• 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.56 no.12
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• pp.929-937
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• 2023

This study aims to develop rules for the Determination of Drought Stages at the Local Level based on the drought cases in Gwangju and Jeollanam-do in 2022-2023. Among the eight drought indicators provided, six indicators (Agricultural drought stage (for paddy), Residential & industrial drought stage, SPI-12, Relative agricultural water storage, Residential water consumption change (for domestic use), Residential water consumption change (for non-domestic use) were confirmed to have statistical correlations with the perceptions of local government officials and experts. Additionally, this drought indicator was applied to a decision tree algorithm to develop rules for determining the severity of drought. Although it presented results similar to those of the existing method presented in previous studies, it showed a significant comparative advantage in explaining the temporal and spatial patterns of drought in the Gwangju and Jeollanam-do.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.89-97
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• 2010

In this study, the impact of climate change on the spatio-temporal behavior of extreme drought events is investigated by comparing drought severity-area-duration curves under present and future climate conditions. In our climate-change impact experiments, the future climate is based on two GCMs(CGCM3.1-T63 and CSIRO-MK3.0). As a result, in the case of CGCM3.1-T63 future drought events are similar to the present, but in the case of CSIRO-MK3.0 future drought risk is likely to increase. Such results indicate that a climate change vulnerability assessment for present water resources supply system is urgent.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.195-207
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• 2024

This study selected major drought events that occurred in the Jeonnam region from 1991 to 2023, examining both meteorological and hydrological drought occurrence mechanisms. The daily drought index was calculated using rainfall and dam storage as input data, and the drought propagation characteristics from meteorological drought to hydrological drought were analyzed. The characteristics of the 2022-23 drought, which recently occurred in the Jeonnam region and caused serious damage, were evaluated. Compared to historical droughts, the duration of the hydrological drought for 2022-2023 lasted 334 days, the second longest after 2017-2018, the drought severity was evaluated as the most severe at -1.76. As a result of a linked analysis of SPI (StandQardized Precipitation Index), and SRSI (Standardized Reservoir Storage Index), it is possible to suggest a proactive utilization for SPI(6) to respond to hydrological drought. Furthermore, by confirming the similarity between SRSI and SPI(12) in long-term drought monitoring, the applicability of SPI(12) to hydrological drought monitoring in ungauged basins was also confirmed. Through this study, it was confirmed that the long-term dryness that occurs during the summer rainy season can transition into a serious level of hydrological drought. Therefore, for preemptive drought response, it is necessary to use real-time monitoring results of various drought indices and understand the propagation phenomenon from meteorological-agricultural-hydrological drought to secure a sufficient drought response period.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.145-153
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• 2014

Several studies regarding drought indices and criteria have been widely studied in the literature. If one defines the onset, severity, and end of droughts, in general, a certain threshold needs to be set to assess the drought events. However, the uncertainty associated with the threshold is a critical problem in drought analysis. To take full advantage of the inherent features in the rainfall series, a Hidden Markov Model (HMM) based probabilistic drought analysis was proposed rather than using the existing threshold based analysis. As a result, the proposed HMM based probabilistic drought analysis scheme shows better performance in terms of defining drought state and understanding underlying characteristics of the drought. In addition, the HMM based approach is capable of quantifying the uncertainties associated with the classifying meteorological drought condition in a systematic way.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.795-805
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• 2013

Drought is one of the severe natural disasters and it can profoundly affect our society and ecosystem. Also, it is a very important variable for water resources planning and management. Therefore, the drought is analyzed in this study to understand the drought distribution and trend. The Standard Precipitation Index (SPI) is estimated using precipitation data obtained from 55 rain gauge stations in South Korea and the SPI based drought variables such as drought duration and drought severity were defined. Drought occurrence and joint probabilistic analysis for SPI based drought variables were performed with run theory and copula functions. And then the return period and spatial distribution of droughts on the South Korea was estimated. As the results, we have shown that Gongju and Chungju in Chungcheong-do and Wonju, Inje, Jeongseon, Taebeak in Gangwon-do have vulnerability to droughts.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6B
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• pp.541-549
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• 2010

While the number of rainy days is decreasing, the mean annual precipitation is increasing due to abnormal climate changes caused by the global warming in Korea. Owing to the biased-concentration of rainfall during specific short terms, not only flood but also drought becomes more and more serious. From the literature, it is easily found that previous studies about flood have been intensively conducted. However, previous studies about drought have been performed rarely. This study conducted the comparison between two representative drought indexes calculated from soil moisture and precipitation. Study area was Haenam-gun, Jeollanam-do in Korea. Soil Moisture Index(SMI) was calculated from soil moisture data while the Standardized Precipitation Index(SPI) and the Palmer Drought Severity Index(PDSI) were calculated from meteorological data. All monthly data utilized in this study were observed at the KoFlux Tower. After the comparative analysis, three indexes showed similar tendency. Therefore, it is thought that the drought index using soil moisture measured at the KoFlux Tower is reasonable, which is because the soil moisture is immediately affected by all the meteorological factors.

• 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.

• 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.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.181-181
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• 2017

Global warming and climate change have been one of the most important problems last 2 decades. Global warming is known to cause abnormal climate and influence ecology, food production and human health. According to climate change model global warming is causing expansion of drought and increase of evaporation. Therefore, securing water in agriculture has been an important issue for crop cultivation. As potato is susceptible to drought, water shortage generally results in decrease of yield and decrease of biomass. In this research, we investigated characteristics of inorganic nutrient absorption and growth of plants grown under drought condition. Plants were sampled in sites of Cheong-ju and Gangneung, where the severity of drought stress were different. During the growth period in Gangneung, total rainfall in 2016 decreased by 50% compared with those in last 5 years average. Especially, there was almost no rain in tuber enlargement period (from mid-May to mid-June). On the other hand, the total rainfall in of Cheong-ju was is similar to those in last 5 years average. Inorganic components including K, Ca and Mg and plant growth factors such as plant length, stem length, leaf area index and plant biomass were investigated. Tuber yields in both areas were investigated at harvest. Growth period of plants was is longer in Cheong-ju than that in Gangneung. Contents of all inorganic components were higher in plants grown in Cheong-ju than in Gangneung. The results were attributed to higher production of plant biomass in Cheong-ju. Considering the results, severe drought stress conditions in Gangneung accelerated plant aging and resulted in low plant growth. Although total yield was greatly reduced under drought stress the rate of commercial yield was is not significantly different with non-drought conditions.