Daily standardized precipitation index with multiple time scale for monitoring water deficit across the mainland China from 1961 to 2018

Qianfeng Wang, Rongrong Zhang, Yanping Qu, J. Zeng, Xiaoping Wu, Xiao-feng Zhou, Binyu Ren, Xiaohang Li, D. Zhou
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引用次数: 2

Abstract

Abstract. With the increasing shortage of water resources, drought has become one of the hot issues in the world. The standardized precipitation index (SPI) is one of the widely used drought assessment indicators because of its simple and effective calculation method, but it can only assess drought events more than one month. We developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI and meet the needs of drought types at different time scales. Taking three typical stations in Henan, Yunnan and Fujian Province as examples, the drought events identified by SPI with different scales were consistent with the historical drought events recorded. Meanwhile, we took the 3-month scale SPI of soil and agricultural drought as an example, and analyzed the characteristics of drought events in 484 stations in Chinese mainland. The results showed that most of the drought events the mainland China did not increase significantly, and some parts of the northwestern Xinjiang and Northeast China showed signs of gradual relief. In short, our daily SPI data set is freely available to the public on the website https://doi.org/10.6084/m9.figshare.14135144 , and can effectively capture drought events of different scales. It can also meet the needs of drought research in different fields such as meteorology, hydrology, agriculture, social economy, etc.
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1961 - 2018年中国大陆多时间尺度日标准化降水指数监测水分亏缺
摘要随着水资源的日益短缺,干旱已成为世界各国关注的热点问题之一。标准化降水指数(SPI)因其计算方法简单有效而成为应用广泛的干旱评价指标之一,但它只能评价一个月以上的干旱事件。为了弥补常用SPI的不足,满足不同时间尺度干旱类型的需求,我们开发了一个新的多尺度日SPI数据集。以河南、云南和福建3个典型台站为例,不同尺度SPI识别的干旱事件与历史记录的干旱事件基本一致。同时,以土壤和农业干旱3个月尺度SPI为例,分析了中国大陆484个站点的干旱事件特征。结果表明,中国大陆大部分干旱事件没有明显增加,新疆西北部和东北部分地区有逐渐缓解的迹象。简而言之,我们每天的SPI数据集在https://doi.org/10.6084/m9.figshare.14135144网站上免费向公众开放,可以有效地捕捉不同尺度的干旱事件。可满足气象、水文、农业、社会经济等不同领域的干旱研究需求。
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