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| DOI | 10.1016/j.ejrh.2024.101717 |
| Analysis of SPI index trend variations in the United Kingdom - A cluster-based and bayesian ensemble algorithms approach | |
| 发表日期 | 2024 |
| EISSN | 2214-5818 |
| 起始页码 | 52 |
| 卷号 | 52 |
| 英文摘要 | Study region: United Kingdom (UK). Study focus: A regional investigation of the Standard Precipitation Index (SPI) trends and abrupt changes in the UK has been carried out. The K-means algorithm was employed to partition the study area into six homogeneous regions, each distinguished by specific SPI characteristics. Subsequently, the seasonal Mann-Kendall (MK) test and the Bayesian Changepoint Detection and Time Series Decomposition (BEAST) algorithm were used to evaluate the overall trends for each cluster and SPI time scale, as well as to identify abrupt changes in trend and seasonality along the SPI time series, respectively. New hydrological insights for the region: The seasonal MK test revealed statistically significant increasing SPI trends for all clusters, except for the southeastern area of the UK, where decreasing, but not statistically significant, SPI trends were observed. Moreover, despite a scenario suggesting an increasingly humid UK, the BEAST analysis allowed the detection of decreasing abrupt changes in trends, resulting in sudden changes from wet to dry conditions, that cannot be identified using the MK test. Alongside these, the BEAST analysis has also revealed positive abrupt changes in trends across all UK, as well as positive or negative variations in seasonality, which are followed by longer or shorter wet or dry periods, respectively. Overall, the study approach provides a detailed picture of the SPI trends and abrupt changes, in light of the impact of climate change on the different areas of the UK. |
| 英文关键词 | Drought; SPI; Clustering; Changepoint detection; United Kingdom |
| 语种 | 英语 |
| WOS研究方向 | Water Resources |
| WOS类目 | Water Resources |
| WOS记录号 | WOS:001195879300001 |
| 来源期刊 | JOURNAL OF HYDROLOGY-REGIONAL STUDIES
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/297876 |
| 作者单位 | University of Cassino |
| 推荐引用方式 GB/T 7714 | . Analysis of SPI index trend variations in the United Kingdom - A cluster-based and bayesian ensemble algorithms approach[J],2024,52. |
| APA | (2024).Analysis of SPI index trend variations in the United Kingdom - A cluster-based and bayesian ensemble algorithms approach.JOURNAL OF HYDROLOGY-REGIONAL STUDIES,52. |
| MLA | "Analysis of SPI index trend variations in the United Kingdom - A cluster-based and bayesian ensemble algorithms approach".JOURNAL OF HYDROLOGY-REGIONAL STUDIES 52(2024). |
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