• 한국농공학회논문집
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• 제64권4호
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• pp.11-20
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• 2022

Currently, the operation rule of agricultural reservoirs in case of drought events follows the drought forecast warning standard of agricultural water supply. However, it is difficult to preemptively manage drought in individual reservoirs because drought forecasting standards are set according to average reservoir storage ratio such as 70%, 60%, 50%, and 40%. The equal standards based on average water level across the country could not reflect the actual drought situation in the region. In this study, we proposed the improvement of drought operation rule for agricultural reservoirs based on the percentile approach using past water level of each reservoir. The percentile approach is applied to monitor drought conditions and determine drought criteria in the U.S. Drought Monitoring (USDM). We applied the drought operation rule to reservoir storage rate in extreme 2017 spring drought year, the one of the most climatologically driest spring seasons over the 1961-2021 period of record. We counted frequency of each drought criteria which are existing and developed operation rules to compare drought operation rule determining the actual drought conditions during 2016-2017. As a result of comparing the current standard and the percentile standard with SPI6, the percentile standard showed severe-level when SPI6 showed severe drought condition, but the current standard fell short of the results. Results can be used to improve the drought operation criteria of drought events that better reflects the actual drought conditions in agricultural reservoirs.

• 한국농공학회지
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• 제26권3호
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• pp.35-45
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• 1984

Generally speaking, agriculture exist in a climatic environment of uncertainty. Namely, normal rainfall value, as given by the mean values, does not exist. Thought on exists, itl does not affect like extreme Precipitation value on the part of agriculture and of others. Therefore, it is important that we measure the duration and severity index of drought caused by extreme precipitation deficit. In this purpose, this study was dealt with the calculation of drought duration and severity indexs by the method of monthly weighting coefficient. There is no quantitive definition of drought that is universally acceptable. Most of the criteria was used to identify drought have been arbitrary because a drought is a 'non-event' as opposed to a distinct event such as a flood. Therefore, confusion arises when an attempt is made to define the drought phenomenon, the calculation of duration, drought index is based on the following four fundamental question, and this study was dealt with the answers of these four questions as they related to this analytical method, as follows. First, the primary interest in this study is to be the lack of precipitation as it relates to agricultural effective rainfall. Second, the time interval was used to be month in this analysis. Third, Drought event, distinguished analytically from other event, is noted by monthly weighting coefficient method based on monthly rainfall data. Fin-ally, the seven regions used in this study have continually affected by drought on account of their rainfall deficit. The result from this method was very similar to the previous papers studied by many workers. Therefore, I think that this method is very available in Korea to identify the duration of drought, the deficit of precipitation and severity index of drought, But according to the climate of Korea exist the Asia Monsoon zone. The monthly weighting coefficient is modify a little, Because get out of 0.1-0.4 occasionally.

• 한국농공학회논문집
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• 제63권5호
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• pp.1-11
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• 2021

Soil moisture plays a critical role in hydrological processes, land-atmosphere interactions and climate variability. It can limit vegetation growth as well as infiltration of rainfall and therefore very important for agriculture sector and food protection. Recently, due to the increased damage from drought caused by climate change, there is a frequent occurrence of shortage of agricultural water, making it difficult to supply and manage stable agricultural water. Efficient water management is necessary to reduce drought damage, and soil moisture management is important in case of upland crops. In this study, soil moisture was calculated based on the water balance model, and the suitability of soil moisture data was verified through the application. The regional soil moisture was calculated based on the meteorological data collected by the meteorological station, and applied the Runs theory. We analyzed the spatiotemporal variability of soil moisture and drought impacts, and analyzed the correlation between actual drought impacts and drought damage through correlation analysis of Standardized Precipitation Index (SPI). The soil moisture steadily decreased and increased until the rainy season, while the drought size steadily increased and decreased until the rainy season. The regional magnitude of the drought was large in Gyeonggi-do and Gyeongsang-do, and in winter, severe drought occurred in areas of Gangwon-do. As a result of comparative analysis with actual drought events, it was confirmed that there is a high correlation with SPI by each time scale drought events with a correlation coefficient.

