• Atmosphere
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• v.22 no.2
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.815-831
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• 2021

Drought forecasting is crucial to minimize the damage to food security and water resources caused by drought. Satellite-based drought research has been conducted since 1980s, which includes drought monitoring, assessment, and prediction. Unlike numerous studies on drought monitoring and assessment for the past few decades, satellite-based drought forecasting has gained popularity in recent years. For successful drought forecasting, it is necessary to carefully identify the relationships between drought factors and drought conditions by drought type and lead time. This paper aims to provide an overview of recent research trends and challenges for satellite-based drought forecasts focusing on lead times. Based on the recent literature survey during the past decade, the satellite-based drought forecasting studies were divided into three groups by lead time (i.e., short-term, sub-seasonal, and seasonal) and reviewed with the characteristics of the predictors (i.e., drought factors) and predictands (i.e., drought indices). Then, three major challenges-difficulty in model generalization, model resolution and feature selection, and saturation of forecasting skill improvement-were discussed, which led to provide several future research directions of satellite-based drought forecasting.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.743-750
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• 2019

Most of the water supply facilities that use rivers as sources do not have monitoring facilities such as precipitation and stream flow measurement, and there is no judgment standard for drought response such as water intake control in river flow during dry season. In addition, it was confirmed that local government officials, who deal with actual drought work, have limitations in applying the drought index (SPI, PDSI, etc.) and diffusion models that have been proposed so far in advance. Therefore, in this study, the drought prediction system was constructed to determine the number of water-intake available days using SWAT (Soil and Water Assessment Tool) and the water supply network from the intake source to the beneficiary area, suggesting the drought spreading time and space.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.55-63
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• 2018

This study analyzed the applications of near real-time drought monitoring using satellite rainfall for the Korean Peninsula and un-gaged basins. We used AWS data of Yongdam-Dam, Hoengseong-Dam in Korea area, the meteorological station of Nakhon Rachasima, Pak chong for test-bed to evaluate the validation and the opportunity for un-gaged basins. In addition, we calculated EDI (Effective doought index) using the stations and co-located PERSIANN-CDR, TRMM (Tropical Rainfall Measurement Mission) TMPA (The TRMM Multisatellite Precipitation Analysis), GPM IMERG (the integrated Multi-satellitE Retrievals for GPM) rainfall data and compared the EDI-based station data with satellite data for applications of drought monitoring. The results showed that the correlation coefficient and the determination coefficient were 0.830 and 0.914 in Yongdam-dam, and 0.689 and 0.835 in Hoengseng-Dam respectively. Also, the correlation coefficient were 0.830, 0.914 from TRMM TMPA datasets and compasion with 0.660, 0.660 based on PERSIANN-CDR and TRMM data in nakhon and pakchong station. Our results were confirmed possibility of near real-time drought monitoring using EDI with daily satellite rainfall for un-gaged basins.

• Journal of Korea Water Resources Association
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• v.44 no.8
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• pp.639-652
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• 2011

In this study, the suitability of drought indices was analyzed using the quantified drought records from official reports, newspapers and drought indices estimated using precipitation and air temperature data of 69 weather stations from 1973 to 2009. Test statistics of the suitability of meteorological drought indices were evaluated using the ROC analysis. Results demonstrated that PN shows the best relationships with drought records. SPI3 and Deciles Distribution Ratio also show good relationships with drought records and their variability according to the administrative divisions is relatively small. Results of the analysis of the spatial and temporal variability of drought and the accuracy of the drought indices can be used to evaluate the accuracy of drought indices in drought monitoring and prediction, and to select the best index in drought management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.981-987
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• 2017

Jeju Island is a volcanic island which has a large permeability. Groundwater is a major water resources and its proper management is essential. Especially, there is a multilevel restriction due to the groundwater level decline during a drought period to protect sea water intrusion. Preliminary countermeasure using long-term groundwater level prediction is necessary to use agricultural groundwater properly. For this purpose, the monthly groundwater level prediction technique by Artificial Neural Network model was developed and applied to the representative monitoring wells. The monthly prediction model showed excellent results for training and test periods. The continuous groundwater level prediction model also developed, which used the monthly forecasted values adaptively as input data. The characteristics of groundwater declines were analyzed under extreme cases without precipitation for several months.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.82-82
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• 2021

