Utilizing GRACE-based groundwater drought index for drought characterization and teleconnection factors analysis in the North China Plain
journal contributionposted on 10.07.2020, 13:26 authored by Fei Wang, Zongmin Wang, Haibo Yang, Danyang Di, Yong Zhao, Qiuhua LiangQiuhua Liang
Traditional drought monitoring methods rely on ground station data, which are difficult to reflect large-scale dynamic drought information. Thus, Gravity Recovery and Climate Experiment (GRACE) gravity satellite technology is applied to monitor and estimate drought, which can provide new data sources and measurement instruments for drought investigation. In this study, the GRACE groundwater drought index (GGDI) was utilized as a metric for assessing drought. The temporal evolution, spatial distribution and trend characteristics of drought were comprehensively identified in the North China Plain (NCP) from 2003 to 2015. Subsequently, the links between GGDI and teleconnection factors were clarified using cross wavelet transform technology. The results indicated that: (1) the quantitative results of GRACE were reliable and robust for drought evaluation; (2) the most serious drought event occurred from August 2013 to September 2014, with an average GGDI value of −1.36; (3) the monthly and seasonal droughts were increasing based on the modified Mann-Kendall (MMK) trend test method; and (4) the cross wavelet transform revealed that teleconnection factors had significant influences on drought evolution, and El Niño-Southern Oscillation (ENSO) had the strongest impact on drought in the NCP. This study sheds new insights into drought monitoring by using GRACE gravity satellite, which can be applied in other regions as well.
National Key R&D Program of China (grant number 2018YFC0406505)
Key Scientific Research Projects of Henan Colleges and Universities (grant number 19A170014)
National Natural Science Foundation of China (grant number 51779093 & 51739009)
Science and technology project of Guizhou Province Water Resources Department (grant number KT201705)
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