• 지질공학
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• 제34권2호
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• pp.329-338
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• 2024

본 연구에서는 인제 지역에 대해 표준강수지수(SPI), 수문학적 가뭄지수(SDI)를 이용한 가뭄 평가를 수행하였다. 가뭄 분석을 위한 기초자료(강우, 유량) 자료 등을 통해서 월별 유량 비율 등을 검토하였고, 인제군 유역 인근의 강수 및 수위/유량 관측소를 활용하여 기상학적 가뭄 및 수문학적 가뭄분석을 진행한 결과 모든 가뭄지수(SPI, SDI)에서 공통적으로 2014년에 발생한 가뭄이 2017년까지 지속되었던 것으로 분석되었다. 지속기간 12개월의 수문기상자료를 활용하여 가뭄지수를 산정하여 분석한 경우, 심한가뭄 지속기간이 24개월 정도 지속되었던 것으로 확인되었으며 따라서 가뭄으로 인한 피해가 극심했을 것으로 평가된다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.166-166
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• 2023

Compound hazards (CHs) are two or more extreme climate events combined which occur simultaneously in the same region at the same time. Compared to individual hazards, the combination of hazards that cause CHs can result in greater economic losses and deaths. While several extreme climate events have been recorded across Asia for the past decades, many studies have only focused on a single hazard. In this study, we assess the spatiotemporal pattern of dry compound hazards which includes drought, heatwave, fire and wind across Asia for the last 42 years (1980-2021) using the historical data from ERA5 Reanalysis dataset. We utilize a daily spatial data of each climate event to assess the occurrence of such compound hazards on a daily basis. Heatwave, fire and wind hazard occurrences are analyzed using daily percentile-based thresholds while a pre-defined threshold for SPI is applied for drought occurrence. Then, the occurrence of each type of compound hazard is taken from overlapping the map of daily occurrences of a single hazard. Lastly, a multivariate assessment are conducted to quantify the occurrence frequency, hotspots and trends of each type of compound hazard across Asia. By conducting a multivariate analysis of the occurrence of these compound hazards, we identify the relationships and interactions in dry compound hazards including droughts, heatwaves, fires, and winds, ultimately leading to better-informed decisions and strategies in the natural risk management.

• 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.

• 한국농공학회논문집
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• 제62권2호
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• pp.63-73
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• 2020

Drought is considered as a devastating hazard that causes serious agricultural, ecological and socio-economic impacts worldwide. Fundamentally, the drought can be defined as temporarily different levels of inadequate precipitation, soil moisture, and water supply relative to the long-term average conditions. From no unified definition of droughts, droughts have been divided into different severity level, i.e., moderate drought, severe drought, extreme drought and exceptional drought. The drought severity classification defined the ranges for each indicator for each dryness level. Because the ranges of the various indicators often don't coincide, the final drought category tends to be based on what the majority of the indicators show and on local observations. Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used as a index of the droughts occurring rapidly in a short period of time from studies showing a more sensitive and fast response to drought compared to Standardized Precipitation Index (SPI), and Palmer Drought Severity Index (PDSI). However, ESI is difficult to provide an objective drought assessment because it does not have clear drought severity classification criteria. In this study, U.S. Drought Monitor (USDM), the standard for drought determination used in the United States, was applied to ESI, and the Percentile method was used to classify drought categories by severity. Regarding the actual 2017 drought event in South Korea, we compare the spatial distribution of drought area and understand the USDM-based ESI by comparing the results of Standardized Groundwater level Index (SGI) and drought impact information. These results demonstrated that the USDM-based ESI could be an effective tool to provide objective drought conditions to inform management decisions for drought policy.

• 한국농공학회논문집
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• 제60권6호
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• pp.121-131
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• 2018

Climate change has caused changes in environmental factors that have a direct impact on agriculture such as temperature and precipitation. The meteorological disaster that has the greatest impact on agriculture is drought, and its forecasts are closely related to agricultural production and water supply. In the case of terrestrial data, the accuracy of the spatial map obtained by interpolating the each point data is lowered because it is based on the point observation. Therefore, acquisition of various meteorological data through satellite imagery can complement this terrestrial based drought monitoring. In this study, Evaporative Stress Index (ESI) was used as satellite data for drought determination. The ESI was developed by NASA and USDA, and is calculated through thermal observations of GOES satellites, MODIS, Landsat 5, 7 and 8. We will identify the difference between ESI and other satellite-based drought assessment indices (Vegetation Health Index, VHI, Leaf Area Index, LAI, Enhanced Vegetation Index, EVI), and use it to analyze the drought in South Korea, and examines the applicability of ESI as a new indicator of agricultural drought monitoring.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.341-341
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• 2017