전 세계적으로 가뭄은 농업·식량안보·수자원관리·생태계 등 다양한 분야에서 부정적인 영향을 미치고 있다. 일반적으로 가뭄은 강수량의 부족으로 발생하고, 지표수와 지하수의 가용성이 제한됨에 따라 작물생산 및 사회·경제적으로 피해가 발생한다. 이러한 영향은 특정 가뭄 모니터링 및 조기 경보와 관련하여 가뭄 지표를 결정할 때 중요한 고려사항이다. 가뭄을 분석하기 위해서는 가뭄 지표를 적용하여 정확하게 반영하고 나타내는 것이 중요하다. 가뭄의 특성을 객관적으로 정량화하기 어렵기 때문에 다양한 지표와 계산을 통한 가뭄 모니터링 및 분석 기술이 필요하며, 강수량, 토양수분, 증발산량 및 식생과 관련하여 가뭄 지표가 개발되었다. 본 연구에서는 혼합 가뭄 지표 (Drought Indicator Blends) 활용하여 우리나라의 가뭄을 분석하였다. 혼합 가뭄 지표는 NOAA (National Oceanic and Atmospheric Administration)의 기후 예측 센터 (Climate Prediction Center, CPC)에서 여러 가뭄 지수를 단기 또는 장기로 구분하여 통합, 개발되었다. 단기 및 장기 혼합 제품은 PDSI (Palmer Drought Severity Index), Z-Index, SPI (Standardized Precipitation Index)를 결합하여 가뭄을 추정한다. 혼합 가뭄 지표는 해당 지역의 단기 및 장기 가뭄을 이해하는데 유용하게 활용할 수 있으며, 현재까지 미국에서 활발하게 연구가 진행되고 있다. 단기 지표는 비관개 농업, 토양수분 등 강수량에 밀접한 관련이 있는 가뭄과 관련되어 평가하며, 장기 지표의 경우 관개 농업, 지하수위 등 장기간 가뭄과 연관성을 가지고 있다. 단기 및 장기 혼합 가뭄 지표를 우리나라에 적용함으로써 기존 단일 가뭄 지수를 활용한 가뭄 분석 이상으로 다방면에서 효율적인 가뭄 모니터링을 할 수 있을 것이라 판단된다.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1021-1029
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• 2018

A primary objective of this study is to develop a drought forecasting technique based on groundwater which can be exploit for water supply under drought stress. For this purpose, we explored the lagged relationships between regionalized SGI (standardized groundwater level index) and SPI (standardized precipitation index) in view of the drought propagation. A regional prediction model was constructed using a NARX (nonlinear autoregressive exogenous) artificial neural network model which can effectively capture nonlinear relationships with the lagged independent variable. During the training phase, model performance in terms of correlation coefficient was found to be satisfactory with the correlation coefficient over 0.7. Moreover, the model performance was described by root mean squared error (RMSE). It can be concluded that the proposed approach is able to provide a reliable SGI forecasts along with rainfall forecasts provided by the Korea Meteorological Administration.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.163-174
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• 2017

This study developed the prototype of the system and implemented its main functions, which is the intelligent integrated agricultural water management information system and service (IaWAMISS). The developed system was designed to be able to collect, process and analyze the agricultural water information of spatially dispersed reservoirs in whole country and spatial geographic information distributed in various systems of other organizations. The system, IaWAMISS, is also possible to provide the reproduced information services in each reservoir and space units, such as agricultural water demand and supply analysis and drought prediction, to the people, experts, and policy makers. This study defined the 6 step modules to develop the system, which are to design the components of intelligent integrated information system, to derive the utilization contents of existing systems, to design the new development elements for IaWAMISS, to design the reservoir information system can be used by managers of city and county, to designate the monitoring reservoirs managed by city and county, and finally to prepare the sharing system between organizations with the existing information systems. In order to implement the prototype of the system, this study shows the results for three important functions of the system: spatial integration of reservoirs' information, data link integration between the existing systems, and intelligent analysis program development to assist decision support for agricultural water management. For the spatial integration with the reservoir water information of the Korea Rural Community Corporation, this study get IaWAMISS to receive the real-time reservoir storage information from the measurement facility installed in the municipal management reservoir. The data link integration connecting databases of the existing systems, was implemented by integrating the meteorological information of the Korea Meteorological Administration with IaWAMISS, so that the rainfall forecast data could be derived and used. For the implementation of the intelligent analysis program, this study also showed the results of analysis and prediction of agricultural water demand and supply amount, estimation of Palmer drought index, analysis of flood risk area in typhoon course region, and analysis of the storage status of reservoirs related to each storm. This study confirmed the possibility and efficiency of an useful system development through the prototype design and implementation of IaWAMISS. By solving the preliminary 6 step modules presented in this study, it is possible not only to efficiently manage water by spatial unit, but also to provide the service of information and to enhance the relevant policy and national understanding to the people.