Drought characteristics over China during 1980–2015

Shao, Dongguo; Shu, Chen; Tan, Xuezhi; Gu, W

doi:10.1002/joc.5515

Cited by 61 publications

(57 citation statements)

References 54 publications

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“…The features of droughts have changed significantly due to climate change impact on rainfall parameters such as frequency, intensity and distribution of rainfall (Azam et al, 2018;Shao et al, 2018). Blenkinsop and Fowler (2007) reported a decrease in duration but an increase in the intensity of droughts in Britain.…”

Section: Introductionmentioning

confidence: 99%

Spatial assessment of meteorological drought features over different climate regions in Iran

Sharafati

Nabaei

Shahid

2019

Intl Journal of Climatology

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Iran has a predominantly arid and semi‐arid climate where the drought hazards and their variability are the crucial concerns for water resources management. This study assesses the characteristics and trends of meteorological droughts features in different climate regions of Iran. Monthly rainfall data are analysed using Standardized Precipitation Index (SPI) to reconstruct meteorological droughts for different time steps (1, 3, 6, 9 and 12). The drought events are decomposed into three features, namely Severity (S), Duration (D) and Peak (P) to assess their spatial variations in different climate regions. The Mann–Kendall (MK) test is used to detect the trends in drought features in different climate regions. The percentage area (PA) of increasing/decreasing trend in drought features is computed to assess the spatial variations of trends in each region. Besides, SPI is compared with Standardized Precipitation Evapotranspiration Index (SPEI) to understand the importance of evapotranspiration on meteorological droughts. The high correlations between SPI and SPEI indicate that the results obtained using SPI would not vary if a similar analysis is conducted using SPEI. The results obtained using SPI reveal that short‐duration droughts (6 months or less) are more frequent and severe in the northwest and the north along the Caspian plains while the longer‐duration droughts (more than 6 months) are more frequent and severe in the south, southeast and southwest. Overall, the northwest region of Iran is found most susceptible to droughts in terms of S, P and D. Moderate (40% < PA < 60%) or significant (PA > 60%) increase in the drought features are observed in all climate regions for shorter SPI (3 months or less) except northwest, while no drought feature is found to increase significantly for SPI‐12. Overall, the higher increase in drought S, P and D are found in the central arid region and at higher altitudes.

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Section: Introductionmentioning

confidence: 99%

Spatial assessment of meteorological drought features over different climate regions in Iran

Sharafati

Nabaei

Shahid

2019

Intl Journal of Climatology

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“…They can be grouped into four types including meteorological drought (deficiencies of precipitation), agricultural drought (lack of soil moisture affecting crop development or plant growth), hydrological drought (shortfall on water, such as decreased streamflow or low levels in lakes or reservoirs) and socioeconomic drought (impacts of drought on the supply and demand of certain economic goods) [3]. Due to their high frequency and tremendous damage, evaluations of drought variabilities have attracted increasing attentions in recent studies [1,2,[5][6][7][8]. A multitude of studies have been devoted to the historical assessment of droughts based on different indices and showed the increased risk of droughts under global warming [5,9].…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Variations of Compound Droughts and Hot Extremes in China

Hao

et al. 2019

Atmosphere

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Droughts and hot extremes may lead to tremendous impacts on the ecosystem and different sectors of the society. A variety of studies have been conducted on the variability of the individual drought or hot extreme in China. However, the evaluation of compound droughts and hot extremes, which may induce even larger impacts than the individual drought or hot extreme, is still lacking. The aim of this study is to investigate changes in the frequency and spatial extent of compound droughts and hot extremes during summer in China using monthly precipitation and daily temperature data from 1953 to 2012. Results show that a high frequency of compound droughts and hot extremes mostly occur in the regions stretching from northeast to southwest of China. There is an overall increase in the frequency of co-occurrence of droughts and hot extremes across most parts of China with distinct regional patterns. In addition, an increasing trend in the areas covered by compound extremes has been observed, especially after the 1990s. At regional scales, the increase of the frequency and spatial extent of compound extremes has been shown to be most profound in North China (NC), South China (SC), and Southwest China (SWC), while the decrease of compound extremes was found in Central China (CC). These results show the variability of compound droughts and hot extremes and could provide useful insights into the mitigation efforts of extreme events in China.

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“…Andreadis et al [37] created a severity-area-duration (SAD) analysis method, which regards drought as an individual event. This method combines severity, area (extent), and duration of drought events to effectively analyze changes in the drought characteristics of different regions (e.g., Xiao et al [38]; Shao et al [39]). For example, Sheffield et al [40] used cluster analysis and the SAD method to analyze global and continental drought characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al [43] used the SAD method to analyze the spatial and temporal evolution of drought events between 2000 and 2008 in the Colorado River basin, USA. Shao et al [39] used SC-PDSI index and SAD method to analyze the drought characteristics of recent decades , and found that both methods can capture well the historical drought events of China.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Characterization of Drought Events in China Using the Severity-Area-Duration Method

Yang

Zhang

Wang

et al. 2020

Water

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Global climate change not only affects the processes within the water cycle but also leads to the frequent occurrences of local and regional extreme drought events. In China, spatial and temporal characterizations of drought events and their future changing trends are of great importance in water resources planning and management. In this study, we employed self-calibrating Palmer drought severity index (SC-PDSI), cluster algorithm, and severity-area-duration (SAD) methods to identify drought events and analyze the spatial and temporal distributions of various drought characteristics in China using observed data and CMIP5 model outputs. Results showed that during the historical period (1961–2000), the drought event of September 1965 was the most severe, affecting 47.07% of the entire land area of China, and shorter duration drought centers (lasting less than 6 months) were distributed all over the country. In the future (2021–2060), under both representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios, drought is projected to occur less frequently, but the duration of the most severe drought event is expected to be longer than that in the historical period. Furthermore, drought centers with shorter duration are expected to occur throughout China, but the long-duration drought centers (lasting more than 24 months) are expected to mostly occur in the west of the arid region and in the northeast of the semi-arid region.

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Drought characteristics over China during 1980–2015

Cited by 61 publications

References 54 publications

Spatial assessment of meteorological drought features over different climate regions in Iran

Spatial assessment of meteorological drought features over different climate regions in Iran

Spatial and Temporal Variations of Compound Droughts and Hot Extremes in China

Spatial and Temporal Characterization of Drought Events in China Using the Severity-Area-Duration Method

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