• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.330-330
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• 2021

본 연구에서는 새롭게 개발 중인 SSP 시나리오의 일단위 강수량과 온도 자료를 활용하여 청미천 유역의 미래 가뭄의 예측 및 분석을 실시하였다. SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5에 따른 새롭게 개발 중인 CMIP6 (Coupled Model Intercomparison Project) GCM (General Circulation Models) 중 ACCESS-ESM1.5(Australian Community Climate and Earth System Simulator model)를 이용하였다. GCM 자료는 Quantile Mapping 방법을 사용하여 편이보정 되었고, 유출분석은 SWAT(Soil and Water Assessment Tool) 모형을 사용하여 청미천 유역에 대해 수행하였다. 청미천 유역의 가뭄분석을 위해 기상학적 가뭄지수인 SPI(Standardized Precipitation Index)와 SPEI(Standardized Precipitation Evapotranspiration Index), 수문학적 가뭄지수인 SDI(Standardized Streamflow Index)를 산정하였다. 그 후, 시간에 따른 가뭄의 특성을 분석하기 위해 가까운 미래 (2025-2064)와 먼 미래 (2065-2100) 로 구분하여 분석을 진행하였다. 그 결과, 청미천 유역의 가뭄 발생은 SSP시나리오, 가뭄지수에 따라 차이점을 확인할 수 있었다. SSP 시나리오의 경우 SSP5-8.5에서 가장 심각한 가뭄이 발생하였다. 가뭄지수의 경우 강수만을 고려한 SPI는 먼 미래에 비해 가까운 미래에서 더욱 심각한 가뭄이 발생하였다. SDI의 경우 강수량의 변동이 일반적으로 하천의 흐름에 영향을 미치기에 SPI와 비슷한 양상을 나타내었다. SPEI의 경우 시간에 따른 기온상승으로 먼 미래에 심각한 가뭄이 발생하였다.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.471-479
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• 2018

This study analyzed the peak time of drought severity and drought period using meteorological and hydrological drought indices. Standardized Precipitation Index (SPI) using rainfall data was used for meteorological drought and Streamflow Drought Index (SDI) and Standardized Streamflow Index (SSI) using streamflow data were used for the hydrological drought. This study was applied to the Cheongmicheon watershed which is a mixture area for rural and urban regions. The rainfall data period used in this study is 32.5 years (January of 1985~June of 2017) and the corresponding streamflow was simulated using SWAT. After the drought indices were calculated using the collected data, the characteristics of drought were analyzed by time series distribution of the calculated drought indices. Based on the results of the this study, it can be seen that hydrological drought occurs after meteorological drought. The difference between SDI and SPI peak occurrence time, difference in drought start date and average drought duration is greater than SSI and SPI. In general, SSI shows more severe than SDI. Therefore, various drought indices should be used at the identification of drought characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1209-1218
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• 2015

As the drought disasters are increased in the world, the need of study using satellite image data is on the rise. This study is conducted to analyze the drought in the region using satellite image, and to analyze the correlation with the standard precipitation index (SPI) and the actual drought cases. We selected Dongducheon and Taebaek region for domestic major drought (2001, 2008-2009). The correlation with the SPI and the observed water level data was analyzed using the $0.05^{\circ}$ spatial resolution and 8days MODIS DSI (Drought Severity Index). In Dongducheon, 6-months DSI has a correlation of 0.71 with the SPI (30). In Taebaek, the correlation between 6-months DSI and SPI (90) was a 0.40 and showed an average hit ratio of 65.7% in comparing with the observed water level of study area. In summary, this study showed a limited correlation between DSI based on satellite images and meteorological drought index SPI and confirmed the possibility of using DSI for the domestic study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1117-1123
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• 2014

Water is a necessary condition of plants, animals and human. The state of the water shortage, that drought is globally one of the most feared disasters. This study was calculated target standardized precipitation index with unit of region for judgment and preparation of drought in consideration of the regional characteristics. First of all, Standardized Precipitation Index (3) were calculated by monthly rainfall data from rainfall data more than 30 years of 88 stations. Parametric frequency and nonparametric frequency using boundary kernel density function were analysed using annual minimum data that were extracted from calculated SPI (3). Also, Target return period sets up 30 year and target SPI analysed unit of region using thiessen by result of nonparametric frequency. Analyzed result, Drought was entirely different from severity and frequency by region. This study results will contribute to a national water resources plan and disaster prevention measures with data foundation for judgment and preparation of drought in korea.

