Assessment of Meteorological Drought in Korea under Climate Change

被引：25

作者：

Kwak, Jaewon ^{[1
]}

Kim, Soojun ^{[2
]}

Jung, Jaewon ^{[3
]}

Singh, Vijay P. ^{[4
]}

Lee, Dong Ryul ^{[5
]}

Kim, Hung Soo ^{[6
]}

机构：

[1] Nakdong River Flood Control Off, Forecast & Control Div, Busan 49300, South Korea

[2] Columbia Univ, Earth Inst, Columbia Water Ctr, New York, NY 10027 USA

[3] Seoul Inst, Dept Safety & Environm Res, Seoul 06756, South Korea

[4] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA

[5] Korea Inst Civil Engn & Bldg Technol, Water Resources Res Div, Goyang 10223, South Korea

[6] Inha Univ, Dept Civil Engn, Inchon 22212, South Korea

来源：

ADVANCES IN METEOROLOGY | 2016年 / 2016卷

关键词：

STANDARDIZED PRECIPITATION INDEX; CHANGE IMPACTS; FREQUENCY-ANALYSIS; RIVER-BASIN; POTENTIAL DROUGHT; NEURAL-NETWORK; SEVERITY; CHINA; SPI; VULNERABILITY;

D O I：

10.1155/2016/1879024

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Drought has become one of the most important elements for water resources planning and management in Korea. The objective of this study is to estimate the spatial distribution of drought and change in the drought characteristics over time due to climate change. For the spatial characterization of drought, the standardized precipitation index (SPI) is calculated from the 45 observatories in Korea and the spatial distribution is also estimated based on the joint probability analysis using the copula method. To analyze the effect of climate change, spatial distribution of drought in the future is analyzed using the SPI time series calculated from Representative Concentration Pathways (RCPs) scenarios and HADGEM3-RA regional climate model. The results show that the Youngsan River and the northwest of Nakdong River basins in Korea have nearly doubled drought amount compared to the present and are most vulnerable to drought in near future (2016 to 2039 years).

引用

页数：13

共 92 条

[1]

Adlouni S. E., 2009, WATER RESOURCES RES, V45

[2]

[Anonymous], 1967, J HYDROL, DOI DOI 10.1016/0022-1694(69)90110-3

[3]

[Anonymous], 2014, IPCC 5 REP

[4]

[Anonymous], J GEOPHYS RES

[5]

[Anonymous], 2000, DROUGHT GLOBAL ASSES

[6]

[Anonymous], 2013, IPCC AR5 WG1, P21

[7]

Ashkani J., 2007, Journal of Agricultural Science and Technology, V9, P267

[8] Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models [J].

Belayneh, A. ;

Adamowski, J. ;

Khalil, B. ;

Ozga-Zielinski, B. .

JOURNAL OF HYDROLOGY, 2014, 508 :418-429

[9] Changes in European drought characteristics projected by the PRUDENCE regional climate models [J].

Blenkinsop, S. ;

Fowler, H. J. .

INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2007, 27 (12) :1595-1610

[10] Assessing water resource system vulnerability to unprecedented hydrological drought using copulas to characterize drought duration and deficit [J].

Borgomeo, Edoardo ;

Pflug, Georg ;

Hall, Jim W. ;

Hochrainer-Stigler, Stefan .

WATER RESOURCES RESEARCH, 2015, 51 (11) :8927-8948

← 1 2 3 4 5 6 7 8 9 10 →