Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area and Data
2.2. Marginal Distributions and Copulas
2.3. Return Period in a Bivariate Framework
2.4. Kendall Return Period
3. Results
3.1. Drought Characteristics across South Korea during 1980–2015
3.2. Marginal Probability Distributions of Drought Duration and Severity
3.3. Application of Bivariate Copulas
3.4. Spatial Distribution of the Bivariate Return Period
3.5. Comparison of Return Periods Using Identified Drought Events
4. Conclusions
- (1)
- Drought characteristics on the basis of SPI indicate that due to the unusual precipitation pattern in the southwest coastal areas, Jecheon station faced the drought of longest duration and greater severity among 55 stations across South Korea.
- (2)
- Based on the KS test, RMSE and graphical comparison applied to 55 stations, four models (exp, wei, gpa and pe3) were best fitted for drought duration and seven models (wei, ln3, gpa, gno, glo, exp, and pe3) for drought severity. Pe3 is the most common model existing in both drought duration and severity. Based on Sn, AIC and the probability-probability plot, the choice of copula varies from station to station. In addition, the Frank copula is the most common best fitted copula among 55 stations. It is concluded that several different measures are necessary to identify the best fit marginal distributions and copulas. Since different measures reflect different characteristics of marginal distributions and copulas, a single measure may lead to under- or over-estimation of the probability of drought.
- (3)
- The properties of the spatial distributions of , and are the same. However, showed droughts of longer durations and higher severities compared to and droughts of shorter durations and lower severities compared to . The spatial distribution of the joint return period indicates that the southwestern coast of South Korea and surrounding areas of Uljin have a high risk of drought, while the northwestern portion and surrounding areas of Yeongju, Uiseong, Boeun and Daejeon stations have a relatively low risk of drought. The results indicate the serious challenge in the water resource management and human mitigation of drought hazards in the southwestern coast due to abrupt changes in the precipitation pattern. In order to cope with drought hazards, accurate hydrological regulations of reservoirs in the southwest coast is necessary.
- (4)
- The comparison of univariate and bivariate return periods using the top twenty drought events showed, as can be noticed from Table 7, that the secondary return period is always larger than the and shorter than . It is also concluded that the Kendall return period and primary return periods cannot be interchanged, as their applicability changes according to the type of drought risk considered.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Copulas | Bivariate Copula | Parameters |
---|---|---|