• Journal of Soil and Groundwater Environment
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• v.11 no.3
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• pp.31-42
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• 2006

Drought indices, such as PDSI (palmer Drought Severity Index), SWSI (Surface Water Supply Index) and SPI (Standardized Precipitation Index), have been developed to assess and forecast an intensity of drought. To find the applicability of groundwater level data to a drought assessment, a correlation analysis between SPI and groundwater levels was conducted for each time series at a drought season in 2001. The comparative results between SPI and groundwater levels of shallow wells of three national groundwater monitoring stations, Chungju Gageum, Yangpyung Gaegun, and Yeongju Munjeong, show that these two factors are highly correlated. In case of SPI with a duration of 1 month, cross-correlation coefficients between two factors are 0.843 at Chungju Gageum, 0.825 at Yangpyung Gaegun, and 0.737 at Yeongju Munjeong. The time lag between peak values of two factors is nearly zero in case of SPI with a duration of 1 month, which means that groundwater level fluctuation is similar to SPI values. Moreover, in case of SPI with a duration of 3 month, it is found that groundwater level can be a leading indicator to predict the SPI values I week later. Some of the national groundwater monitoring stations can be designated as DIW (Drought Index Well) based on the detailed survey of site characteristics and also new DIWs need to be drilled to assess and forecast the drought in this country.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1211-1215
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• 2006

가뭄에 대한 대책을 수립하기 위해서는 가뭄의 심도 및 지속기간 등 가뭄특성을 산정하여 가뭄을 정량화 하는 것이 필요하다. 본 연구에서는 가뭄을 해석하기 위하여 강수를 이용한 표준강수지수(SPI, Standardized precipitation Index)를 이용하여 가뭄 특성을 산정하였다. 서울지점은 강수의 근대 관측 기간이 약 100년 정도(1907년 ${\sim}$ 2003년) 이기 때문에 측우기 자료를 이용하여 조선 말까지(1770년 ${\sim}$ 1907년) 자료를 확장하여 가뭄지수를 산정하였다. 산정된 SPI로부터 절단 수준법 개념을 이용하여 SPI의 -1이하를 가뭄으로 정의 하고, 연속된 가뭄으로부터 가뭄 심도 및 가뭄 지속기간을 구하였다. 가뭄의 지속기간과 심도를 이변수 감마 분포(Bivariate Gamma Distribution)를 이용하여 가뭄의 재현특성을 분석하였고, 가뭄의 지속기간만을 고려한 재현기간과 본 연구에서 산정된 이변수 가뭄 재현기간을 서로 비교하였다.

• The Journal of Engineering Geology
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• v.34 no.2
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• pp.329-338
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• 2024

In this study, drought assessment using the standardized precipitation index (SPI) and streamflow drought index (SDI) was conducted for the Inje region, Gangwon Province, South Korea. Monthly streamflow ratios were reviewed through basic data for drought analysis (rainfall, streamflow), and meteorological drought and hydrological drought analysis were conducted using precipitation and water level/flow observation stations near the Inje watershed. The analysis revealed that the drought that occurred in 2014 persisted until 2017 consistently across all drought indices (SPI, SDI). When analyzing drought indices calculated using 12 months of hydrometeorological data, it was found that severe drought lasted for approximately 24 months, indicating that drought damage would have been severe.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.509-518
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• 2016

This study assessed drought of Cheongmicheon watershed from 1985 to 2015 according to duration. In order to quantify drought, we used meteorological and hydrological drought index. Standardized Precipitation Index(SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index(SPEI) based on precipitation and evapotranspiration were applied as meteorological drought index. Palmer Drought Severity Index(PDSI) and Stream Drought Index(SDI) based on simulation of Soil and Water Assessment Tool(SWAT) model were applied as agricultural and hydrological drought index. As a result, in case average of extreme and averaged drought, 2014 and 2015 have the most vulnerable in all drought indices. Variation of drought showed different trend with regard to analysis of frequency. Also, the extreme and averaged drought have high correlation between drought indices excluding between PDSIs. However, each drought index showed different occurrence year and severity of drought Therefore, drought indices with various characteristics were used to analysis drought.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.128-141
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• 2010

Drought indices such as SPI(Standard Precipitation Index) and PDSI(Palmer Drought Severity Index) estimated using ground observations are not enough to describe detail spatial distribution of drought condition. In this study, the drought index with improved spatial resolution was estimated by using the CART algorithm and ancillary data such as MODIS NDVI, MODIS LST, land cover, rainfall, average air temperature, SPI, and PDSI data. Estimated drought index using the proposed approach for the year 2008 demonstrates better spatial information than that of traditional approaches. Results show that the availability of satellite imageries and various associated data allows us to get improved spatial drought information using a data mining technique and ancillary data and get better understanding of drought condition and prediction.

• Journal of Korea Water Resources Association
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• v.48 no.1
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• pp.69-78
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• 2015

In this study, meteorological drought indices were examined to simulate hydrological drought. SPI (Standardized Precipitation Index) and SPEI (Standardized Precipitation Evapotranspiration Index) was applied to represent meteorological drought. Further, in order to evaluate the hydrological drought, monthly total inflow and SDI (Streamflow Drought Index) was computed. Finally, the correlation between meteorological and hydrological drought indices were analyzed. As a results, in monthly correlation comparison, the correlation between meteorological drought index and monthly total inflow was highest with 0.67 in duration of 270-day. In addition, a meteorological drought index were correlated 0.72 to 0.87 with SDI. In compared to the annual extremes, the relationship between meteorological drought index and minimum monthly inflow was hardly confirmed. But SDI and SPEI showed a slightly higher correlation. There are limitation that analyze extreme hydrological drought using meteorological drought index. For the evaluation of the hydrological drought, drought index which included inflow directly is required.