• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.349-349
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• 2017

표준강수지수(Standardized precipitation index, SPI)는 가장 널리 사용되고 있는 가뭄지수로, 우리나라 뿐만 아니라 세계기상기구(World Meteorological Organization)에서도 추천하고 있는 대표적인 기상학적 가뭄 지수라고 할 수 있다. 현재 표준강수지수는 2변수 gamma 분포를 적용하여 강수 부족 상황을 지수화하여 나타내고 있는데, 일부 연구에서는 다른 확률분포형의 적용하기도 하였다(Guttman, 1999; Lloyd-Hughes and Saunders, 2002; Stagge et al., 2015). 우리나라에서는 유원희(2000)에 의해 Pearson type 3, 2변수 gamma, generalized logistic, GEV, 3변수 log-normal 분포에 따른 SPI 산정 결과를 비교한 연구가 수행되었는데, SPI 산정에는 분포형별 차이가 뚜렷하지 않다는 결론을 얻었다. 그러나 이때 금강유역 내 지점에 국한하여 적용하였고, 분포형별 적합도 검정을 수행하지 않고 SPI 산정결과만을 비교하여 우리나라에 일반적으로 적용하기에는 어려움이 있다. 따라서 본 연구에서는 우리나라의 강우특성을 반영할 수 있도록 다양한 확률분포형을 고려하여 표준강수지수를 분석하고자 한다. 이를 위해 관측기간이 30년 이상인 기상관측소의 월단위 강우자료를 구축하고, 월단위 강우자료에 다양한 확률분포형을 적용하고자 한다. 이때 적용하는 확률분포형은 2변수 gamma, Gumbel, normal 분포이다. 적정 확률분포형 선정을 위해 적합도 검정을 수행하고자 한다. 또한 각 분포형별로 산정된 표준강수지수를 기존 표준강수지수와 비교검토하고자 한다.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1249-1263
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• 2013

In order to minimize the damages caused by long-term drought, appropriate drought management plans of the basin should be established with the drought forecasting technology. Further, in order to build reasonable adaptive measurement for future drought, the duration and severity of drought must be predicted quantitatively in advance. Thus, this study, attempts to forecast drought in Korea by using an Artificial Neural Network Model, and drought index, which are the representative statistical approach most frequently used for hydrological time series forecasting. SPI (Standardized Precipitation Index) for major weather stations in Korea, estimated using observed historical precipitation, was used as input variables to the MLP (Multi Layer Perceptron) Neural Network model. Data set from 1976 to 2000 was selected as the training period for the parameter calibration and data from 2001 to 2010 was set as the validation period for the drought forecast. The optimal model for drought forecast determined by training process was applied to drought forecast using SPI (3), SPI (6) and SPI (12) over different forecasting lead time (1 to 6 months). Drought forecast with SPI (3) shows good result only in case of 1 month forecast lead time, SPI (6) shows good accordance with observed data for 1-3 months forecast lead time and SPI (12) shows relatively good results in case of up to 1~5 months forecast lead time. The analysis of this study shows that SPI (3) can be used for only 1-month short-term drought forecast. SPI (6) and SPI (12) have advantage over long-term drought forecast for 3~5 months lead time.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.602-602
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• 2015

가뭄에 대한 정의와 구분이 다양하게 존재하나 일반적으로 기상학적 가뭄으로부터 농업적 가뭄, 수문학적 가뭄, 사회경제학적 가뭄으로 전이되므로 강수량의 부족이 가뭄의 첫 번째 원인인 것은 자명하다. 최근까지 여러 가지 기상학적 가뭄지수가 개발되어 다양한 목적으로 세계 곳곳에서 활용되고 있으나, 그 중 적용사례가 가장 많은 것은 표준강수지수 (SPI; Standardized Precipitation Index)이다. 월단위로 계산되어지는 SPI는 우리나라와 같이 강수의 변동성이 큰 지역에서는 그 활용성이 떨어지는 경우가 있어 최근에는 일 단위 SPI를 산정하여 활용하는 경우도 있다. 그러나, 일단위 SPI는 가뭄기간 동안 가뭄단계가 'Extreme drought'에서 'Moderate drought'로 약해질 경우 가뭄 지속기간이 가장 긴 'Moderate drought' 단계에서 가뭄피해 및 체감하는 고통이 가장 클수 있어, 가뭄에 대응하거나 대국민 가뭄정보 전달에 한계가 있다. 가뭄에 대응하거나 가뭄정보 전달을 위해서는 가뭄이 지속되는 동안 가뭄단계가 높아질 필요성이 있다. 이에 본 연구에서는 가뭄사상의 특성 중 가뭄의 강도(Intensity)와 지속기간(Duration)의 특성을 모두 포함하는 가뭄의 심도(Severity)를 활용하여 기상학적 가뭄을 평가하였다. 일단위 SPI 값(강도)을 가뭄기간동안 누적하여 일단위 가뭄심도(SPI-S)를 산정하고 이를 통해 가뭄단계를 제안하였다. 또한 다양한 SPI 대상기간에 대해 최솟값을 취하는 Blended SPI에 대해서도 같은 방법으로 가뭄심도(SPIB-S)를 산정하고 가뭄단계를 적용하였다. 2001년, 2008-2009년, 2012년 가뭄사례에 적용한 결과 SPI-S(or SPIB-S)는 가뭄기간동안 단계적인 가뭄단계의 상승으로 당시의 가뭄상황을 잘 나타내었다. 이는 SPI-S(or SPIB-S)가 단계적인 가뭄대비와 대응 지수로 가뭄피해 경감에 활용도가 높을 것으로 판단되며, 가뭄상황을 지역민들에게 단계적, 일관적으로 전달할 수 있어 가뭄극복을 위한 시민참여를 유도하기에 유리할 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.150-150
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• 2019

