relationship between the SPEI and El Niño-Southern Oscillation indexes (the Niño 1+2 SST Index (SST1), Niño 3 SST Index (SST2), Niño 3.4 SST Index (SST3), Niño 4 SST Index (SST4), and Southern Oscillation Index (SOI)). The results reveal that the changing trends of yearly, spring, summer, autumn, and winter precipitation were 0.56, 1.47 (p &lt; 0.05), 0.13, 0.04, and 0.16 (p &lt; 0.05) mm/a, respectively; the precipitations were higher in the southeastern regions and lower in the western regions, with extreme values of 831.62 mm and 381.69 mm, respectively. The SPEI was significantly increased (p &lt; 0.05) with a gradient of 0.01/a on a yearly scale and were increased in all seasons (significant in winter (p &lt; 0.05)). The drought probability on a yearly scale was dominated by summer and autumn. The SPEI was positively correlated with SST1, SST2, SST3, and SST4 in a different period with a different resonant period and was negatively correlated with the SOI with a short-term period for 3–4 years from 1986 to 1990 and a long-term period for 9–12 years from 1992 to 2010. These results could provide a scientific guide for drought prevention in the SHRB.

Spatio-Temporal Characteristics of Drought and Its Relationship with El Niño-Southern Oscillation in the Songhua River Basin from 1960 to 2019