• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.57-67
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• 2023

A flash drought is a rapid-onset drought that develops over a short period of time as weather and environmental factors change rapidly, unlike general droughts, due to meteorological abnormalities. Abnormally high evapotranspiration rates and rapid declines in soil moisture increase vegetation stress. In addition, crop yields may decrease due to flash droughts during crop growth and may damage agricultural and economic ecosystems. In this study, Flash Drought Intensity Index (FDII) based on soil moisture data from Gravity Recovery Climate Experiment (GRACE) was used to analyze flash drought. FDII, which is calculated using soil moisture percentile, is expressed by multiplying two factors: the rate of intensification and the drought severity. FDII was developed for domestic flash drought events from 2014 to 2018. The flash drought that occurred in 2018, Chungcheongbuk-do showed the highest FDII. FDII was higher in heat wave flash drought than in precipitation deficit flash drought. The results of this study show that FDII is reliable flash drought analysis tool and can be applied to quantitatively analyze the characteristics of flash drought in South Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.399-399
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• 2021

최근 전세계적으로 발생하고 있는 기후변화로 인해 가뭄, 홍수, 태풍 등 자연재해의 빈도가 증가하고 있다. 특히, 강수량의 변동성이 커지면서 가뭄과 홍수가 단기간에 번갈아 가며 발생하는 경우가 자주 발생하고 있다. 가뭄과 홍수가 짧은 기간 동안에 교차해서 발생하는 급변사상은 예측하기 어려우며, 갑작스럽게 중첩되는 재난으로 인명과 재산피해 뿐 아니라 생태계에까지 심각한 영향을 미칠 것이다. 본 연구에서는 일 강수량 자료를 바탕으로 표준가중평균강수지수(Standard Weighted Average Precipitation, SWAP)를 산정하고 한강 유역의 가뭄-홍수 급변사상에 대한 특성을 분석하였다. 1966년부터 2018년까지의 한강유역 중권역별 면적평균강수량과 가중치, 이전 강수량의 영향을 받는 일수를 바탕으로 SWAP를 산정하였다. SWAP 지수가 10일 연속 -1 미만일 때를 가뭄이라 정의하고, 이후 SWAP 지수가 7일 연속 0.5 이상이면 가뭄사상이 종료된다고 판정하였다. 또한 SWAP 지수가 10일 연속 +1 초과일 때를 홍수라고 정의하고, SWAP 지수가 7일 연속 -0.5 이하가 되면 홍수사상이 종료된다고 판정하였다. 가뭄-홍수 급변사상이란 가뭄의 종료시점과 홍수의 시작시점의 차이가 5일 이내일 경우에 해당한다. 급변사상의 전·후로 강수량이 얼마나 급격하게 차이 나는지를 판단하기 위하여 급변 시점 전·후 5일의 누적 SWAP 지수인 심각도 K(Severity)를 분석지표로 활용하였다. K를 통해 한강유역 가뭄-홍수 급변사상의 시·공간적 분포를 분석하고 미래의 급변사상의 발생가능성을 예측할 수 있다. 본 연구 결과, 한강 유역의 24개 중권역 중에서 18개의 중권역이 가뭄-홍수 급변사상의 심각도가 점점 상승하는 추세이고, 가장 심각도 상승폭이 높은 중권역은 홍천강(1014)으로 첫 사상인 1967년부터부터 2015년의 마지막 사상까지 약 55% 정도 상승하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.140-140
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• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.683-690
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• 2008

The objectives of this study are to provide an observation-based urban flood prediction model and to evaluate their performance on a restored Cheonggye stream. The study area, which has its own unique hydrologic and flooding conditions that can be characterized the standard of flood occurrence by watergate opening and walk lane inundation, measured stream discharges at the 5 sites and watergate opening and walk lane inundation through the main stream since 2006. This study derived the relationship between precipitation intensity and watergate opening and walk lane inundation time by using the observations of 2006 and verified their performance on 2007 flood events. The result showed that the coefficients of determination are ranged on 0.57-0.75, which would be acceptable if considering the complexity of the area and the proposed model simplicity. It also suggested the continuous observation of these properties is required for further improvement of the models.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.475-488
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• 2017

To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.

