• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.2
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• pp.14-26
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• 2016

This study analyzed the correlation between the standardized precipitation index(SPI) and forest fire occurrences using monthly accumulative rainfall data since 1970 and regional fire occurrence data since 1991. To understand the relationship between the SPI and forest fire occurrences, the correlations among the SPI of nine main observatory weather stations including Seoul, number of fire occurrences, and log of fire occurrences were analyzed. We analyzed the correlation of SPI with fire occurrences in the 1990s and 2000s and found that in the 1990s, the SPI of 3 months showed high correlation in Gyeonggi, Gangwon, and Chungnam, while the SPI of 6 months showed high correlation in Chungbuk, and the SPI of 12 months showed high correlation in Gyeongnam, Gyenongbuk, Jeonnam, and Jeonbuk. In the 2000s, the SPI of 6 months showed high correlation with the fire frequency in Gyeonggi, Chungnam, Chungbuk, Jeonnam, and Jeonbuk, whereas the fire frequency in western Gangwon was highly correlated with the SPI of 3 months and, in eastern Gangwon, Gyeongnam, and Gyenongbuk, with the SPI of 1 month. In the 1990s, distinct differences in the drought condition between the SPI of 3 months and 12 months in the northern and southern regions of Korean Peninsula were found, whereas the differences in both the SPI of 1 month and 6 months were found in the Baekdudaegan region except western Gangwon since the 2000s. Therefore, this study suggests that we can develop a model to predict forest fire occurrences by applying the SPI of 1-month and 6-month data in the future.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• 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 Korea Water Resources Association
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• v.45 no.4
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• pp.409-418
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• 2012

A modified standardized precipitation index was developed by considering the length of dry period and surface run-off effect. The official reports and newspapers on drought from 1973 to 2009 were quantified to evaluate drought indices. The developed index was evaluated using the receiver operating characteristic analysis. In order to suggest improved drought index, we cut the precipitation amount that may do not contribute the mitigation of drought and weight dry period by considering cumulative distribution, decile distribution of dry periods. Drought detection capability of the suggested index has improved by weighting of dry period effects and considering precipitation amounts contributing drought mitigation.

• Journal of Korea Water Resources Association
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• v.37 no.7
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• pp.553-567
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• 2004

This study proposes a modified standardized precipitation index (MSPI) which was developed to make up for the weakness of the SPI. Both MSPI and SPI are applied to the monthly rainfall at the Seoul station for the drought analysis. The MSPI proposed is nothing but the SPI for the normalized monthly rainfall, that is, an extra step for normalizing the monthly rainfall is included before driving the SPI. Thus, the MSPI has a structure to transfer the relative amount of rainfall to the next months, but the SPI the absolute amount of rainfall. The monthly rainfall data at the Seoul station used in this study are those collected from 1777 to 1996. The rainfall data collected before and after the long dry period around 1900 were also analyzed separately for the comparison. The results derived are as follows. (1) The MSPI was found to be more practical compared to the SPI. This was assured by comparing the analysis results of the data including and excluding the long dry period around 1900. (2) The MSPI is found to be less sensitive than the SPI to the extreme rainfall events. For the MSPI, the occurrence probabilities of moderate drought before and after the long dry period are similar, but those for the extreme drought becomes slightly decreased after the long dry period (from about 18 years of return period before the long dry period to the 16 years after the long dry period). However, the duration becomes longer after the long dry period (the duration for the extreme drought has been increased from 2 to 2.5 months after the long dry period). This results can also be compared with a rather unreasonable result derived by applying the SPI (for the extreme drought the return period has been decreased to be from 25 to 10 years after the long dry period, on the other hand the duration has been increased from 1.5 months to 3.5 months). So, we man conclude that the MSPI is more practical for the drought analysis that the SPI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.175-185
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• 2023

As drought risk increases due to climate change, various research works are underway around the world to respond to drought so as to minimize drought damage. In particular, in recent years, many studies are focused on analyzing regional patterns of drought in a comprehensive manner, however there is still insufficient to quantitatively identify drought-risk areas in a large river basin considering climate change in Korea. In this study, we calculated the Standardized Precipitation Index (SPI) and the Modified Standardized Precipitation Index (M_SPI) as representative meteorological drought index, and performed spatial autocorrelation analysis to identify the drought hotspot region under climate change scenarios of Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The SPI was calculated by estimating parameters for each observation station within the study area, whereas the M_SPI was calculated by estimating parameters for the entire study area. It is more reasonable to use the M_SPI for assessing meteorological drought from an overall perspective within the study area. When the M_SPI was used, long-term droughts showed drought hotspot areas clearly larger than short-term droughts. In addition, the drought hotspot area moved from the center of the Nakdong River basin to the Seomjin River basin over time. Especially, the moving patterns of the short-term/long-term drought were apparent under the RCP 4.5, whereas the moving patterns of the long-term drought were distinct under the RCP 8.5 scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.23-23
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• 2015

