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Meteorological Drought Events and Their Evolution from 1960 to 2015 Using the Daily SWAP Index in Chongqing, China
Meteorological droughts are natural disasters that have been linked to economic losses and casualties. Decision-makers need to understand the temporal and spatial variation of meteorological drought events at a daily to weekly scale to develop a more elaborate framework for drought risk management. The present study used the standardized weighted average of precipitation index (SWAP) as an indicator of meteorological droughts, computed from the daily precipitation dataset (1960–2015) of 34 meteorological stations in Chongqing, China. The multi-threshold run theory was applied to identify drought events. Variation of drought characteristics was estimated by the modified Sen’s trend test. The results suggested the following findings: (1) the onset, duration, and severity of drought events identified by the SWAP index are in good agreement with the real local records; (2) there was no significant linear trend and abrupt change in annual duration and severity of drought events, but the decadal variation was obvious. From a decadal perspective, the annual frequency, duration, and severity of drought events showed a steady decreasing trend before the 1990s, and then fluctuated upward; (3) the spatial variation of the duration and severity of ordinary drought events was quite inconsistent at different periods. The annual drought days and severity increased from 1960 to 2015 but decreased after 1990. From 1960 to 2015, the duration days and severity of persistent, long persistent, severe, and extreme drought events declined insignificantly in most parts of the middle and southeast regions but increased in the western and northeast regions. The drought situation in Chongqing shows a large range of variation and obvious spatial heterogeneity. The SWAP index is an effective tool to identify the evolution of daily scale meteorological drought events.
Meteorological Drought Events and Their Evolution from 1960 to 2015 Using the Daily SWAP Index in Chongqing, China
Meteorological droughts are natural disasters that have been linked to economic losses and casualties. Decision-makers need to understand the temporal and spatial variation of meteorological drought events at a daily to weekly scale to develop a more elaborate framework for drought risk management. The present study used the standardized weighted average of precipitation index (SWAP) as an indicator of meteorological droughts, computed from the daily precipitation dataset (1960–2015) of 34 meteorological stations in Chongqing, China. The multi-threshold run theory was applied to identify drought events. Variation of drought characteristics was estimated by the modified Sen’s trend test. The results suggested the following findings: (1) the onset, duration, and severity of drought events identified by the SWAP index are in good agreement with the real local records; (2) there was no significant linear trend and abrupt change in annual duration and severity of drought events, but the decadal variation was obvious. From a decadal perspective, the annual frequency, duration, and severity of drought events showed a steady decreasing trend before the 1990s, and then fluctuated upward; (3) the spatial variation of the duration and severity of ordinary drought events was quite inconsistent at different periods. The annual drought days and severity increased from 1960 to 2015 but decreased after 1990. From 1960 to 2015, the duration days and severity of persistent, long persistent, severe, and extreme drought events declined insignificantly in most parts of the middle and southeast regions but increased in the western and northeast regions. The drought situation in Chongqing shows a large range of variation and obvious spatial heterogeneity. The SWAP index is an effective tool to identify the evolution of daily scale meteorological drought events.
Meteorological Drought Events and Their Evolution from 1960 to 2015 Using the Daily SWAP Index in Chongqing, China
Bo Liu (Autor:in) / Yubing Liu (Autor:in) / Wenpeng Wang (Autor:in) / Chunlei Li (Autor:in)
2021
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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