• The Journal of Engineering Geology
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• v.21 no.2
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• pp.133-145
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• 2011

Unsaturated soil column tests were performed for weathered gneiss soil and weathered granite soil to assess the relationship between infiltration velocity and rainfall condition for different rainfall durations and for multiple rainfall events separated by dry periods of various lengths (herein, 'rainfall break duration'). The volumetric water content was measured using TDR (Time Domain Reflectometry) sensors at regular time intervals. For the column tests, rainfall intensity was 20 mm/h and we varied the rainfall duration and rainfall break duration. The unit weight of weathered gneiss soil was designed 1.21 $g/cm^3$, which is lower than the in situ unit weight without overflow in the column. The in situ unit weight for weathered granite soil was designed 1.35 $g/cm^3$. The initial infiltration velocity of precipitation for the two weathered soils under total amount of rainfall as much as 200 mm conditions was $2.090{\times}10^{-3}$ to $2.854{\times}10^{-3}$ cm/s and $1.692{\times}10^{-3}$ to $2.012{\times}10^{-3}$ cm/s, respectively. These rates are higher than the repeated-infiltration velocities of precipitation under total amount of rainfall as much as 100 mm conditions ($1.309{\times}10^{-3}$ to $1.871{\times}10^{-3}$ cm/s and $1.175{\times}10^{-3}$ to $1.581{\times}10^{-3}$ cm/s, respectively), because the amount of precipitation under 200 mm conditions is more than that under 100 mm conditions. The repeated-infiltration velocities of weathered gneiss soil and weathered granite soil were $1.309{\times}10^{-3}$ to $2.854{\times}10^{-3}$ cm/s and $1.175{\times}10^{-3}$ to $2.012{\times}10^{-3}$ cm/s, respectively, being higher than the first-infiltration velocities ($1.307{\times}10^{-2}$ to $1.718{\times}10^{-2}$ cm/s and $1.789{\times}10^{-2}$ to $2.070{\times}10^{-2}$ cm/s, respectively). The results reflect the effect of reduced matric suction due to a reduction in the amount of air in the soil.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.237-251
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• 2011

This study presents a review on the recent climate change over the Korean peninsula, which has experienced a significant change due to the human-induced global warming more strongly than other regions. The recent measurement of carbon dioxide concentrations over the Korean peninsula shows a faster rise than the global average, and the increasing trend in surface temperature over this region is much larger than the global mean trend. Recent observational studies reporting the weakened cold extremes and intensified warm extremes over the region support consistently the increase of mean temperature. Surface vegetation greenness in spring has also progressed relatively more quickly. Summer precipitation over the Korean peninsula has increased by about 15% since 1990 compared to the previous period. This was mainly due to an increase in August. On the other hand, a slight decrease in the precipitation (about 5%) during Changma period (rainy season of the East Asian summer monsoon), was observed. The heavy rainfall amounts exhibit an increasing trend particularly since the late 1970s, and a consecutive dry-day has also increased primarily over the southern area. This indicates that the duration of precipitation events has shortened, while their intensity became stronger. During the past decades, there have been more stronger typhoons affecting the Korean peninsula with landing more preferentially over the southeastern area. Meanwhile, the urbanization effect is likely to contribute to the rapid warming, explaining about 28% of total temperature increase during the past 55 years. The impact of El Nino on seasonal climate over the Korean peninsula has been well established - winter [summer] temperatures was generally higher [lower] than normal, and summer rainfall tends to increase during El-Nino years. It is suggested that more frequent occurrence of the 'central-Pacific El-Nino' during recent decades may have induced warmer summer and fall over the Korean peninsula. In short, detection and attribution studies provided fundamental information that needed to construct more reliable projections of future climate changes, and therefore more comprehensive researches are required for better understanding of past climate variations.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.3
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• pp.208-213
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• 2007

When overland flow water is small and slow, it moves down a stream slowly and we use it as available resource. However, it could not only be good for nothing but arouse an inundation if a lot of runoff pour down to stream at a torrential rain. So it is important to know how much water to flow out and be stored in soil and on land in order to predict a flood and conserve soil and water quality. We intended to develop the prediction model of runoff in upland at a torrential rain and conducted lysimeter study in soybean cultivation and bare soil with 3 slopeness, 3 slope length and 5 soil texture from 1985 to 1991. The data of rainfall and runoff were used when daily rainfall was over 80 mm, the level of torrential rain warning. Minimum rainfall occurring runoff (MROR) was dependent on surface coverage and slope length. However soil texture and slopeness had a little influence on MROR. Runoff after MROR increased in proportion to precipitation which depended on surface coverage, soil texture and slope. Runoff ratio was larger in fine texture and bare soil than coarse soil and soybean coverage. Runoff ratio was in proportion to a square root of slope angle(radian) and reduced with slope length to converge a certain value. From these basis, we developed the prediction model following as $$Runoff(mm)=a(s^{0.5}+l^b)(Rainfall(mm)-80(1-e^{-bl}))$$ where a is a coefficient relevant soil hydraulic properties, b is a surface coverage coefficient, s is a slope angle and l is a slope length. The coefficient a was 0.5 in sandy loam and 0.6 in clay, and b was 0.06 in bare soil and 0.5 in soybean cultivation.

• 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.