Analysis on the Characteristics of Dry and Wet Periods in The Yangtze River Basin

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

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 < 0.05), 0.13, 0.04, and 0.16 (p < 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 < 0.05) with a gradient of 0.01/a on a yearly scale and were increased in all seasons (significant in winter (p < 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.

Possible Linkages of Hydrological Variables to Ocean–Atmosphere Signals and Sunspot Activity in the Upstream Yangtze River Basin

Profiling the hydrological response of watershed precipitation and streamflow to large-scale circulation patterns and astronomical factors provides novel information into the scientific management and prediction of regional water resources. Possible contacts of El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), sunspot activity to precipitation and streamflow in the upper Yangtze River basin (UYRB) were investigated in this work. Monthly precipitation and streamflow were utilized as well as contemporaneous same-scale teleconnections time series spanning a total of 70 years from 1951 to 2020 in precipitation and 121 years from 1900 to 2020 in streamflow. The principal component analysis (PCA) method was applied so as to characterize the dominant variability patterns over UYRB precipitation time series, with the temporal variability of first two modes explaining more than 80% of total variance. Long-term evolutionary pattern and periodic variation characteristics of precipitation and streamflow are explored by applying continuous wavelet transform (CWT), cross-wavelet transform (XWT) and wavelet coherence (WTC), analyzing multi-scale correlation between hydrological variables and teleconnections in the time-frequency domain. The results manifest that ENSO exhibits multiple interannual period resonance with precipitation and streamflow, while correlations are unstable in time and phase. PDO and sunspot effects on precipitation and streamflow at interannual scales vary with time-frequency domains, yet significant differences are exhibited in their effects at interdecadal scales. PDO exhibits a steady negative correlation with streamflow on interdecadal scales of approximately 10 years, while the effect of sunspot on streamflow exhibits extremely steady positive correlation on longer interdecadal scales of approximately 36 years. Analysis reveals that both PDO and sunspot have significantly stronger effects on streamflow variability than precipitation, which might be associated with the high spatiotemporal variability of precipitation.