Abiotic stress adversely affects crop growth worldwide. Drought of the major abiotic stresses have the most significant impact on all of the crop. The main objective of this study was to assess the effects of drought stress on photochemical performance and vitality of maize (Zea mays L.). The photochemical characteristics were analyzed in the context of period of drought stress during the maize growth. Drought experiment was carried out for four weeks, thereafter, the drought treated maize was re-watered. The polyphasic OJIP fluorescence transient was used to evaluate the behavior of photosystem II (PSII) and photosystem I (PSI) during the entire experiment period. In drought stress, the performance Index (PI) level was reached earlier when compared to the controls. For the screening of drought stress tolerance the drought factor index (DFI) of each variety was calculated as follow DFI= log(A) + 2log(B). All the fourteen cultivars show DFI ranged from -0.69 to 0.30, meaning less useful in selection of drought tolerant cultivars. PI and electron transport flux values of fourteen cultivars were to indicate reduction of photosynthetic performance during the early vegetative stage under drought stress. In conclusion, DFI and energy flux parameters can be used as photochemical and physiological index.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.

• 한국수자원학회논문집
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• 제51권7호
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• pp.617-627
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• 2018

본 연구에서는 미래 기간의 극한 가뭄을 분석하기 위하여 RCP 시나리오 기반의 CMIP5 GCMs 강우자료(2011~2099)를 활용하였으며, 과거 관측치의 경우 기상청 ASOS자료(1976~2005)를 이용하여, 미래 가뭄 평가를 하였다. 한반도 5대강(한강, 낙동강, 금강, 섬진강, 영산강)을 대상으로 연평균 강우량, 무강우일수, Drought Spell, Average Severity를 비교 분석한 결과, 가장 심한 수준의 미래 가뭄을 전망하는 GCM은 CMCC-CMS, IPSL-CM5A-LR, IPSL-CM5A-MR로 나타났으며, 보통 수준의 미래 가뭄을 전망하는 GCM은 HadGEM2-CC, CMCC-CM, HadGEM2-ES, 상대적으로 미래의 가뭄을 약하게 전망하는 GCM은 CESM1-CAM5, MIROC-ESM-CHEM, CanESM2로 선정되었다. 극한 가뭄을 전망하는 모델로는 CMCC-CMS, 가장 약한 가뭄을 전망하는 모델은 CanESM2를 선정하여 한반도에 적용한 결과 CMCC-CMS는 과거 대비 가뭄의 심도 및 빈도가 증가하는 것을 확인할 수 있었으며, CanESM2는 과거 대비 심도는 증가하였지만 발생빈도는 적어지는 것을 확인할 수 있었다. 본 연구 결과는 미래 극한 가뭄 평가에 있어서 합리적인 기후변화 시나리오를 선정하는 기초 자료로 활용될 것으로 판단된다.

• 한국토양비료학회지
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• 제46권6호
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• pp.434-444
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• 2013

In order to evaluate drought risk at upland according to climate change scenario (RCP8.5), we have carried out the simulation using agricultural water balance estimation model, called AFKAE0.5, at 66 weather station sites in 2020, 2046, 2050, 2084, and 2090. Total Drought Risk Index between the first month (f) and last month (l) (TDRI(f/l)) and maximum continuous drought risk index (MCDRI(f/l)) were defined as the index for analyzing pattern and strength of drought simulated by the model. Based on distribution maps of MCDRI (1/12), drought strength was predicted to be most severe in 2084 for all regions. Some regions showed severe risk of drought meaning over 20 days of MCDRI (1/12) in the other years, while MCDRI (1/12) in other regions did not reach 5 days. Even though maximum value of TDRI (1/12) in 2090 was greater than in 2050, more severe drought risk in 2050 than in 2090 was predicted based on MCDRI (4/6). It implies that drought risk should be assessed for each crop with its own growing season.

• 대한토목학회논문집
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• 제34권1호
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• pp.145-153
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• 2014

현재 국내외적으로 다양한 가뭄지수들이 개발과 더불어 가뭄평가를 위한 다양한 기준이 개발되고 있다. 가뭄지수를 이용하여 가뭄의 시작, 강도 및 종료 시점을 정의할 경우, 일반적으로 특정 기준값(threshold)에 근거한 해석이 이루어지고 있으나, 이는 실제 가뭄을 평가하는데 불확실성을 가중시키는 원인으로 작용하고 있다. 따라서 본 연구에서는 기존의 가뭄지수 기반의 가뭄판단 시 적용되어져 왔던 특정한 기준값에 근거한 해석이 아닌, 기상학적 가뭄발생의 주된 원인 중 하나인 월강수량 자료에 내재되어 있는 특징을 최대한 활용하고자 은닉 마코프 모형(Hidden Markov Model, HMM) 기반의 확률론적 가뭄해석기법을 제안하였다. 그 결과, 본 연구에서 제시한 HMM 기반의 확률론적 가뭄해석기법은 기존의 다양한 가뭄지수를 적용한 가뭄해석과 비교하여 기상학적 측면에서의 가뭄판단의 명확한 기준 제시 및 가뭄발생의 원인을 규명하는 데 있어 체계적으로 불확실성을 감안한 해석이 가능하였다.