• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.701-701
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• 2012

장시간의 강수부족으로부터 야기되는 가뭄은 다른 자연재해에 비하여 하나의 물리적인 특성으로 표현하기에는 한계가 있다. 이러한 가뭄의 특성을 파악하기 위하여 다양한 지수들이 사용되고 있으며, 각각의 지수는 기후적 혹은 물리적 특성 등을 반영하여 가뭄을 평가하고 있다. 다양한 가뭄지수중 SPI(Standardized Precipitation Index)는 가뭄 발생에 있어 가장 중요한 요소를 차지하는 강수를 이용하여 가뭄을 평가하고 있으며, 비교적 간단한 방법으로 계산되어지며 다양한 기관에서 사용되고 있다. 본 연구에서는 무강수일수와 선행강수조건에 따른 영향을 고려한 개선된 SPI 지수를 제시하고 가뭄감지능력을 기존의 가뭄지수와 비교 분석 하였다. 무강수일수의 고려를 위하여 월 최대 무강수일수의 확률분포를 구하고 이를 다시 누적확률분포로 나타냄으로서 기존에 가뭄지수에 무강수일수의 영향을 추가할 수 있는 가중치를 생성하였다. 또한 추가적으로 월 최대 무강수일의 시점을 전기, 중기, 후기로 구분하여 각각의 기간에 따라 가중치를 변환하여 수행하였다. 이전의 강수효과를 고려하기 위하여 15일 이전의 강수를 성수기와 비성수기로 구분하고 각각의 기간에 강수량에 따른 가중치를 세분하여 기존의 가뭄지수에 추가하였다. 기존의 가뭄지수와 새롭게 제시된 가뭄지수의 평가를 위하여 ROC분석을 사용하였으며, ROC분석은 실제 발생했던 사실과 산정된 값을 평가하는 방법으로 본 연구에서는 과거 실제 방생한 가뭄기록과 산정된 지수의 수치를 4가지의 범주로 나누어 분석하였다. 평가 기간은 1973년부터 2009년까지이며, 사용된 자료는 우리나라 기상청의 76개 지상관측지점 중 섬 지역 7개를 제외한 69개 지점의 정보를 이용하였다. 분석결과 기존의 SPI3에 비하여 전반적으로 향상된 가뭄감지능력을 보여주었다. 무강수일수와 선행강수효과를 이용한 가뭄지수의 가중치 생성은 SPI3 뿐만 아니라 다양한 지수에 적용되어 사용성이 높아 뛰어난 가뭄감지능력을 가지는 가뭄지수 개발에 효과적으로 활용될 것으로 기대된다.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.329-340
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• 2021

Purpose: In this paper, using artificial neural network algorithm, the Korean Peninsula was analyzed for drought vulnerable areas by predicting weather data changes. Method: Monthly cumulative precipitation data were utilized for research areas considering the specific nature areas, and weather data prediction through artificial neural network algorithm was carried out using statistical program R. The predicted data were applied to the Standardized Precipitation Index (SPI) to analyze drought vulnerable areas in the Korean Peninsula. Result: In this paper, the correlation coefficient values between real and predicted data are found to be 0.043879 higher on average than the regression results, using artificial neural network algorithms. Conclusion: The results of the research are expected to be used as basic research materials for responding to drought.

• Journal of Korea Water Resources Association
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• v.49 no.3
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• pp.187-196
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• 2016

Standardized Precipitation Evapotranspiration Index (SPEI) considering evapotranspiration and precipitation is generally used to quantify the drought severity. Also, Reconnaissance Drought Index (RDI) has been frequently used in the arid regions which is suffering severe droughts, but drought analysis in association with RDI has been the focus of few studies in South Korea. Therefore, this study compared two meterological drought indices based on precipitation and evapotranspiration using Thornthwaite, Hargreaves, and Blaney-Criddle evaportranspiration calculation methods. Meteorological data of sixteen weather stations which are operated by Korea Meteorological Administration (KMA) were used to quantify drought and to compare characteristics of drought for the Han River Basin from 1992 to 2015. As a result, in case of Han River Basin, severe drought sharply increased in recent years. While the correlation coefficients are relatively high between the SPEIs and RDIs, the drought severity and year of severe drought are partially different. Therefore, it is necessary that RDI will be also measured to quantify severity and occurrence year of drought.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• 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.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1555-1559
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• 2009