• 한국수자원학회논문집
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• 제30권1호
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• pp.55-62
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• 1997

전국적인 가뭄특성을 조사하고 '94-'95 가뭄의 심도를 기왕의 주요 가뭄과 비교평가하기 위하여 전국의 47개 소유역으로 분할한 후 강우량계열로부터 작성된 가뭄우량계열의 지역빈도분석을 실시하였다. L-모멘트법을 사용하여 적정확률분포의 매개 변수를 결정하였으며, 강우지속기간별, 재현기간별 가뭄우량을 산정하여 지속기간별 확률가뭄우량도를 작성하였다. 강우지속기간-재현기간-가뭄우량 관계를 고려하여 '94-'95 가뭄의 심도와 지역적 범위를 기왕의 주요가뭄과 비교평가하였다. 본 연구결과를 고려하여 현행 이수안전도를 평가하고 안전도 기준의 상향조정을 제안하였다.

• 한국수자원학회논문집
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• 제46권12호
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• pp.1249-1263
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• 2013

장기간의 가뭄에 의한 피해를 최소화하기 위해서는 유역에 적합한 가뭄관리 대책의 수립과 함께 미래에 발생하게 될 가뭄을 미리 예측할 수 있는 기술이 구축되어야 한다. 또한 미래의 가뭄에 대한 합리적 대응 방안을 수립하기 위해서는 가뭄의 지속기간(duration)과 심도(severity)의 정량적인 예측이 선행되어야 한다. 본 연구에서는 수문 시계열의 예측에 가장 많이 이용되고 있는 대표적인 통계학적 기법인 인공신경망 모형(Artificial Neural Network Model)과 가뭄지수를 이용하여 남한지역의 서울, 대전, 대구, 광주 등의 4개 기상관측소를 선정하여 가뭄예측을시도하였다. 가뭄 예측을 위하여 남한지역 내 선정한 기상관측소의 관측된 과거 강수량 자료를 이용하여 산정된 SPI (Standardized Precipitation Index)를 입력변수로 하여 다층 퍼셉트론(Multi Layer Perceptron) 인공신경망 모델에 적용하였으며, 매개변수 보정을 위한 학습기간으로 1976~2000년과 2001~2010년을 예측을 위한 검증기간으로 선정하여, 학습 및 예측을 시도하였다. 학습된 최적의 예측모형을 이용하여 서로 다른 선행예보시간(1~6개월)을 갖고 SPI (3), SPI (6), SPI (12)별로 가뭄을 예측하였으며, 가뭄예측 결과, SPI (3)의 경우에는 1개월 선행예보에서만 좋은 결과를 나타내었으며, SPI (6)의 경우 1~3개월 후의 가뭄을 예측하는 경우에 비교적 관측자료와 잘 일치하는 결과를 나타내었다. SPI (12)의 경우에는 약5개월 후까지의 가뭄예측에 양호한 결과를 나타내었다.

• 한국수자원학회논문집
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• 제52권4호
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• pp.279-289
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• 2019

가뭄재해는 다른 재해와 다르게 광범위한 공간에 걸쳐서 충분한 강우가 발생하기 전까지 오랜 기간 동안 발생되는 특성이 있다. 위성 영상은 시공간적으로 지속적인 강수량 관측을 제공할 수 있다. 본 연구는 위성 영상 기반의 강수자료를 활용하여 기상학적 가뭄 전망 모형을 개발하였다. PERSIANN_CDR, TRMM 3B42와 GPM IMERG 영상을 활용하여 강수 자료를 구축한 뒤, 표준강수지수(SPI)를 기반으로 기상학적 가뭄을 정의하였다. 과거의 가뭄 정보와 물리적 예측 모형 기반의 가뭄 예측 결과를 결합할 수 있는 베이지안 네트워크 기반 가뭄 예측 기법을 이용하여 확률론적 가뭄 예측 결과를 생산하였으며, 가뭄 예측결과를 가뭄 전망 의사결정 모형에 적용하여 가뭄 전망 결과를 도출하였다. 가뭄 전망 정보는 가뭄 발생, 지속, 종결, 가뭄 없음의 4단계로 구분하였다. 본 연구의 가뭄 전망 결과는 ROC 분석을 통하여 물리적 예측 모형인 다중모형 앙상블(MME)을 활용한 가뭄 전망 결과와 전망 성능을 비교하였다. 그 결과, 2~3개월 가뭄 전망에 대한 가뭄 발생 및 지속의 단계에서는 MME 모형보다 높은 전망성능을 보여주었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.151-151
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• 2019