Archimedean copulas | ||
Clayton | ||
Frank | ||
Gumbel | ||
Joe | ||
Elliptical copulas | ||
Student’s t | where | |
Gaussian |
Distribution | CDF | Parameters |
---|---|---|
Exponential (exp) | , | |
Gamma (gam) | , | |
Generalized extreme value (gev) | , , | |
Generalized logistic (glo) | , , | |
generalized normal (gno) | , , | |
Generalized Pareto (gpa) | , , | |
Gumbel (gum) | , | |
Lognormal (ln3) | , , | |
Pearson Type 3 (pe3) | , | |
Weibull (wei) | , |
Station | Drought Events | M.D | M.S | Mx | Station | Drought Events | M.D | M.S | Mx |
---|---|---|---|---|---|---|---|---|---|
Sokcho | 29 | 2.31 | 3.37 | 9 | Ganghwa | 24 | 2.17 | 3.51 | 11 |
Daegwallyeong | 28 | 2.36 | 3.31 | 9 | Yangpyeong | 28 | 2.46 | 3.65 | 9 |
Chuncheon | 31 | 2.29 | 3.35 | 8 | Icheon | 21 | 2.90 | 4.66 | 7 |
Gangneung | 29 | 2.45 | 3.55 | 7 | Inje | 24 | 2.96 | 4.33 | 8 |
Seoul | 24 | 2.79 | 4.18 | 10 | Jecheon | 23 | 3.43 | 5.14 | 13 |
Incheon | 32 | 2.19 | 3.16 | 10 | Boeun | 29 | 2.31 | 3.43 | 8 |
Wonju | 24 | 2.50 | 4.08 | 8 | Cheonan | 28 | 2.32 | 3.50 | 7 |
Suwon | 26 | 2.38 | 3.63 | 7 | Boryeong | 29 | 2.69 | 4.12 | 7 |
Chungju | 27 | 2.59 | 3.90 | 7 | Buyeo | 30 | 2.37 | 3.46 | 8 |
Seosan | 28 | 2.61 | 3.82 | 6 | Geumsan | 30 | 2.77 | 4.11 | 8 |
Uljin | 25 | 2.92 | 4.16 | 6 | Buan | 30 | 2.70 | 3.98 | 10 |
Cheongju | 27 | 2.52 | 3.99 | 7 | Imsil | 26 | 2.85 | 4.54 | 9 |
Daejeon | 31 | 2.26 | 3.40 | 7 | Jeongeup | 30 | 2.63 | 3.83 | 9 |
Chupungnyeong | 28 | 2.57 | 3.90 | 9 | Namwon | 25 | 2.80 | 4.57 | 9 |
Pohang | 16 | 2.06 | 2.85 | 6 | Jangheung | 23 | 3.35 | 5.03 | 8 |
Gunsan | 25 | 2.68 | 4.14 | 9 | Haenam | 26 | 2.58 | 3.84 | 8 |
Daegu | 29 | 2.17 | 3.52 | 7 | Goheung | 21 | 3.29 | 5.12 | 9 |
Jeonju | 28 | 2.64 | 4.21 | 8 | Yeongju | 29 | 2.38 | 3.68 | 12 |
Ulsan | 27 | 2.52 | 3.80 | 8 | Mungyeong | 27 | 2.44 | 3.79 | 10 |
Gwangju | 26 | 2.58 | 4.06 | 8 | Yeongdeok | 24 | 2.83 | 4.20 | 9 |
Busan | 31 | 2.00 | 2.95 | 7 | Uiseong | 29 | 2.00 | 3.33 | 8 |
Tongyeong | 33 | 1.97 | 2.78 | 7 | Gumi | 24 | 3.17 | 4.74 | 9 |
Mokpo | 20 | 2.80 | 4.65 | 8 | Yeongcheon | 24 | 2.58 | 4.07 | 8 |
Yeosu | 30 | 2.53 | 3.73 | 8 | Geochang | 24 | 2.88 | 4.65 | 10 |
Wando | 21 | 3.05 | 4.69 | 9 | Miryang | 27 | 2.93 | 4.35 | 10 |
Suncheon | 27 | 2.56 | 3.92 | 10 | Sancheong | 21 | 3.00 | 4.97 | 9 |
Jinju | 28 | 2.61 | 4.01 | 9 | Geoje | 24 | 2.67 | 3.89 | 7 |
Namhae | 24 | 2.63 | 4.19 | 8 | |||||
Average | 2.60 | 3.96 | 8.40 |
Drought Duration | Drought Severity | |||||||
---|---|---|---|---|---|---|---|---|
Distribution | Parameters | RMSE | KS Test | Parameters | RMSE | KS Test | ||
Statistic | p-Value | Statistic | p-Value | |||||
exp | ξ = 0.04 | 0.173 | 0.247 | 0.121 | ξ = −0.21 | 0.082 | 0.208 | 0.274 |
α = 3.40 | α = 5.33 | |||||||
gam | α = 1.03 | 0.174 | 0.247 | 0.122 | α = 0.90 | 0.079 | 0.205 | 0.287 |
β = 3.34 | β = 5.70 | |||||||
gev | ξ = 1.70 | 0.212 | 0.290 | 0.042 | ξ = 2.49 | 0.098 | 0.192 | 0.367 |