The development of prolong and severe drought can directly impact on the environment, agriculture, economics and society of country. A lot of efforts have been made across worldwide in the planning, monitoring and mitigation of drought. Currently, different drought indices such as the Palmer Drought Severity Index (PDSI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) are developed and most commonly used to monitor drought characteristics quantitatively. However, it will be very meaningful and essential to develop a more effective technique for assessment and monitoring of onset and end of drought. Therefore, in this study, the hidden Markov Bayesian classifier (MBC) was employed for the assessment of onset and end of meteorological drought classes. The results showed that the probabilities of different classes based on the MBC were quite suitable and can be employed to estimate onset and end of each class for meteorological droughts. The classification results of MBC were compared with SPI and with past studies which proved that the MBC was able to account accuracy in determining the accurate drought classes. For more performance evaluation of classification results confusion matrix was used to find accuracy and precision in predicting the classes and their results are also appropriate. The overall results indicate that the MBC was effective in predicating the onset and end of drought events and can utilized for monitoring and management of short-term drought risk.

• 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.

• 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 the Korean Society of Hazard Mitigation
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• v.5 no.4 s.19
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• pp.59-69
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• 2005

Drought is difficult to detect and monitor, but it is easy to interpret through the drought index. The Palmer Drought Severity Index(PDSI), which is most commonly used as one of drought indices, have been widely used, however, the index have limitation as operational tools and triggers for policy responses. Recently, a new index, the Standardized Precipitation Index(SPI), was developed to improve drought detection and monitoring capabilities. The SPI has an improvement over previous indices md has several characteristics including its simplicity and temporal flexibility that allow its application for water resources on all timescales. Keetch-Byram Dought Index(KBDI) was defined as a number representing the net effect of evapotranspiration and precipitation in producing cumulative moisture deficiency in deep duff or upper soil layer. The purpose of this study is to analyze drought in Korea by using PDSI, SPI and KBDI. The result of this study suggests standard drought index by comparing of estimated drought indices. The data are obtained from Korea Meteorological Administration 56 stations over 30 years in each of the 8 sub-basins covering the whole nation. It is found that the PDSI had the advantage to detect the stage of drought resulting from cumulative shortage of rainfall, while SPI and KBDI had the advantage to detect the stage of drought resulting from short-term shortage of rainfall.

• Journal of Environmental Science International
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• v.25 no.11
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• pp.1511-1519
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• 2016

Jeju Island relies on subterranean water for over 98% of its water resources, and it is therefore necessary to continue to perform studies on drought due to climate changes. In this study, the representative standardized precipitation index (SPI) is classified by various criteria, and the spatial characteristics and applicability of drought in Jeju Island are evaluated from the results. As the result of calculating SPI of 4 weather stations (SPI 3, 6, 9, 12), SPI 12 was found to be relatively simple compared to SPI 6. Also, it was verified that the fluctuation of SPI was greater fot short-term data, and that long-term data was relatively more useful for judging extreme drought. Cluster analysis was performed using the K-means technique, with two variables extracted as the result of factor analysis, and the clustering was terminated with seven-time repeated calculations, and eventually two clusters were formed.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.2
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• pp.1-11
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• 2019

Remote sensing products have long been used to monitor and forecast natural disasters. Satellite-derived rainfall products are becoming more accurate as space and time resolution improve, and are widely used in areas where measurement is difficult because of the periodic accumulation of images in large areas. In the case of North Korea, there is a limit to the estimation of precipitation for unmeasured areas due to the limited accessibility and quality of statistical data. CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) is global satellite-derived rainfall data of 0.05 degree grid resolution. It has been available since 1981 from USAID (U.S. Agency for International Development), NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration). This study evaluates the applicability of CHIRPS rainfall products for South Korea and North Korea by comparing CHIRPS data with ground observation data, and analyzing temporal and spatial drought trends using the Standardized Precipitation Index (SPI), a meteorological drought index available through CHIRPS. The results indicate that the data set performed well in assessing drought years (1994, 2000, 2015 and 2017). Overall, this study concludes that CHIRPS is a valuable tool for using data to estimate precipitation and drought monitoring in Korea.

• Journal of Korea Water Resources Association
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• v.47 no.1
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• pp.71-82
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• 2014

The objective of this study is to project and analyze drought conditions using future climate and hydrology information over South Korea. This study used three Global Climate Models (GCMs) and three hydrological models considering the uncertainty of future scenario. Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI) and Standardized Soil moisture Index (SSI) classified as meteorological, hydrological and agricultural droughts were estimated from the precipitation, runoff and soil moisture. The Mann-Kendall test showed high increase in future drought trend during spring and winter seasons, and the drought frequency of SRI and SSI is expected higher than that of SPI. These results show the high impact of climate change on hydrological and agriculture drought compared to meteorological drought.