Because drought is a complex and stochastic phenomenon in nature, statistical approaches for drought assessment receive great attention for water resource planning and management. Generally drought characteristics such as severity, duration and intensity are modelled separately. This study aims to develop a relationship between drought characteristics using a bivariate copula model. To achieve the objective, we calculated the Standardized Precipitation Index (SPI) using rainfall data at 6 rain gauge stations for the period of 1961-1999 in Jehlum River Basin, Pakistan, and investigated the drought characteristics. Since there is a significant correlation between drought severity and duration, they are usually modeled using different marginal distributions and joint distribution function. Using exponential distribution for drought severity and log-logistic distribution for drought duration, the Galambos copula was recognized as best copula to model joint distribution of drought severity and duration based on the KS-statistic. Various return periods of drought were calculated to identify time interval of repeated drought events. The result of this study can provide useful information for effective water resource management and shows superiority against univariate drought analysis.

• Journal of Ecology and Environment
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• 제44권3호
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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.

• 한국방재학회 논문집
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• 제4권2호
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• pp.61-69
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• 2004

가뭄은 주요 자연 재해 중의 하나이다. 가뭄 파악을 위하여 주로 강우량과 같은 기상자료를 주요 입력 자료로 활용하여 분석하고 있으나, 이러한 기상 자료는 한정된 기상 관측소로부터 얻어진 점자료에 해당된다. 따라서, 위성을 이용한 원격탐사 자료를 기상자료에서 포착할 수 없는 문제점을 보완하기 위한 자료로 활용할 수 있다는 확신 하에 본 연구를 진행하게 되었다. 본 연구에서는 NOAA 위성에 탑재되어 있는 AVHRR 센서로부터 얻어지는 자료를 이용하여 가뭄파악을 위한 분석을 실시하였다. NOAA/AVHRR로부터 얻어진 식생지수(NDVI)와 이로부터 얻을 수 있는 식생상태지수(VCI)를 이용하여 가뭄분석을 실시하였으며, 또한 광역적인 가뭄분석을 위해 위성자료를 이용하여 기후학적 물수지에 근거하는 간편한 방법을 제안하고 있다. 본 연구를 통하여 가뭄에 대한 시간적, 공간적 특성을 파악하는데 위성자료가 유용하게 이용될 수 있음을 알 수 있었으며, 습윤지표를 통하여 가뭄 지역도 작성이 가능함을 보여주고 있다.

• 대기
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• 제23권4호
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• pp.539-547
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• 2013

The objective of this study is to standardize the calculation method of Palmer Drought Severity Index (PDSI) for the three Drought Management Agencies (DMA) in south Korea, and to evaluate the PDSI applicability. For comparison and review of the method, the code and input data of PDSI are collected from each DMA. The calculation method is the same, but the used input data (number of meteorological stations, normal year period, Available Water Capacity (AWC) of the soil) are different. Through discussions with drought experts and literature review, the standardized method is determined. 61 stations which have the data period more than 30 years are selected. Also the normal year is fixed for 30 years and updated every 10 years. The observed AWC is utilized using GIS data. Empirical equation of PDSI is re-estimated according to domestic climate characteristics. For evaluating the standardized PDSI, past drought events are investigated and drought indices including the existing SPI and PDSI are used for comparative analysis. As results, although the accuracy of standardized PDSI through ROC analysis is lower than SPI, the newly standardized PDSI is better than existing PDSI from DMA, Also it reasonably explain the spatial drought situation through the spatial analysis.