α = 1.51 | α = 2.72 | |||||||
κ = −0.37 | κ = −0.29 | |||||||
glo | ξ = 2.33 | 0.215 | 0.292 | 0.040 | ξ = 3.61 | 0.104 | 0.202 | 0.305 |
α = 1.22 | α = 2.11 | |||||||
κ = −0.43 | κ = −0.37 | |||||||
gno | ξ = 2.22 | 0.200 | 0.275 | 0.061 | ξ = 3.45 | 0.090 | 0.176 | 0.407 |
α = 2.10 | α = 3.66 | |||||||
κ = −0.93 | κ = −0.08 | |||||||
gpa | ξ = 0.39 | 0.189 | 0.259 | 0.091 | ξ = −0.01 | 0.080 | 0.195 | 0.346 |
α = 2.42 | α = 4.73 | |||||||
κ = −0.21 | κ = −0.07 | |||||||
gum | ξ = 2.02 | 0.202 | 0.259 | 0.092 | ξ = 2.90 | 0.110 | 0.205 | 0.289 |
α = 2.45 | α = 3.84 | |||||||
ln3 | ζ = −0.05 | 0.200 | 0.275 | 0.061 | ζ = −1.24 | 0.090 | 0.202 | 0.305 |
µ = 0.82 | µ = 1.55 | |||||||
σ = 0.93 | σ = 0.78 | |||||||
pe3 | ξ = 2.43 | 0.170 | 0.244 | 0.129 | ξ = 5.12 | 0.077 | 0.176 | 0.472 |
β = 3.67 | β = 5.47 | |||||||
α = 2.61 | α = 2.22 | |||||||
wei | ζ = −0.54 | 0.179 | 0.246 | 0.123 | ζ = −0.11 | 0.078 | 0.199 | 0.324 |
β = 2.52 | β = 2.52 | |||||||
δ = 0.78 | δ = 0.78 |
Copula | Sn | p-Value | AIC | θ |
---|---|---|---|---|
Student’s t | 0.023 | 0.203 | 69.989 | 0.989 |
Normal | 0.030 | 0.035 | 84.973 | 0.989 |
Clayton | 0.033 | 0.124 | 86.223 | 11.024 |
Gumbel | 0.022 | 0.391 | 68.996 | 8.872 |
Frank | 0.031 | 0.054 | 80.005 | 38.072 |
Joe | 0.024 | 0.104 | 79.259 | 11.493 |
Station | Correlation | p-Value | Station | Correlation | p-Value |
---|---|---|---|---|---|
Sokcho | 0.984 | 9.5 × 10−22 | Ganghwa | 0.988 | 2.9 × 10−19 |
Daegwallyeong | 0.979 | 1.2 × 10−19 | Yangpyeong | 0.978 | 3.0 × 10−19 |
Chuncheon | 0.973 | 4.5 × 10−20 | Icheon | 0.968 | 6.5 × 10−13 |
Gangneung | 0.981 | 1.0 × 10−20 | Inje | 0.995 | 4.6 × 10−23 |
Seoul | 0.994 | 2.6 × 10−22 | Jecheon | 0.977 | 1.2 × 10−15 |
Incheon | 0.961 | 2.7 × 10−18 | Boeun | 0.983 | 1.4 × 10−21 |
Wonju | 0.987 | 7.2 × 10−19 | Cheonan | 0.966 | 8.3 × 10−17 |
Suwon | 0.946 | 2.9 × 10−13 | Boryeong | 0.970 | 4.6 × 10−18 |
Chungju | 0.983 | 4.8 × 10−20 | Buyeo | 0.975 | 6.5 × 10−20 |
Seosan | 0.971 | 1.0 × 10−17 | Geumsan | 0.977 | 2.4 × 10−20 |
Uljin | 0.976 | 1.0 × 10−16 | Buan | 0.987 | 6.2 × 10−24 |
Cheongju | 0.965 | 4.4 × 10−16 | Imsil | 0.974 | 4.8 × 10−17 |
Daejeon | 0.974 | 3.2 × 10−20 | Jeongeup | 0.988 | 3.1 × 10−24 |
Chupungnyeong | 0.972 | 5.9 × 10−18 | Namwon | 0.985 | 4.3 × 10−19 |
Pohang | 0.985 | 5.4 × 10−12 | Jangheung | 0.965 | 1.0 × 10−13 |
Gunsan | 0.985 | 6.3 × 10−19 | Haenam | 0.975 | 3.4 × 10−17 |
Daegu | 0.971 | 3.1 × 10−18 | Goheung | 0.966 | 1.3 × 10−12 |
Jeonju | 0.968 | 4.1 × 10−17 | Yeongju | 0.991 | 4.9 × 10−25 |
Ulsan | 0.972 | 3.2 × 10−17 | Mungyeong | 0.985 | 9.6 × 10−21 |
Gwangju | 0.976 | 2.6 × 10−17 | Yeongdeok | 0.989 | 7.5 × 10−20 |
Busan | 0.980 | 9.6 × 10−22 | Uiseong | 0.988 | 2.9 × 10−23 |
Tongyeong | 0.981 | 3.1 × 10−24 | Gumi | 0.990 | 2.6 × 10−20 |
Mokpo | 0.985 | 2.7 × 10−15 | Yeongcheon | 0.970 | 5.7 × 10−15 |
Yeosu | 0.971 | 7.3 × 10−19 | Geochang | 0.972 | 2.4 × 10−15 |