우리나라의 연 강수량은 지역에 따라 다르지만 대체로 1280mm 정도로 연강수량의 60%$\sim$80%가 여름철에 집중되어 있는 특성 때문에 비가 많이 오는 여름에는 홍수대책을, 남은 계절은 용수 확보를 위하여 늘 고심하게 된다. 특히 2008년도 여름철에 우리나라에 영향을 끼친 태풍은 단 하나로, 여름철에 많은 강우가 발생하지 않아 연 강수량은 정상대비 강수량에 70%$\sim$80% 수준에 불과하다. 그로 인해 용수확보에 고심하고 있으며 현재 일부지역에서 극심한 물 부족현상을 겪고 있는 실정이다. 따라서 본 연구에서는 전국에 주요지점을 인천, 서울, 대구, 전주, 부산, 목포지점으로 총 6지점을 선정하여, 대표적인 가뭄지수라 할 수 있는 표준강수지수 (Standardized Precipitation Index, SPI)와 팔머가뭄심도지수(Palmer Drought Severity Index, PDSI)를 이용하여 가뭄지수의 민감도 분석을 실시하였다. 강우자료 및 온도자료는 기상청에서 제공하는 30년간의 정상(71$\sim$00년)자료를 이용하여 가뭄지수의 민감도 분석을 실시하였다. 분석방법은 강우량자료가 정상 강우대비 0%, $\pm10%$, $\pm20%$, $\pm30%$, $\pm40%$, $\pm50%$로 변동 한다 보고 각각의 가뭄지수를 산정하여 비교분석을 실시하였다.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.171-182
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• 2014

The objective of this study is to evaluate the utilization of bivariate joint drought index in South Korea. In order to develop the bivariate joint drought index, in this study, Clayton copula was used to estimate the joint distribution function and the calibration method was employed for parameter estimation. Precipitation and soil moisture data were selected as input data of bivariate joint drought index for period of 1977~2012. The time series analysis, ROC (Receiver Operating Characteristic) analysis, spatial analysis were used to evaluate the bivariate joint drought index with SPI (Standardized Precipitation Index) and SSI (Standardized Soil moisture Index). As a result, SPI performed better for drought onset and SSI for drought demise. On the other hand the bivariate joint drought index captured both drought onset and demise very well. The ROC score of bivariate joint drought index was higher than that of SPI and SSI, and it also reflected the local drought situations. The bivariate joint drought index overcomes the limitations of existing drought indices and is useful for drought analysis.

• Journal of Ecology and Environment
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• v.44 no.3
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• pp.115-125
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• 2020

Background: The phenomenon of tree dieback in forest ecosystems around the world, which is known to be associated with high temperatures that occur simultaneously with drought, has received much attention. Korea is experiencing a rapid rise in temperature relative to other regions. Particularly in the growth of evergreen conifers, temperature increases in winter and spring can have great influence. In recent years, there have been reports of group dieback of Pinus densiflora trees in Korea, and many studies are being conducted to identify the causes. However, research on techniques to diagnose and monitor drought stress in forest ecosystems on local and regional scales has been lacking. Results: In this study, we developed and evaluated an index to identify drought and high-temperature vulnerability in Pinus densiflora forests. We found the Drought Stress Index (DSI) that we developed to be effective in generally assessing the drought-reactive physiology of trees. During 2001-2016, in Korea, we refined the index and produced DSI data from a 1 × 1-km unit grid spanning the entire country. We found that the DSI data correlated with the event data of Pinus densiflora mass dieback compiled in this study. The average DSI value at times of occurrence of Pinus densiflora group dieback was 0.6, which was notably higher than during times of nonoccurrence. Conclusions: Our combination of the Standard Precipitation Index and growing degree days evolved and short- and long-term effects into a new index by which we found meaningful results using dieback event data. Topographical and biological factors and climate data should be considered to improve the DSI. This study serves as the first step in developing an even more robust index to monitor the vulnerability of forest ecosystems in Korea.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.299-311
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• 2007

Climatic abnormal phenomena involving El Nino and La Nina have been frequently reported in recent decades. The interannual climate variability represented by El Nino-Southern Oscillation (ENSO) is sometimes investigated to account for the climatic abnormal phenomena around the world. Although many hydroclimatologists have studied the impact of ENSO on regional precipitation and streamflow, however, there are still many difficulties in finding the dominant causal relationship between them. This relationship is very useful in making hydrological forecasting models for water resources management. In this study, the seasonal relationships between ENSO and hydrologic variables were investigated in Korea. As an ENSO indicator, Southern Oscillation Index (SOI) was used. Monthly precipitation, monthly mean temperature, and monthly dam inflow data were used after being transformed to the standardized normal index. Seasonal relationships between ENSO and hydrologic variables were investigated based on the exceedance probability and distribution of hydrologic variables conditioned on the ENSO episode. The results from the analysis of this study showed that the warm ENSO episode affects increases in precipitation and temperature, and the cold ENSO episode is related with decreases in precipitation and temperature in Korea. However, in some regions, the local relationships do not correspond with the general seasonal relationship.