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.

Highlights

  • Drought is the most frequent, complex, chronic, and severe natural disasters worldwide (Wang et al, 2014; Wang et al, 2015; Zhong et al, 2019)

  • Drought areas caused by water deficit have significantly spread in the past several decades over China because of climate change (Chang et al, 2016), drought situation in China will exacerbate in the future decades (Chen and Sun, 2017), the northwestern China is suffer to severe water resources crises and drought risk (Yao et al, 2018)

  • The results show that the characteristics of drought events in mainland China did not increase significantly, while some stations in the northwest, northeast and southeast regions showed signs of drought reduction, which is identical to previous studies (Cai et al, 2020; Han et al, 2020)

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Summary

Introduction

Drought is the most frequent, complex, chronic, and severe natural disasters worldwide (Wang et al, 2014; Wang et al, 2015; Zhong et al, 2019). Drought have induced the severe economic impacts (Wang et al, 2014; Wang et al, 2015), annual approximately 221 billion dollars loss are caused by the drought worldwide from to 2016 according to statistics of the International Disaster Database (EM-DAT), and drought in China brought in direct economic losses of about USD 10 billion annually between 2004 and 2013 (Hao et al, 2020). It lacks to assess the evolution and spatial-temporal characteristics of drought resulting from water anomalies at the country scale (Wang et al, 2015; Wang et al, 2014). It is imperative to evaluate and monitor and assess the drought characteristics using the long time series data at the large scale, this can play the important role in water resources management, responses to alleviating drought and drought risks management Drought monitoring and evaluation have become the hot topics of discussion and attracted the attention from hydrologists, ecologist, geographer, meteorologists, and other the non-scientists (Todisco et al, 2013; Osorio and Galiano, 2012), there are evidences that drought are intensifying in this century in spatial and temporal terms under climate change (Solomon et al, 2007). it lacks to assess the evolution and spatial-temporal characteristics of drought resulting from water anomalies at the country scale (Wang et al, 2015; Wang et al, 2014).

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