scholarly journals Spatial and Temporal Characteristics of Drought and Flood in Quanzhou Based on Standardized Precipitation Index (SPI) in Recent 55 Years

2018 ◽  
Vol 06 (08) ◽  
pp. 25-37 ◽  
Author(s):  
Dehe Liu ◽  
Jingfei You ◽  
Qijie Xie ◽  
Yuanyuan Huang ◽  
Huajun Tong
Keyword(s):  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Temporal Characteristics ◽  
Drought And Flood ◽  
Spatial And Temporal Characteristics

scholarly journals Determining Extremes for Future Precipitation in South Korea Based on RCP Scenarios Using Non-Parametric SPI

2020 ◽  
Vol 12 (3) ◽  
pp. 963
Author(s):  
Hemen Mark Butu ◽  
Yongwon Seo ◽  
Jeung Soo Huh
Keyword(s):  
South Korea ◽  
Extreme Precipitation ◽  
Standardized Precipitation Index ◽  
Extreme Drought ◽  
Rcp Scenarios ◽  
Temporal Characteristics ◽  
Extreme Precipitation Events ◽  
Spatial And Temporal Characteristics ◽  
Precipitation Events ◽  
Non Parametric

Historical, downscaled and projected data for six cities in South Korea were collected and analyzed using non-parametric Standardized Precipitation Index (SPI) across the Representative Concentration Pathways (RCPs) RCP4.5 and RCP8.5. SPI results were utilized in further analyses: intensity, decadal frequency, and temporal shifts. Non-parametric SPI was used as it produces more reliable results in terms of their statistical, spatial and temporal characteristics. RCP4.5 was taken to represent concentrations under the current emissions trajectory, while RCP8.5 represents the high-end scenario. Findings suggest that extreme precipitation events are more likely to increase in number than extreme drought across all timescales and RCPs. Variability was observed to increase when comparing SPI obtained from actual, measured and gridded precipitation. More extreme droughts are expected under RCP8.5 forcing as are the occurrence of multiyear droughts and extreme wet events relative to RCP4.5. A seasonal shift in extreme precipitation of up to 3 months earlier was observed. Generally, the period between 2080 and 2100 holds the highest probability to host extremely rare and persistent events.

Drought and Flood Distribution Variation Based on SPI in Nanjing, China

2013 ◽  
Vol 295-298 ◽  
pp. 2116-2120
Author(s):  
Jian Fen Liu ◽  
Xing Nan Zhang ◽  
Hui Min Wang
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Precipitation Data ◽  
Temporal Scales ◽  
Drought And Flood ◽  
Three Stages ◽  
The Standardized Precipitation Index

Many drought and flood indices have been developed, the Standardized Precipitation Index (SPI) is one which has various temporal scales together to form an overall judgment of drought and flood and can be applied easily to different locations to identify and monitor drought and flood. Take Nanjing, China in the study as an example to analysis drought and flood variation by computing SPI values of four time scales including 3-months, 6-months, 12-months and 24-months, applying precipitation data from 1946-2000 of the study area. The results demonstrated SPI can be appropriate to analyze drought and flood variation of Nanjing, while the precipitation data were divided into three stages(1946-1963,1964-1981,1982-2000), the frequencies of various drought and flood classes from various time scales are different, particularly 12-months and 24-months. The time series is longer, the frequencies are more reliable and the differences more little.

Economical exposition to drought events (1980-2001)

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
World Bank ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Precipitation Index ◽  
Climatic Research Unit ◽  
Columbia University ◽  
East Anglia ◽  
Gis Modeling ◽  
The World Bank ◽  
Year 2000

Estimation of the annual economical exposition to drought based on Standardized Precipitation Index. It is based on three sources: 1) A global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia). 2) A GIS modeling of global Standardized Precipitation Index based on Brad Lyon (IRI, Columbia University) methodology. 3) A Global Domestic Product grid for the year 2010, provided by the World Bank. Unit is expected average annual GDP (2007 as the year of reference) exposed in (US $, year 2000 equivalent). For more information, visit: http://preview.grid.unep.ch/ Cost Drought Exposure Risk

Sign in / Sign up

Export Citation Format

Share Document