遥相关
蒸散量
气候学
环境科学
水流
连接词(语言学)
太平洋十年振荡
厄尔尼诺南方涛动
降水
流域
气象学
地理
地质学
数学
生物
生态学
地图学
计量经济学
作者
Fei Wang,Zongmin Wang,Haibo Yang,Danyang Di,Yong Zhao,Qiuhua Liang
标识
DOI:10.1016/j.jhydrol.2020.124793
摘要
Traditional univariate drought indices are likely to be insufficient for reflecting the comprehensive information of drought. Thus, it is of great significance to construct a comprehensive drought index for drought monitoring under the consideration of the complexity of meteorological and hydrological conditions in a changing environment. In this study, a new copula-based Standardized Precipitation Evapotranspiration Streamflow Index (SPESI) was proposed, which can synthetically characterize meteorological and hydrological drought. The temporal change, spatial distribution and return period of drought were comprehensively identified in the Yellow River Basin (YRB) from 1961 to 2015. Subsequently, the links between SPESI and teleconnection factors were revealed using cross wavelet transform technology. The results indicated that: (1) based on the combination of meteorological and hydrological drought information, the constructed SPESI could capture the occurrence, duration and termination of drought sensitively and effectively; (2) the seasonal and annual droughts were increasing in the YRB during 1961–2015, with different temporal change characteristics in each subzone; (3) the month and season with the most serious drought was June and summer, with an average SPESI value of −1.23 and −0.89, respectively; (4) Frank-copula was considered to be the best-fitted copula function in the YRB; and (5) the cross wavelet transform illustrated that teleconnection factors had strong influences on the evolution of drought in the YRB, and the impacts of El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and sunspot on the droughts were stronger than those of Pacific Decadal Oscillation (PDO). This study can provide a reliable and effective multivariate index for drought monitoring, which can also be applied in other regions.
科研通智能强力驱动
Strongly Powered by AbleSci AI