• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.393-402
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• 2023

Drought, which has been increasing in frequency and magnitude due to recent abnormal weather events, poses severe challenges in various sectors. To address this issue, it is important to develop technologies for drought monitoring, forecasting, and response in order to implement effective measures and safeguard the ecological health of aquatic systems during water scarcity caused by drought. This study aimed to predict water quality fluctuations during drought periods by integrating the watershed model HSPF and the water quality model QUAL-MEV. The researchers examined the SPI and RCP 4.5 scenarios, and analyzed water quality changes based on flow rates by simulating them using the HSPF and QUAL-MEV models. The study found a strong correlation between water flow and water quality during the low flow. However, the relationship between precipitation and water quality was deemed insignificant. Moreover, the flow rate and SPI6 exhibited different trends. It was observed that the relationship with the mid- to long-term drought index was not significant when predicting changes in water quality influenced by drought. Therefore, to accurately assess the impact of drought on water quality, it is necessary to employ a short-term drought index and develop an evaluation method that considers fluctuations in flow.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.3
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• pp.119-131
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• 2010

Drought is one of disaster causing factors to produce severe damage in the World because drought is destroyed to the ecosystem as well as to make difficult the economy of the drought area. This study, using Palmer Drought Severity Index carries out correlation analysis with sea surface temperatures. Comparative analysis carries out by calculated Palmer Drought Severity Index and past drought occurrence year. Result of comparative analysis, PDSI indexes were in accord with the past drought. Cluster analysis for correlation analysis carries out using precipitation and temperature that is input datas palmer drought severity index, and the result of cluster analysis was classified as 6. Also, principal component carries out using result of cluster analysis. 14 principal component analyze out through principal component analysis. Using analyzed 14 principal component carries out correlation analysis with sea surface temperature that is delay time from 0month until 11month. Correlation analysis carries out sea surface temperatures and calculated cycle component of the low frequency through Wavelet Transform analysis form principal component. Result of correlation analysis, yang(+) correlation is bigger than yin(-) correlation. It is possible to check similar correlation statistically the area of sea surface temperature with sea surface temperature in the Pacific. Forecasting possibility of the future drought make propose using sea surface temperature.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.583-595
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• 2002

The purposes of this study are to perform the management and monitoring of droughts for Mokpo area via the monthly Palmer index(PDSI), the data is obtained from the Mokpo meteorological station, and the used data are in the period of 1906 to 1999. Monthly Palmer index is classified into 7 stochastic classes and its dynamic change of monthly transition probability estimated by Markov chain is investigated. We also estimate the steady state probability of the classified PDSI. The 4th class shows the highest frequency of 49.6% out of 7 classes and the 7th class which is the most extreme drought show that a stochastic transition probability is more or less larger than an empirical one. Also, we found that the monthly steady state probability could be used for the forecasting of changing pattern of drought magnitude for the study area.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.691-701
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• 2017

The objective of this study is to evaluate the long-term drought outlook information based on long-term forecast data for the 2015 drought event. In order to estimate the Standardized Precipitation Index (SPI) for different durations (3-, 6-, 9-, 12-months), we used the observation precipitation of 59 Automated Synoptic Observing System (ASOS) sites, forecast and hindcast data of GloSea5. The Receiver Operating Characteristic (ROC) analysis and statistical analysis (Correlation Coefficient, CC; Root Mean Square Error, RMSE) were used to evaluate the utilization of drought outlook information for the forecast lead-times (1~6months). As a result of ROC analysis, ROC scores of SPI(3), SPI(6), SPI(9) and SPI(12) were estimated to be over 0.70 until the 2-, 3-, 4- and 5-months. The CC and RMSE values of SPI(3), SPI(6), SPI(9) and SPI(12) for forecast lead-time were estimated as (0.60, 0.87), (0.72, 0.95), (0.75, 0.95) and (0.77, 0.89) until the 2-, 4-, 5- and 6-months respectively.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.427-436
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• 2020

It is uncertain how global climate change will influence future drought characteristics over the Korean peninsula. This study aims to project the future droughts using climate change and land use change scenarios over the Korean peninsula with the land surface modeling system, i.e., Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro). The Representative Concentration Pathways (RCPs) 2.6 and 8.5 are used as future climate scenarios and the Shared Socio-economic Pathways (SSPs), specifically SSP2, is adopted for the land use scenario. The using Threshold Level Method (TLM), we identify future hydrological and ecological drought events with runoff and Net Primary Productivity (NPP), respectively, and assess drought characteristics of durations and intensities in different scenarios. Results show that the duration of drought is longer over RCP2.6-SSP2 for near future (2031-2050) and RCP8.5-SSP2 (2080-2099) for the far future for hydrological drought. On the other hand, RCP2.6-SSP2 for the far future and RCP8.5-SSP2 for the near future show longer duration for ecological drought. In addition, the drought intensities in both hydrological and ecological drought show different characteristics with the drought duration. The intensity of the hydrological droughts was greatly affected by threshold level methods and RCP2.6-SSP2 for far future shows the severest intensity. However, for ecological drought, the difference of the intensity among the threshold level is not significant and RCP2.6-SSP2 for near future and RCP2.6-SSP2 for near future show the severest intensity. This study suggests a possible future drought characteristics is in the Korea peninsula using combined climate and land use changes, which will help the community to understand and manage the future drought risks.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.386-386
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• 2019