Wando | 0.982 | 3.4 × 10−15 | Miryang | 0.990 | 6.6 × 10−23 |
Suncheon | 0.988 | 1.3 × 10−21 | Sancheong | 0.968 | 7.6 × 10−13 |
Jinju | 0.977 | 6.1 × 10−19 | Geoje | 0.966 | 2.2 × 10−14 |
Namhae | 0.986 | 1.4 × 10−18 |
# 1 | Station | Date | D 1 | S 1 | 1 | 1 | 1 | 1 | 1 |
---|---|---|---|---|---|---|---|---|---|
1 | Jecheon | April 2008~April 2009 | 13 | 16.04 | 33.53 | 19.79 | 34.81 | 19.39 | 22.22 |
2 | Yeongju | March 1982~February 1983 | 12 | 22.30 | 62.65 | 68.10 | 78.27 | 55.96 | 69.51 |
3 | Ganghwa | March 2014~January 2015 | 11 | 20.01 | 41.55 | 48.56 | 63.49 | 34.59 | 45.89 |
4 | Geochang | July 2008~April 2009 | 10 | 21.50 | 44.58 | 57.40 | 165.38 | 29.58 | 86.51 |
5 | Suncheon | April 1988~January 1989 | 10 | 16.98 | 21.41 | 17.41 | 23.18 | 16.39 | 18.79 |
6 | Miryang | April 1988~January 1989 | 10 | 16.46 | 27.63 | 29.91 | 62.36 | 18.66 | 44.06 |
7 | Mungyeong | March 1982~December 1982 | 10 | 16.15 | 35.96 | 35.99 | 44.37 | 30.25 | 39.46 |
8 | Buan | April 1988~January 1989 | 10 | 16.00 | 60.95 | 44.97 | 370.57 | 27.82 | 194.56 |
9 | Seoul | March 2014~December 2014 | 10 | 15.44 | 29.42 | 25.48 | 57.26 | 17.93 | 40.12 |
10 | Incheon | March 2014~December 2014 | 10 | 12.94 | 51.67 | 31.50 | 149.37 | 22.52 | 79.45 |
11 | Namwon | May 1994~January 1995 | 9 | 20.55 | 27.05 | 37.45 | 134.63 | 17.78 | 79.61 |
12 | Jinju | June 1994~February 1995 | 9 | 17.61 | 31.02 | 39.77 | 96.66 | 21.26 | 63.71 |
13 | Imsil | April 1995~December 1995 | 9 | 17.41 | 25.26 | 28.63 | 33.81 | 22.25 | 26.45 |
14 | Daegwallyeong | April 2015~December 2015 | 9 | 16.16 | 35.70 | 46.99 | 54.69 | 32.25 | 45.52 |
15 | Chupungnyeong | March 1982~November 1982 | 9 | 15.54 | 26.49 | 38.04 | 96.25 | 18.64 | 63.54 |
16 | Wando | June 1995~February 1996 | 9 | 14.86 | 34.48 | 26.83 | 34.90 | 26.58 | 31.56 |
17 | Sokcho | February 2015~October 2015 | 9 | 14.71 | 32.96 | 34.95 | 67.56 | 22.65 | 39.47 |
18 | Jeongeup | April 1994~December 1994 | 9 | 14.58 | 31.99 | 31.82 | 56.82 | 22.18 | 42.01 |
19 | Yangpyeong | April 2000~December 2000 | 9 | 13.88 | 31.44 | 26.94 | 121.26 | 16.48 | 61.29 |
20 | Gunsan | May 1988~January 1989 | 9 | 13.25 | 28.99 | 23.06 | 29.60 | 22.69 | 25.91 |
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Maeng, S.J.; Azam, M.; Kim, H.S.; Hwang, J.H. Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea. Water 2017, 9, 679. https://doi.org/10.3390/w9090679
Maeng SJ, Azam M, Kim HS, Hwang JH. Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea. Water. 2017; 9(9):679. https://doi.org/10.3390/w9090679
Chicago/Turabian StyleMaeng, Seung Jin, Muhammad Azam, Hyung San Kim, and Ju Ha Hwang. 2017. "Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea" Water 9, no. 9: 679. https://doi.org/10.3390/w9090679
APA StyleMaeng, S. J., Azam, M., Kim, H. S., & Hwang, J. H. (2017). Analysis of Changes in Spatio-Temporal Patterns of Drought across South Korea. Water, 9(9), 679. https://doi.org/10.3390/w9090679