Abstract
The intensity and frequency of droughts in Poyang Lake Basin have been increasing due to global warming. To properly manage water resources and mitigate drought disasters, it is important to understand the long-term characteristics of drought and its possible link with large-scale climate indices. Based on the monthly meteorological data of 41 meteorological stations in Poyang Lake Basin from 1958 to 2017, the spatiotemporal variations of drought were investigated using the standardized precipitation evapotranspiration index (SPEI). Ensemble empirical mode decomposition (EEMD) methods and the modified Mann–Kendall (MMK) trend test were used to explore the spatiotemporal characteristics and trends of drought. Furthermore, to reveal possible links between drought variations and large-scale climate indices in Poyang Lake Basin, the relationships between SPEI and large-scale climate indices, such as North Atlantic Oscillation (NAO), El Niño–Southern Oscillation (ENSO), Arctic Oscillation (AO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO) were examined using cross-wavelet transform. The results showed that the SPEI in Poyang Lake Basin exhibited relatively stable quasi-periodic oscillation, with approximate quasi-3-year and quasi-6-year periods at the inter-annual scale and quasi-15-year and quasi-30-year periods at the inter-decadal scale from 1958 to 2017. Moreover, the Poyang Lake Basin experienced an insignificantly wetter trend as a whole at the annual and seasonal scales during the period of 1958–2017, except for spring, which had a drought trend. The special characteristics of the trend variations were markedly different in the basin. The areas in which drought was most likely to occur were mainly located in the Poyang Lake region, northwest and south of the basin, respectively. Furthermore, relationships between the drought and six climate indices showed that the drought exhibited a significant temporal correlation with five climate indices at restricted intervals, except for IOD. The dominant influences of the large-scale climate indices on the drought evolutions shifted in the Poyang Lake Basin during 1958–2017, from the NAO, Niño 3.4, and the Southern Oscillation Index (SOI) before the late 1960s and early 1970s, to the AO and PDO during the 1980s, then to the NAO, AO and SOI after the early 2000s. The NAO, AO and SOI exerted a significant influence on the drought events in the basin. The results of this study will benefit regional water resource management, agriculture production, and ecosystem protection in the Poyang Lake Basin.
Highlights
Drought, one of the most complex and widespread natural disasters, has serious impacts on water resources, agriculture, natural ecosystems, and socio-economic development [1,2]
Taking annual Standardized Precipitation Evapotranspiration Index (SPEI) as an example, an overall wetting process during 1958–2017 was detected by both Ensemble empirical mode decomposition (EEMD) and traditional trend methods, our study further indicated that the annual SPEI presented apparent non-linear trends, with first a wetting and a drying trend, suggesting that an obvious transition period from wet to dry occurred in the late 1980s
All the results indicated that EEMD, as an efficient signal analysis method, showed an excellent ability to precisely reflect the nonlinear characteristics of drought variations by extracting the inter-annual and inter-decadal trends from the SPEI series
Summary
One of the most complex and widespread natural disasters, has serious impacts on water resources, agriculture, natural ecosystems, and socio-economic development [1,2]. The PSDI, an index based on precipitation, temperature, and soil moisture that considers water supply and demand, has been successful in long-term drought monitoring. It is weak at demonstrating the effects of short-term drought and cannot assess the intrinsic multi-scalar nature of drought [14]. The SPEI combines simple calculation and the multi-scale features of the SPI with the sensitivity of the PDSI to changes in evaporation demand caused by temperature fluctuations [20] It is good at detecting, monitoring and exploring the characteristics of drought in the context of climate warming [21]. In China, the SPEI has been applied to investigate spatiotemporal variations of droughts in a number of important regions [22,23,24]
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