A new perspective for assessing hydro-meteorological drought relationships at large scale based on causality analysis
Bibliographic Data
| ID | 15552467 |
|---|---|
| Authors | Zhaoqiang Zhou (0000-0002-0303-1932, Southern University of Science and Technology), Yibo Ding (0000-0002-2544-3882, Yellow River Institute of Hydraulic Research), Yiyang Zhao (0000-0003-4935-0688, Zhejiang University-University of Edinburgh Institute), Peng Chen (0009-0001-5590-8732, Hohai University), Qiang Fu (0009-0000-9606-6001, Northeast Agricultural University), Ping Xue (0000-0003-0013-7923, Northeast Agricultural University), Suning Liu (0000-0001-9209-4400, Southern University of Science and Technology), Shengzhi Huang (0000-0001-7592-5268, Xi'an University of Technology), Haiyun Shi (0000-0001-5793-1138, Southern University of Science and Technology, corresponding author) |
| Year | 2023 |
| Volume | 18 |
| Issue | 10 |
| Pages | 104046-104046 |
| Publication date | 2023-09-28 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/acfe1e |
| OpenAlex | W4387124448 |
| Language | EN |
| Citations received | 1 |
| References cited | 72 |
Correlation analysis is the common method to evaluate the relationship between two variables; however, it may sometimes cause spurious correlations. Specifically, in the field of hydrometeorology, with the impacts of climate change and human activities, correlation analysis is difficult to identify the true relationship between variables, and thus, causality analysis should be adopted instead. This study analyzed the causal relationship between meteorological drought and hydrological drought in different climatic regions of China by using convergent cross mapping (CCM). We improved the identification of CCM convergence by using the coefficient of variation and applied it in the field of large-scale hydrometeorology. The results of correlation analysis were compared, and the applicability of causality analysis was explored. The results revealed that: In Southeast China, the correlation and causality between meteorological drought and hydrological drought were both large. In Northeast China and central Qinghai–Tibet Plateau, the correlation between meteorological drought and hydrological drought was small, but the causality was large. In view of the spurious correlation, introducing causality analysis can better explain the relationship between meteorological drought and hydrological drought, especially in areas with snowmelt runoff. Overall, CCM can provide valuable causal information from common time series in the field of large-scale hydrometeorology and has a wide range of application values. However, causality analysis cannot explain the positive or negative relationship between variables. Therefore, when analyzing the relationship between variables, the advantages of the two methods should be given full play
Causality (physics · Climatology · Econometrics · Field (mathematics · Geography · Hydrometeorology · Meteorology · Precipitation · Scale (ratio · Scale analysis (mathematics · Snow · Snowmelt · Spurious relationship · Statistics · Climate variability and models · Environmental Science · Hydrology and Drought Analysis · Hydrology and Watershed Management Studies · Mathematics · Geology
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| Citations per year | 1 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |