• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.231-238
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• 2017

Water supply safety index plays an important role on assessing the water supply capacity of hydrologic system. Due to the absence of consistent guidance, however, practical problems have been brought up on data period used for dam design and performance evaluation. Therefore, this study employed bivariate drought frequency analysis which is able to consider drought severity and duration simultaneously, in order to evaluate water supply capacity of multi-purpose dams. Drought characteristics were analyzed based on the probabilistic approach, and water supply capacity of five multi-purpose dams in Korea (Soyang River, Chungju, Andong, Daecheong, Seomjin River) were evaluated under the specific drought conditions. As a result, it would be possible to have stable water supply with their own inflow during summer and fall, whereas water shortage would occur even under the 1-year return period drought event during spring and winter due to low rainfall.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.129-136
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• 2020

Drought is an environmental disaster typically defined as an unusual deficiency of water supply over an extended period. Satellite remote sensing provides an alternative approach to monitoring drought over large areas. In this study, we monitored drought patterns over about 30 years (1985-2015), using satellite imagery of Lake Soyang, Gangwondo, South Korea. Landsat images were classified using ISODATA, maximum likelihood analysis, and an artificial neural network to derive the lake area. In addition, the relationship between areas of Lake Soyang and the Standardized Precipitation Index (SPI) was analyzed. The results showed that the artificial neural network was a better method for determining the area of the lake. Based on the relationship between the SPI value and changes in area, the R² value was 0.52. This means that the area of the lake varied depending on SPI value. This study was able to detect and monitor drought conditions in the Lake Soyang area. The results of this study are used in the development of a regional drought monitoring program.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.839-852
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• 2018

The purpose of this study is to predict monthly agricultural reservoir storage by developing weather data-based Multiple Linear Regression Model (MLRM) with precipitation, maximum temperature, minimum temperature, average temperature, and average wind speed. Using Naïve-Bayes classification, total 1,559 nationwide reservoirs were classified into 30 clusters based on geomorphological specification (effective storage volume, irrigation area, watershed area, latitude, longitude and frequency of drought). For each cluster, the monthly MLRM was derived using 13 years (2002~2014) meteorological data by KMA (Korea Meteorological Administration) and reservoir storage rate data by KRC (Korea Rural Community). The MLRM for reservoir storage rate showed the determination coefficient ($R^2$) of 0.76, Nash-Sutcliffe efficiency (NSE) of 0.73, and root mean square error (RMSE) of 8.33% respectively. The MLRM was evaluated for 2 years (2015~2016) using 3 months weather forecast data of GloSea5 (GS5) by KMA. The Reservoir Drought Index (RDI) that was represented by present and normal year reservoir storage rate showed that the ROC (Receiver Operating Characteristics) average hit rate was 0.80 using observed data and 0.73 using GS5 data in the MLRM. Using the results of this study, future reservoir storage rates can be predicted and used as decision-making data on stable future agricultural water supply.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.1-11
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• 2022

Recently, climate change has been regarded as a major cause of large-scale forest fires worldwide, and there is concern that more frequent and severe forest fires will occur due to the level of greenhouse gas emissions. In this study, the daily Keetch and Byram Drought Index (KBDI) of the Baekdudaegan in Chungcheong region including Sobaeksan, Songnisan, and Woraksan National Parks were calculated to assess effect of climate change on the forest fire potential- severity of annual maximum KBDI and frequency of high KBDI days. The present (2000~2019) and future KBDI(2021~2040, 2041~2060, 2081~2090) were calculated based on the meteorological observation and the ensemble regional climate model of the SSP1-2.6 and SSP5-8.5 scenarios with a spatial resolution of 1-km provided by Korea Meteorological Administration(KMA). Under the SSP5-8.5 scenario, 6.5℃ increase and 14% precipitation increase are expected at the end of the 21st century. The severity of maximum daily KBDI increases by 48% (+50mm), and the frequency of high KBDI days (> 100 KBDI) increases more than 100 days, which means the high potential for serious forest fires. The analysis results showed that Songnisan National Park has the highest potential for forest fire risk and will continue to be high in intensity and frequency in the future. It is expected that the forest vulnerability of the Baekdudaegan in the Chungcheong region will greatly increase and the difficulty in preventing and suppressing forest fires will increase as the abundance of combustible materials increases along with climate changes.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1847-1859
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• 2022

Wildfires in North Korea can have a directly or indirectly affect South Korea if they go south to the Demilitarized Zone. Therefore, this study calculates the regional optimized Forest Fire Danger Index (FFDI) based on Local Data Assessment and Prediction System (LDAPS) weather data to obtain forest fire risk in North Korea, and applied it to the cases in Goseong-gun and Cheorwon-gun, North Korea in April 2022. As a result, the suitability was confirmed as the FFDI at the time of ignition corresponded to the risk class Extreme and Severe sections, respectively. In addition, a qualitative comparison of the risk map and the soil moisture map before and after the wildfire, the correlation was grasped. A new forest fire risk index that combines drought factors such as soil moisture, Standardized Precipitation Index (SPI), and Normalized Difference Water Index (NDWI) will be needed in the future.

• Journal of Forest and Environmental Science
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• v.34 no.3
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• pp.224-234
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• 2018

An efficient method to select drought tolerant Korean native plants using in vitro culture system was established in this study. While the plant growths and root inductions of each plant were proportionately affected by concentrations of mannitol on in vitro culturing seven plant species to test tolerance to osmotic stress, growth index (GI) and number of root induction of Chrysanthemi zawadskii var. latilobum and Dianthus chinensis var. semperflorens plantlets were higher than the others in 125mM mannitol. In test with polyethylene glycol (PEG), plantlets of C. zawadskii var. latilobum and D. chinensis var. semperflorens showed higher GI and number of root induction than the others in 33.3mM. On testing whether the well grown plants under osmotic stress are tolerant to virtual drought stress, there were significant differences in the withering rates of C. zawadskii var. latilobum and D. chinensis and those of were Aster yomena and Centaurea cyanus after 12 days without watering. It was found that significantly lower stomata numbers were shown in both drought tolerant plants than the sensitive plants. Averages of the stomata circumferences and the stomata area in the plantlets of the tolerant species were larger than those of the sensitive plants D. chinensis var. semperflorens showed the lowest transpiration level per unit area. The highest stomatal area per unit area was found in C. zawadskii, followed by D. chinensis var. semperflorens, Aster yomena and C. cyanus. In conclusion, C. zawadskii var. latilobum and D. chinensis var. semperflorens were more tolerant to drought than other two species. Furthermore in vitro selection was successfully used to screen drought tolerance species of native plant species.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.295-295
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• 2022

강우 변동성과 기온의 증가 추세로 전 세계 여러 지역에서 가뭄의 빈도, 지속기간, 심각도, 영향면적이 증가하고 있다. 기후변화로 인한 극심한 가뭄은 담수 생태계에 심각한 결과를 가져올 수 있으며, 이는 중대한 사회적 경제적 영향을 미칠 수 있다. 본 연구에서는 낙동강 수질오염총량관리 단위유역에서 기상학적 가뭄 발생 시 하천 수생태계가 받는 수질 스트레스 위험도가 식별된다. 기상학적 가뭄은 표준강수지수(SPI)로 한정되며 하천 수질은 BOD로 한정되어 분석이 수행된다. 또한, 본 연구에서는 하천의 수질 스트레스를 식별하기 위하여 가뭄 시 환경영향 지수인 Environmental Drought Condition Index-water quality(EDCI-wq)를 제안한다. EDCI-wq는 기상학적 가뭄이 발생하였을 때 수생태계가 평상시 대비 스트레스를 받을 가능성을 표현한 지수이다. 최종적으로 산정된 EDCI-wq를 기반으로 하천 구간별로 관심, 주의, 경계, 심각 단계 구분 기준을 마련하여 기상학적 가뭄 발생 시 하천 수생태계가 받는 수질 스트레스를 단계적으로 식별할 수 있는 수질 스트레스 위험도 지도가 작성된다.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.931-946
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• 2017

The purpose of this study is to observe and analyze soil moisture conditions with high resolution and to evaluate its application feasibility to agriculture. For this purpose, we used three Landsat-8 OLI (Operational Land Imager)/TIRS (Thermal Infrared Sensor) optical and thermal infrared satellite images taken from May to June 2015, 2016, and 2017, including the rural areas of Jeollabuk-do, where 46% of agricultural areas are located. The soil moisture conditions at each date in the study area can be effectively obtained through the SPI (Standardized Precipitation Index)3 drought index, and each image has near normal, moderately wet, and moderately dry soil moisture conditions. The temperature vegetation dryness index (TVDI) was calculated to observe the soil moisture status from the Landsat-8 OLI/TIRS images with different soil moisture conditions and to compare and analyze the soil moisture conditions obtained from the SPI3 drought index. TVDI is estimated from the relationship between LST (Land Surface Temperature) and NDVI (Normalized Difference Vegetation Index) calculated from Landsat-8 OLI/TIRS satellite images. The maximum/minimum values of LST according to NDVI are extracted from the distribution of pixels in the feature space of LST-NDVI, and the Dry/Wet edges of LST according to NDVI can be determined by linear regression analysis. The TVDI value is obtained by calculating the ratio of the LST value between the two edges. We classified the relative soil moisture conditions from the TVDI values into five stages: very wet, wet, normal, dry, and very dry and compared to the soil moisture conditions obtained from SPI3. Due to the rice-planing season from May to June, 62% of the whole images were classified as wet and very wet due to paddy field areas which are the largest proportions in the image. Also, the pixels classified as normal were analyzed because of the influence of the field area in the image. The TVDI classification results for the whole image roughly corresponded to the SPI3 soil moisture condition, but they did not correspond to the subdivision results which are very dry, wet, and very wet. In addition, after extracting and classifying agricultural areas of paddy field and field, the paddy field area did not correspond to the SPI3 drought index in the very dry, normal and very wet classification results, and the field area did not correspond to the SPI3 drought index in the normal classification. This is considered to be a problem in Dry/Wet edge estimation due to outlier such as extremely dry bare soil and very wet paddy field area, water, cloud and mountain topography effects (shadow). However, in the agricultural area, especially the field area, in May to June, it was possible to effectively observe the soil moisture conditions as a subdivision. It is expected that the application of this method will be possible by observing the temporal and spatial changes of the soil moisture status in the agricultural area using the optical satellite with high spatial resolution and forecasting the agricultural production.

• Korean Journal of Environmental Biology
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• v.34 no.4
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• pp.223-232
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• 2016

Drought is one of important environmental stress for plant. Drought has deleterious effect to plant growth including maize (Zea mays L.) such as vegetative and/or reproductive growth, root extension, photosynthesis efficiency, flowering, anthesis-silking interval (ASI), fertilization, and grain filling. In this study, we screened drought tolerant maize in 21 cultivars from different sources, sixteen NAM parent lines (B73, CML103, CML228, CML247, CML277, CML322, CML333, CML69, Ki11, Ki3, Ky21, M37W, Mo18w, NC350, Oh43 and Tx303), four Korean hybrids (Cheongdaok, Gangdaok, Kwangpyeongok and Pyeonganok) and one Southeast Asian genotype (DK9955). Drought stress (DS) index was evaluated with leaf rolling score at seedling stage and ASI at silking date. The leaf rolling scoring of CML228, DK9955 and Ki11 were determined 1.28, 1.85, 1.86, respectively. However, M37W, Kwangpyeongok, B73 and NC350 were determined over the 3. ASI analysis revealed that CML228, CML103, Cheongdaok, NC350, B73, CML322, Kwangpyeongok and Ki11 are represented less than 5 days under DS and less than 3 days of difference between DS and well-watered (WW), but CML69, Ki3, Pyeonganok, M37W, Mo18w and Gangdaok were represented more than 10 days under DS and more than 8 days of difference between DS and WW. Multi-Dimensional Scaling (MDS) analysis determined CML228, Ki11, and CML322 were regarded as drought tolerance cultivars. Eventually, Ki11 showed genetic similarity with Korean cultivars by QTL analysis and MDS analysis. Ki11 has a potential for development of drought tolerance maize with Korean cultivars.