가뭄은 홍수와 더불어 매우 심각한 자연재해이며, 그 특성상 광역적이고 장기간 발생함에 따라 구체적인 발생시점, 규모, 범위 등을 규명하기가 어렵다. 그동안 가뭄관리 기관에서는 가뭄의 특성을 규명하고자 가뭄 지수를 활용하여 발생시점, 발생빈도, 피해규모, 범위 등을 정량적으로 분석해 왔다. 그러나 가뭄특성은 가뭄 지수의 해석방법 및 판단기준에 따라 다르게 나타나는 문제가 있다. 또한, 대부분 가뭄지수가 단일 기상(강수, 기온 등) 및 수문(유출량, 토양수분량, 증발산량 등)정보 기반으로 산정됨에 따라 대상지역의 가뭄특성을 적절히 고려하지 못하고 있다. 따라서 지역적 가뭄특성을 명확히 나타내기 위해서는 단일변수 기반의 가뭄지수의 활용보다는 두 개 이상의 변수가 고려된 가뭄지수를 활용하는 방안이 필요하다. 본 연구에서는 강수량 및 토양수분량 기반의 이변량 결합가뭄지수(Bivariate Joint Drought Index, BJDI)를 산정하고 기존 단일변수(강수량, 토양수분량)에 의한 가뭄지수와 함께 지역별 가뭄특성을 분석하였다. 이를 위해 강수량은 1977~2012년 동안의 기상청 관할 59개 기상관측소 자료, 토양수분량은 지표수문해석모형으로 부터 산정한 결과를 이용하였다. 59개 지점에 대한 SPI (Standardized Precipitation Index), SSI(Standardized Precipitation Index) 및 BJDI를 산정하였다. 또한, 지점별, 가뭄지수별 빈도해석을 통해 재현기간을 산정하고 과거 가뭄피해사례를 바탕으로 가뭄특성을 정량적으로 비교 및 분석하였다. 그 결과, 재현기간은 동일한 심도일지라도 SPI, SSI, BJDI 순으로 BJDI가 가장 낮게 나타났으며, 지역별로는 중부지역이 높고, 남부지역에서는 낮게 산정되었다.

• Journal of Ecology and Environment
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• v.35 no.4
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• pp.323-329
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• 2012

The Standardized Precipitation Index (SPI) is a widely used drought index to provide good estimations of the intensity, magnitude and spatial extent of droughts. The objective of this study was to analyze the spatial pattern of drought by SPI index. In this paper, the patterns of drought hazard in Iran are evaluated according to the data of 40 weather stations during 1967-2009. The influenced zone of each station was specified by the Thiessen method. It was attempted to make a new model of drought hazard using GIS. Three criteria for drought were studied and considered to define areas of vulnerability. Drought hazard criteria used in the present model included: maximum severity of drought in the period, trend of drought, and the maximum number of sequential arid years. Each of the vulnerability indicators were mapped and these as well as a final hazard map were classified into 5 hazard classes of drought: one, slight, moderate, severe and very severe. The final drought vulnerability map was prepared by overlaying three criteria maps in a GIS, and the final hazard classes were defined on the basis of hazard scores, which were determined according to the means of the main indicators. The final vulnerability map shows that severe hazard areas (43% of the country) which are observed in the west and eastern parts of country are much more widespread than areas under other hazard classes. Overall, approximately half of the country was determined to be under severe and very severe hazard classes for drought.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.735-742
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• 2019

Drought is a social phenomenon in which the degree of perception varies depending on the affected factors, and is defined as various relative concepts such as meteorological drought, hydrological drought, agricultural drought, and climatological drought. In this study, a comparative analysis of meteorological drought among variously defined droughts was conducted and the applicability of the drought index was examined by comparing the actual drought cases and the results of meteorological drought index analysis. In order to compare the drought index, we used standardized Precipitation Index (SPI), China-Z Index (CZI), Modified CZI (MCZI) and Z-Score Index Respectively. Four drought indices were used for the Taebaek and Sokcho areas. The drought index was analyzed using the meteorological data from 1986 to 2015 for a duration of 3 months. As a result of the analysis, the SPI drought index was analyzed to be highly reproducible for the case of drought with past limited water series. In the case of CZI and MCZI drought indices, the number of extreme dry occurrences is similar to that of the past cases, but the reproducibility is low for the actual drought years. In the case of ZSI drought index, it is analyzed that the number of occurrences and the comparison with the past cases are inferior in reproducibility. For the meteorological drought index using precipitation, it would be effective to use the SPI drought index with the highest reproducibility and the past drought case.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.4
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• pp.73-82
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• 2018

In this study, we assessed meteorological and agricultural drought based on the SPI(Standardized Precipitation Index), SMP(Soil Moisture Percentile), and SMDI(Soil Moisture Deficit Index) indices using satellite-based TRMM(Tropical Rainfall Measuring Mission)/GPM(Global Precipitation Measurement) images at the province of Chungcheongbuk-do. The long-term(2000-2015) TRMM/GPM precipitation data were used to estimate the SPI values. Then, we estimated the spatially-/temporally-distributed soil moisture values based on the near-surface soil moisture data assimilation scheme using the TRMM/GPM and MODIS(MODerate resolution Imaging Spectroradiometer) images. Overall, the SPI value was significantly affected by the precipitation at the study region, while both the precipitation and land surface condition have influences on the SMP and SMDI values. But the SMP index showed the relatively extreme wet/dry conditions compared to SPI and SMDI, because SMP only calculates the percentage of current wetness condition without considering the impacts of past wetness condition. Considering that different drought indices have their own advantages and disadvantages, the SMDI index could be useful for evaluating agricultural drought and establishing efficient water management plans.