Jiepeng Li , Lajiao Chen , Geli Zhang , Hui Liu , Hongchang Hu , Mengzhen Xu , Xingyan Guo , Zibo Meng , Zhiqiang Dong
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引用次数: 0
Abstract
The Yellow River Basin (YRB) is one of the regions most severely affected by droughts in China. Understanding spatiotemporal variations in droughts in the YRB has become a research hotspot. Despite the attention being paid to droughts in the YRB, most studies have identified drought events separately in terms of space and time. Such simplified methods cannot accurately describe the spatiotemporal structure of droughts or analyze their occurrence patterns. Therefore, this study used a three-dimensional drought identification method to extract meteorological drought events in the YRB from 1901 to 2022 based on their spatiotemporal structure. Drought duration, area, and severity were used to characterize meteorological drought events. Copula functions were used for multivariate frequency analysis of droughts and for calculating return periods. The results indicated that the drought events identified in this study aligned well with the recorded historical drought events. Droughts in the YRB are frequent and periodic, with high-severity droughts covering the entire basin during major events. The most severe drought occurred between February 1962 and April 1963. Drought evolution patterns exhibited high spatiotemporal heterogeneity. The center of the YRB, including Ningxia, Gansu, and Shaanxi, is the region most severely affected by drought, with high-severity droughts and a high frequency of droughts. Droughts are relatively more common during summer and autumn in the YRB. Over an extended period, the drought center in the YRB exhibited a clear migration trajectory, with the risk of meteorological droughts showing a noticeably declining trend after 2000. The findings of this study provide a scientific basis for ecological conservation and sustainable development of the YRB.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.