Spatiotemporal Variations in Drought and Wetness from 1965 to 2017 in China

Zeng, Zhixiong; Wu, Wenxiang; Li, Yamei; Zhou, Yang; Zhang, Zhengtao; Zhang, Shuilong; Guo, Yahui; Huang, Han; Li, Zhaolei

doi:10.3390/w12082097

Cited by 15 publications

(12 citation statements)

References 47 publications

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“…These results are consistent with those of previous studies (Wu et al 2017;Zhai et al 2015;Wang 2017). For example, Zeng et al (2020) used the SPEI to observe that China had experienced a signi cant wetting trend observed in the western region, the Tibetan Plateau, and eastern China from 1965 to 2017. Xu et al (2015) showed that the western part of the North China Plain and Loess Plateau experienced a signi cant drying trend using three months of SPI, RDI, and SPEI indices; this trend was mainly attributed to a signi cant decrease in precipitation.…”

Section: Discussionsupporting

confidence: 90%

“…The wetting trend mainly occurred in the west, east, and northeast of the study area, whereas the drying trend was concentrated on the Loess Plateau. These results are consistent with those of previous studies (Wu et al 2017;Zhai et al 2015;Wang 2017). For example, Zeng et al (2020) used the SPEI to observe that China had experienced a signi cant wetting trend observed in the western region, the Tibetan Plateau, and eastern China from 1965 to 2017.…”

Section: Discussionsupporting

confidence: 90%

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Does Drought Show a Significant Decreasing Trend From 1961 to 2017 in Northern China?

Liu

et al. 2021

Preprint

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Understanding the variation of drought is essentially important in climate change and risk assessment. Based on the monthly meteorological data at 321 stations, this study computed the Standardized Precipitation Evapotranspiration Index (SPEI), which was estimated using the potential evapotranspiration (PET) with the Penman–Monteith equation. The trends, affected-area, duration, and frequency of drought was determined using the piecewise linear regression method (LRM) for 1961–2017 over northern China. The results found that (1) drought displayed a wetting trend in 1961-2017 at a rate of 0.05/10a (p > 0.05), which generally occurred in winter and in most study areas, particularly in the Xinjiang Uygur Autonomous Region. In contrast, an apparent drying trend occurred on the Loess Plateau. (2) The LRM identified that the turning point (TP) for trends occurred in 1990; the annual SPEI had been increasing pre-1990 and decreasing post-1990. This was especially the case in the Xinjiang Uygur Autonomous Region, Tibet, Gansu, and Inner Mongolia, consistent with patterns of seasonal drought at their respective TP apart from autumn. (3) From 1961 to 2017, the drought-affected area decreased at a rate of −1.69%/10a (p < 0.05). This area decreased before the TP and increased after the TP at different drought levels. The seasonal drought also showed decreasing trend, particularly in winter. (4) The highest frequency and duration of drought occurred in the Loess Plateau and Xinjiang Uygur Autonomous Region, respectively, although it decreased post-1990. These findings suggest that long-term trends in drought were not significant in northern China during 1961–2017. Although the severity, frequency, and duration of drought decreased post-1990, the recent drying trend and increase in the drought-affected area should not be dismissed.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionsupporting

confidence: 90%

Does Drought Show a Significant Decreasing Trend From 1961 to 2017 in Northern China?

Liu

et al. 2021

Preprint

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“…Many meteorological drought indexes had been developed for quantifying drought and wetness fluctuations, including the Palmer drought severity index (PSDI) [14], standardized precipitation index (SPI) [15], China-Z index (CZI) [16], standardized precipitation evapotranspiration index (SPEI) [17], and soil wetness deficit index (SWDI) [18]. Among these indexes, SPI and SPEI are easy to obtain and widely used for drought and wetness changes and their impact on agriculture and ecological environment in many countries and regions of the world [19][20][21][22][23][24][25]. e main advantage of the SPI is that it is calculated at multi-time scales and can monitor different drought types [26,27].…”

Section: Introductionmentioning

confidence: 99%

Drought and Wetness Variability and the Respective Contribution of Temperature and Precipitation in the Qinghai-Tibetan Plateau