가뭄은 홍수와 더불어 주요한 자연재해로 댐이나 저수지의 저수량 저하에 따른 여러 피해를 야기한다. 특히, 용수의 대부분을 댐에서 공급받는 우리나라의 특성상 용수공급중단 등의 큰 피해를 야기할 가능성이 있다. 그러나. 기상학적 가뭄이 널리 사용되고 있는 것에 비하여 댐과 저수지의 가뭄은 예측의 난해함을 이유로 상대적으로 연구되지 않고 있으며, 현재 저수량을 기준으로 하여 소극적인 가뭄대응만이 이루어지고 있다. 이에 본 연구에서는 댐과 저수지 가뭄의 대응시간을 확보하고 수자원의 효율적인 활용을 위하여 댐 저수지 가뭄예측을 위한 연구를 수행하였다. 이를 위하여 기상학적 가뭄에 사용되어진 표준강수지수(SPI)와 동일한 개념을 댐 물수지에 적용한 표준물수지지수(Standardzied Balanced Index; SBI)를 제안하였다. 또한, 산정된 물수지 현황과 현저수량과 인공신경망을 활용하여 향후 댐의 저수량을 예측하기 위한 모형을 구축하였으며, 그 적용성을 검증하였다. 연구결과에 따르면 1개월 단위로 향후 댐의 저수량 경향성을 예측할 수 있는 것으로 나타났다.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.71-83
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• 2020

Resilience is the capacity to maintain essential services under a range of circumstances from normal to extreme. It is achieved through the ability of assets, networks, systems and management to anticipate, absorb and recover from disturbance. It requires adaptive capacity in respect of current and future risks and uncertainties as well as experience to date. The agricultural infrastructures with high resilience can not only reduce the size of the disaster relatively, but also minimize the loss by reducing the time required for recovery. This study aims to evaluate the most suitable drought countermeasures with the analysis of various resilience indices by predicting future agricultural water shortage under land use and climate change scenarios for agricultural areas in Jeju Island. The results showed that the permanent countermeasure is suitable than the temporary countermeasures as drought size and the cost required for recovery increase. Wide-area water supply system, which is a kind of water grid system, is identified as the most advantageous among countermeasures. It is recommended to evaluate the capability of agricultural infrastructure against drought with the various Resilience Indices for reliable assessment of long-term effect.

• Atmosphere
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• v.31 no.5
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• pp.637-656
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• 2021

The United States has been known as the world's major producer of crops such as wheat, corn, and soybeans. Therefore, using meteorological long-term forecast data to project reliable crop yields in the United States is important for planning domestic food policies. The current study is part of an effort to improve the seasonal predictability of regional-scale precipitation across the United States for estimating crop production in the country. For the purpose, a dynamic downscaling method using Weather Research and Forecasting (WRF) model is utilized. The WRF simulation covers the crop-growing period (March to October) during 2000-2020. The initial and lateral boundary conditions of WRF are derived from the Pusan National University Coupled General Circulation Model (PNU CGCM), a participant model of Asia-Pacific Economic Cooperation Climate Center (APCC) Long-Term Multi-Model Ensemble Prediction System. For bias correction of downscaled daily precipitation, empirical quantile mapping (EQM) is applied. The downscaled data set without and with correction are called WRF_UC and WRF_C, respectively. In terms of mean precipitation, the EQM effectively reduces the wet biases over most of the United States and improves the spatial correlation coefficient with observation. The daily precipitation of WRF_C shows the better performance in terms of frequency and extreme precipitation intensity compared to WRF_UC. In addition, WRF_C shows a more reasonable performance in predicting drought frequency according to intensity than WRF_UC.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.743-750
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• 2008

Due to unusual climate change and global warming, drought and flood happen frequently not only in Korea but also in all over the world. It leads to the serious damages and injuries in urban areas as well as rural areas. Since the concentration time is short and the flood flows increase urgently in urban stream basin, the chances of damages become large once heavy storm occurs. A decision support system for flood forecasting and warning in urban stream is developed as an alternative to alleviate the damages from heavy storm. It consists of model base management system based on ANFIS (Adaptive Neuro Fuzzy Inference System), database management system with real time data building capability and user friendly dialog generation and management system. Applying the system to the Tanceon river basin, it can forecast and warn the stream flows from the heavy storm in real time and alleviate the damages.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.1041-1053
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• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.