• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.65-73
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• 2017

This study analyzed the peak drought severity and drought duration of the Cheongmicheon watershed from 1985 to 2015 to assess the lag time of peak drought severity between several drought indices. Standardized Precipitation Index (SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index (SPEI) based on precipitation and evapotranspiration were applied as meteorological drought indices. Streamflow Drought Index (SDI) based on runoff data was applied as hydrological drought index. In case of SDI, we used Soil and Water Assessment Tool (SWAT) model for simulation of daily runoff data. As a result, the time of peak drought severity of SDI occurred after the occurrence of SPI and SPEI. The lag time for the peak drought severity, on average, between SDI and SPI was 0.59 months while SDI and SPEI was 0.79 months. As compared with SDI, the maximum delay was 2 months for both SPI and SPEI. This study results also shows that even though the rainfall events were able to cope with meteorological droughts, they were not always available to solve the hydrological droughts in the same time.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.65-74
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• 2017

North Korea is one of the high vulnerable countries facing the threat of natural disaster and has experienced more frequent disasters in recent years. These disasters have significantly led to food shortages and large reductions in crop yields. In 2015, both North Korean officials and international agencies had identified the extreme drought event, the worst in one hundred years according to the North Korean government. The objective of this study was an assessment of the extreme drought events in 2014~2015, and to apply climatic drought indices for drought monitoring in North Korea. Characteristics of the extreme drought in North Korea are examined by using the weekly-based Standardized Precipitation Evapotranspiration Index (SPEI). The drought characteristics illustrated by the SPEI results are compared with a Standardized Precipitation Index (SPI) results and drought impact information to understand how these indices can explain the drought conditions within the country. These results demonstrated that the SPEI could be an effective tool to provide improved spatial and temporal drought conditions to inform management decisions for drought policy.

• Journal of the Korean earth science society
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• v.27 no.7
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• pp.804-815
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• 2006

Meteorologists define a drought as a period of common dry weather. This may sound straightforward, but it is not so in reality. In this study, we attempted to identify meteorological drought conditions over South Korea. To evaluate the temporal and spatial variability of drought, we calculated two commonly used drought indices, the percent of normal precipitation (PNP) and the Palmer drought severity index (PDSI) calculated from fifty-eight meteorological stations below the Korean Meteorological Administration (KMA). The yearly precipitation has been growing gradually, and the amplitude between maximum and minimum also grow more explicitly from 1960's. According to the analysis of percentile anomaly of monthly precipitation, major drought duration was $1927{\sim}1929,\;1937{\sim}1939,\;1942{\sim}1944,\;1967{\sim}1968,\;1976{\sim}1977,\;1982{\sim}1983,\;1988,\;and\;1994{\sim}1995$. The severe drought occurred most frequently in Mokpo, Daegu, Jeonju, Busan, and Gangneung; it tended to occur more frequently in south sector than in mid sector of Korea and in south west sector than in south east sector. According to the analysis of seasonal distribution, extreme droughts occurred frequently in winter at Seoul, Gangneung, Jeonju, Daegu, and Busan. Severe droughts in summer were formed frequently at Seoul, Gangneung, and Mokpo, while that for spring at Jeonju, Daegu, and Busan. The results of PDSI distribution for the $1994{\sim}1995$ drought period were one of the most severe and widely spreaded droughts; it occurred most frequently in the south sector of South Korea. The comparison of time series between PDSI and Normal Percent showed that they exhibit a strong compatibility for the entire study period; it implies that both drought indices are useful method to indicate drought severity.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.1-10
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• 2016

Drought is a slow-varying natural hazard that is characterized by various factors such that reliable drought forecasting along with uncertainties estimation has been a major issue. In this study, we proposed a stochastic simulation technique based scheme for providing a set of drought scenarios. More specifically, this study utilized a nonstationary Hidden markov model that allows us to include predictors such as climate state variables and global climate model's outputs. The simulated rainfall scenarios were then used to generate the well-known meteorological drought indices such as SPI, PDSI and PN for the three dam watersheds in South Korea. It was found that the proposed modeling scheme showed a capability of effectively reproducing key statistics of the observed rainfall. In addition, the simulated drought indices were generally well correlated with that of the observed.

• Korean Journal of Remote Sensing
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• v.35 no.6_3
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• pp.1285-1298
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• 2019

Drought is one of the factors that can cause wildfires. Drought is related to not only the occurrence of wildfires but also their frequency, extent and severity. In South Korea, most wildfires occur in dry seasons (i.e. spring and autumn), which are highly correlated to drought events. In this study, we examined the relationship between wildfire occurrence and drought factors, and developed satellite-based new drought indices for assessing wildfire risk over South Korea. Drought factors used in this study were high-resolution downscaled soil moisture, Normalized Different Water Index (NDWI), Normalized Multi-band Drought Index (NMDI), Normalized Different Drought Index (NDDI), Temperature Condition Index (TCI), Precipitation Condition Index (PCI) and Vegetation Condition Index (VCI). Drought indices were then proposed through weighted linear combination and one-class support vector machine (One-class SVM) using the drought factors. We found that most drought factors, in particular, soil moisture, NDWI, and PCI were linked well to wildfire occurrence. The validation results using wildfire cases in 2018 showed that all five linear combinations produced consistently good performance (> 88% in occurrence match). In particular, the combination of soil moisture and NDWI, and the combination of soil moisture, NDWI, and precipitation were found to be appropriate for representing wildfire risk.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.340-348
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• 2021