Zhang

Gao

2021

Advances in Meteorology

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Quantifying drought and wetness fluctuations is of great significance to the regional ecological environment and water resource security, especially in the fragile Qinghai-Tibetan Plateau (QTP). In this paper, the standardized precipitation evapotranspiration index (SPEI) was calculated based on the observed data and China Meteorological Forcing Dataset (CMFD) in the QTP for the period of 1979–2015, and the drought and wetness evolution based on the SPEI series and respective contribution of temperature and precipitation were also analyzed. Results indicated that meteorological stations are mainly concentrated in the eastern part of the plateau, which cannot reflect the drought and wetness trend of the whole QTP. The linear trend and Mann–Kendall test revealed that SPEI series calculated based on CMFD data at 1-, 3-, 6-, 9-, 12-, and 24-month time scales all showed significant upward trend p < 0.01 , indicating that the QTP as a whole tended to be wetter. Spatially, the regions with significant drying p < 0.1 and increased drought probability were mainly concentrated in the Qaidam Basin and the southern part of the QTP, and the mean contribution rates of temperature and precipitation variability to SPEI trend in these regions were 60% and −11%, respectively. The regions with significant wetting p < 0.1 and decreased drought probability were mainly concentrated in the northeast, central, and western parts of the plateau, and the mean contribution rates of temperature and precipitation variability to SPEI trend were −9% and 61% in these regions. From the statistics in different climatic regions, most of the arid and humid regions in the QTP tended to be drier, while the semiarid regions tended to be wetter.

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“…In Hubei, the variation in groundwater resources was more significant. (2) The water resources in the eco-economic belt are not evenly spatially distributed; they are concentrated in Anhui, Henan, and Jiangsu, while Hubei exhibits relative water scarcity. (3) The total volume of water resources increases or decreases with the increase or decrease in annual precipitation.…”

Section: Discussionmentioning

confidence: 99%

“…(1) Drought and extreme precipitation events can have significant environmental and socioeconomic impacts. The effects of global warming and intensified anthropogenic activity (e.g., water reservoir construction, urbanization, and deforestation) are expected to accelerate the global hydrological cycle (2,3) and thus alter the spatiotemporal patterns of precipitation. This is in turn projected to result in the increased occurrence of extreme weather events, including severe droughts or floods, in numerous regions around the globe.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Sensitivity Characteristics of Water Resources in Huai River Ecological–Economic Belt, China

Wang¹,

Long²,

Mao³

et al. 2021

Sensors and Materials

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To achieve precision control of water resources in the Huai River Basin, the precision of the forecast and control of such resources must be improved. In the present study, a recharge method was applied to the basic data obtained from the quantitative forecast and precision control of water resources in the Huai River. In addition, the water balance method was used to analyze the spatiotemporal characteristics of the water resources in the Huai River ecological-economic belt (hereafter the eco-economic belt). Using data on water resources in the eco-economic belt from 1998 to 2018, we explored the spatiotemporal changes and the characteristics of the water resources in the region. The analysis revealed the following: (1) The eco-economic belt has abundant water resources with regard to total volume, but they are unevenly spatiotemporally distributed. (2) The water resources in the eco-economic belt display a declining trend. Abundant water resources are concentrated in the provinces of Anhui, Henan, and Jiangsu, while they are relatively scarce in Hubei. (3) Examination of the changes in the water resources of the provinces located in the eco-economic belt indicates substantial changes in total water resources and rainfall on an annual basis. Henan and Anhui had the largest and smallest annual changes in total water resources, respectively. The rainfall changes are essentially periodic; that is, they alternate annually between high and low over time. Henan and Hubei had the highest changes in surface water resources and groundwater resources, respectively. (4) Rainfall is the primary source of the water resources in the eco-economic belt. The spatial distributions of surface water and groundwater are consistent. Overall, the present study provides valuable empirical evidence of water resource control in the eco-economic belt.

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Spatiotemporal Variations in Drought and Wetness from 1965 to 2017 in China

Cited by 15 publications

References 47 publications

Does Drought Show a Significant Decreasing Trend From 1961 to 2017 in Northern China?

Does Drought Show a Significant Decreasing Trend From 1961 to 2017 in Northern China?

Drought and Wetness Variability and the Respective Contribution of Temperature and Precipitation in the Qinghai-Tibetan Plateau

Spatiotemporal Sensitivity Characteristics of Water Resources in Huai River Ecological–Economic Belt, China

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