• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.863-875
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• 2017

In this study, the effects of potential evapotranspiration method on drought index results were evaluated using SC-PDSI. Monthly heat index method, Penman-Monteith method, and Hargreaves equation were used as potential evapotranspiration method. SC-PDSI was calculated using three potential evapotranspiration method at 56 stations and compared the results. As a result, it was confirmed that the results by Penman-Monteith method and Hargreaves equation showed similar SC-PDSI calculation results without much difference, and the result by monthly heat index method showed a relatively large difference. It was confirmed that the results of SC-PDSI and drought situation judgment for the period of spring and winter season showed a big difference by the month. In conclusion, when calculating PDSI in Korea, using Penman-Monteith method and Hargreaves equation will be able to express the drought situation well.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.813-824
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• 2014

In this study, drought of North Korea are analyzed using drought index. 27 weather stations are selected and monthly precipitation and average temperature data are collected for drought analysis. SC-PDSI is used for drought analysis and calculated using collected weather data during 1984~2013 (30 years) in 27 weather stations. From the analysis result of historical drought event using drought index, it is confirmed that severe droughts occurred in the early and mid 2000's at most stations. Secondly, drought frequency analysis was carried out for the derivation of drought severity-duration-frequency (SDF) curves to enable quantitative evaluations of past historical droughts having been occurred in 6 stations (Pyeongyang, Hamheung, Cheongjin, Wonsan, Haeju, Sinuiju). This study can suggest return periods for historical major drought events by using derived SDF curves for each station. In the result, drought events in the early and mid 2000's had return periods of 20~50 years.

• Water for future
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• v.46 no.5
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• pp.108-114
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• 2013

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.417-418
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• 2018

미국 국립가뭄경감센터 (National Drought Mitigation Center, NDMC)는 다양한 가뭄지수를 통합하여 미국 전역의 가뭄진행상황을 모니터링하고 가뭄대응정책 수립을 위한 주요 의사결정정보로 활용하고 있다. 대표적으로 1999년에 개발되어 현재까지 운영 중인 미국가뭄모니터 (United States Drought Monitor, USDM)는 미국 전역에 대하여 가뭄단계를 표시한 지도 (U.S. Drought Monitor map)를 매주 생성하여 제공하고 있다 (http://droughtmonitor.unl.edu/). 가뭄지표(drought index)는 가뭄의 현황과 시공간적인 전개 과정을 분석하고 정량적 가뭄심도 평가 및 가뭄대응계획 수립을 위한 도구로써 다양하게 개발되어 활용되고 있다. 가뭄의 정도를 정량화하기 위하여 개발된 다수의 가뭄지수는 대상과 평가방법에 따라 가뭄을 표현하는 특성이 서로 다르다. 하나의 가뭄지수로는 가뭄특성을 온전히 표현하기 어렵기 때문에, 최근에는 단일 가뭄지수에 의존하기 보다는 다수의 가뭄지수를 이용하되, 여러 가뭄지수 간의 특징을 고려하여 각 가뭄지수가 갖는 장단점을 상호 보완하여 사용하기를 권고하고 있다. USDM은 파머가뭄심도지수 (Palmer Drought Severity Index, PDSI), Soil Moisture Model (NOAA Climate Prediction Center, CPC), 미 지리조사국의 하천유량 주간보고 (USGS Weekly Streamflow), 표준강수지수 (Standardized Precipitation Index, SPI) 등의 주요 가뭄판단지표를 선정하고, 가뭄판단의 기준으로써 각 가뭄지수의 가뭄심도 (drought severity) 및 백분위수 (percentiles)로 등급을 구분하였다. 가뭄등급은 '정상 상태 (none)'를 포함하여 '비정상적인 건조 (abnormally dry, D0)'에서 최악의 가뭄상태를 의미하는 '이례적인 가뭄상태 (exceptional, D4)'에 이르는 6 단계로 구분하고, 정상상태를 제외한 5 단계의 통합가뭄단계로 표시한다. 우리나라에서는 기상청, 수자원공사, 농어촌공사에서 기상/수문/농업관련 가뭄지수의 위험지도를 실시간으로 제공하고 있으며, 각 지표별로 상이한 기준으로 가뭄을 판단하고 있다. 각각의 가뭄지표에 대한 가뭄판단기준은 해당 국가의 장기적으로 축적된 자료를 활용하여 가뭄단계 및 가뭄판단기준의 재설정에 대한 연구가 필요하다. 본 연구에서는 SPI, SC-PDSI, 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI), Evaporative Demand Drought Index (EDDI), 유효가뭄지수 (Effectvie Drought Index, EDI)의 다양한 가뭄지수를 활용하여 USDM의 가뭄심도 및 가뭄판단기준을 적용하고자한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.31-44
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• 2019

The main objective of this research is to develop a hydroclimate drought index (HCDI) using the gridded climate data inputs in a Variable Infiltration Capacity (VIC) modeling platform. Typical drought indices, including, Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), and Self-calibrated Palmer Drought Severity Index (SC-PDSI) in South Korea are also used and compared. Inverse Distance Weighting (IDW) method is applied to create the gridded climate data from 56 ground weather stations using topographic information between weather stations and the respective grid cell ($12km{\times}12km$). R statistical software packages are used to visualize HCDI in Google Earth. Skill score (SS) are computed to evaluate the drought predictability based on water information derived from the observed reservoir storage and the ground weather stations. The study indicates that the proposed HCDI with the gridded climate data input is promising in the sense that it can help us to predict potential drought extents and to mitigate its impacts in a changing climate. The longer term drought prediction (e.g., 9 and 12 month) capability, in particular, shows higher SS so that it can be used for climate-driven future droughts.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.1-9
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• 2015

The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.