Continuous monitoring of RGB (Red, Green, Blue) vegetation indices is important to apply remote sensing technology for the estimation of crop growth. In this study, we evaluated the performance of eight vegetation indices derived from soybean RGB images with various agronomic parameters under drought stress condition. Drought stress influenced the behavior of various RGB vegetation indices related soybean canopy architecture and leaf color. In particular, reported vegetation indices such as ExGR (Excessive green index minus excess red index), Ipca (Principal Component Analysis Index), NGRDI (Normalized Green Red Difference Index), VARI (Visible Atmospherically Resistance Index), SAVI (Soil Adjusted Vegetation Index) were effective tools in obtaining canopy coverage and leaf chlorophyll content in soybean field. In addition, the RGB vegetation indices related to leaf color responded more sensitively to drought stress than those related to canopy coverage. The PLS-DA (Partial Squares-Discriminant Analysis) results showed that the separation of RGB vegetation indices was distinct by drought stress. The results, yet preliminary, display the potential of applying vegetation indices based on RGB images as a tool for monitoring crop environmental stress.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2B
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• pp.87-98
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• 2011

Recently, occurrence frequency of extreme events like flood and drought is increasing due to climate change by global warming. Especially, a drought is more severer than other hydrologic disasters because it causes continuous damage through long period. But, ironically, it is difficult to recognize the importance and seriousness of droughts because droughts occur for a long stretch of time unlike flood. So as to analyze occurrence of droughts and prepare a countermeasure, this study analyzed a meteorologic drought among many kinds of drought that it is closely related with precipitation. Palmer Drought Severity Index, Standard Precipitation and Effective Drought Index are computed using precipitation and temperature material observed by Korean Meteorological Administration. With the result of comparative analysis of computed drought indices, Effective Drought Index is selected to execute frequency analysis because it is accordant to past droughts and has advantage to compute daily indices. A Frequency analysis of Effective Drought Index was executed using boundary kernel density function. In the result of analysis, occurrence periods of spring showed about between 10 year and 20 year, it implies that droughts of spring are more frequent than other seasons. And severity and occurrence period of droughts varied in different regions as occurrence periods of the Youngnam region and the southern coast of Korea are relatively shorter than other regions.

• Journal of Korea Water Resources Association
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• v.45 no.1
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• pp.75-89
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• 2012

This study attempted to analyze statistical characteristics of historical drought of Korea through trend, periodicity and drought spell analysis by using the drought indices. Standard Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI) were calculated using weather data of 59 weather stations under Korea Meteorological Administration (KMA). As a result of analysis, SP13 and SP16 showed trend of drier spring, drier winter and wetter summer in all basin of Korea. However, SPI12 and PDSI showed different trends with shorter duration drought indices. In case of wavelet transform analysis for drought periodicities, in a band of 1~2 years or below 6 years showed significant spectrum. SP13 showed strongest power spectrum near the band of 1~2 year variance, and SPI12 and PDSI showed 6 years periodicities. The results from drought spell showed that Nakdong River Basin, Geum River Basin and Youngsan River Basin were appeared as severe drought vulnerable area of Korea.

• Water Engineering Research
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• v.2 no.2
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• pp.139-148
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• 2001

The teleconnections between El Nino/Southern Oscillation (ENSO) and droughts in Korea and the continental United States(U.S.) are investigated using cross analysis. For this purpose, monthly ENSO data and Palmer Drought Severity Index (PDSI) for Korea and for seven states in the U.S. are used. This study shows that there are significant statistical associations between ENSO indices and PDSI for Korea; however, the associations are very weak. It is found that dry conditions in Korea are positively correlated with El Nino, while wet conditions with La Nina. SOI, SSt in the Nino 4 and Ship track 6 regions among ENSO indices are more strongly correlated with PDSI than the other ENSO indices when using the original standardized data, but the SST Nino 3, SST Nino 4, and Darwin SSP exhibit abetter correlations with PDSI when using filtered data to be removed autocorrelation components of the original standardized data. The response time lag for maximum correlation between ENSO indices and PDSI appears to be affected by filtering the data. This is expecially true for Korea than for state analyzed in U.S. In addition, it is found that the PDSI in the continental U.S. is more strongly correlated wiht ENSO than in Korea. Furthermore, in analyzing the El Nino and La Nina aggregate composite data, it is found that the dry anomalies in Korea occur from the year following El Nino to about tow years after while the wet anomalies occur from La Nina year for a period of about two years.