• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.177-192
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• 2021

The Development Assistance Committee of the Organization for Economic Cooperation and Development discusses the reorganization of the five evaluation criteria of the Public Development Assistance Committee, which are used internationally, and the five evaluation criteria including adequacy, efficiency, effectiveness, impact, and sustainability when assessing public development assistance in 1991. This study is to derive alternatives by applying the evaluation criteria of the Development Assistance Committee of the Organization for Economic Cooperation and Development in the evaluation of the inclusive business program being implemented in Nepal since 2019. As a result of the study, the adequacy of Nepal's inclusive business program was consistent with continuous employment and job creation for vulnerable groups such as disabled and orphan women. Efficiency can be said to be efficient in that processes such as work order and work confirmation are made with an electronic management tool, and delivery of the result is transmitted online, saving time and cost compared to other industries. The effectiveness of this project can be said to be an effective program in that it provides high-quality jobs such as providing specialized computer graphics education for the vulnerable, such as disabled and orphan women in Nepal, and hiring graduates as employees. Sustainability is the point that KOICA's inclusive business program has enabled vulnerable groups in the existing fields of agriculture and manufacturing to engage in the computer graphics industry, and the scalability of movies, characters, education businesses, and role models in other countries.However, considering that the scale of public development assistance will continue to increase in the future, it is necessary to establish a systematic monitoring system and a recirculation system so that the project between the donor and recipient countries can continue.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.376-383
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• 2022

The current study, which consisted of two independent studies (laboratory and greenhouse), was carried out to project the hypothesis fungi-spray scheduling for leaf mold and gray leaf spot in tomato, as well as to evaluate the effect of temperature and leaf wet duration on the effectiveness of different fungicides against these diseases. In the first experiment, tomato leaves were infected with 1 × 10⁴ conidia·mL^-1 and put in a dew chamber for 0 to 18 hours at 10 to 25℃ (Fulvia fulva) and 10 to 30℃ (Stemphylium lycopersici). In farm study, tomato plants were treated for 240 hours with diluted (1,000 times) 30% trimidazole, 50% polyoxin B, and 40% iminoctadine tris (Belkut) for protection of leaf mold, and 10% etridiazole + 55% thiophanate-methyl (Gajiran), and 15% tribasic copper sulfate (Sebinna) for protection of gray leaf spot. In laboratory test, leaf condensation on the leaves of tomato plants were emerged after 9 hrs. of incubation. In conclusion, the incidence degree of leaf mold and gray leaf spot disease on tomato plants shows that it is very closely related to formation of leaf condensation, therefore the incidence of leaf mold was greater at 20 and 15℃, while 25 and 20℃ enhanced the incidence of gray leaf spot. The incidence of leaf mold and gray leaf spot developed 20 days after inoculation, and the latency period was estimated to be 14-15 days. Trihumin fungicide had the maximum effectiveness up to 168 hours of fungicides at 12 hours of wet duration in leaf mold, whereas Gajiran fungicide had the highest control (93%) against gray leaf spot up to 144 hours. All the chemicals showed an around 30-50% decrease in effectiveness after 240 hours of treatment. The model predictions in present study could be help in timely, effective and ecofriendly management of leaf mold disease in tomato.

• Research in Plant Disease
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• v.28 no.3
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• pp.113-121
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• 2022

Rice blast is a major plant disease that occurs worldwide and significantly reduces rice yields. Rice blast disease occurs periodically in Korea, causing significant socio-economic damage due to the unique status of rice as a major staple crop. A disease outbreak prediction system is required for preventing rice blast disease. Epidemiological investigations of disease outbreaks can aid in decision-making for plant disease management. Currently, plant disease prediction and epidemiological investigations are mainly based on quantitatively measurable, structured data such as crop growth and damage, weather, and other environmental factors. On the other hand, text data related to the occurrence of plant diseases are accumulated along with the structured data. However, epidemiological investigations using these unstructured data have not been conducted. The useful information extracted using unstructured data can be used for more effective plant disease management. This study analyzed news articles related to the rice blast disease through text mining to investigate the years and provinces where rice blast disease occurred most in Korea. Moreover, the average temperature, total precipitation, sunshine hours, and supplied rice varieties in the regions were also analyzed. Through these data, it was estimated that the primary causes of the nationwide outbreak in 2020 and the major outbreak in Jeonbuk region in 2021 were meteorological factors. These results obtained through text mining can be combined with deep learning technology to be used as a tool to investigate the epidemiology of rice blast disease in the future.

• Journal of Life Science
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• v.32 no.11
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• pp.872-881
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• 2022

In this study, we optimized the composition of the indole-3-acetic acid (IAA) production medium using response surface methodology on Pantoea agglomerans SRCM 119864 isolated from soil. IAA-producing P. aglomerans SRCM 119864 was identified by 16S rRNA gene sequencing. There are 11 intermediate components known to affect IAA production, hence the effect of each component on IAA production was investigated using a Plackett-Burman design (PBD). Based on the PBD, sucrose, tryptone, and sodium chloride were selected as the main factors that enhanced the IAA production at optimal L-tryptophan concentration. The predicted maximum IAA production (64.34 mg/l) was obtained for a concentration of sucrose of 13.38 g/l, of tryptone of 18.34 g/l, of sodium chloride of 9.71 g/l, and of L-tryptophan of 6.25 g/l using a the hybrid design experimental model. In the experiment, the nutrient broth medium supplemented with 0.1% L-tryptophan as the basal medium produced 45.24 mg/l of IAA, whereas the optimized medium produced 65.40 mg/l of IAA, resulting in a 44.56% increase in efficiency. It was confirmed that the IAA production of the designed optimal composition medium was very similar to the predicted IAA production. The statistical significance and suitability of the experimental model were verified through analysis of variance (ANOVA). Therefore, in this study, we determined the optimal growth medium concentration for the maximum production of IAA, which can contribute to sustainable agriculture and increase crop yield.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.393-404
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• 2022

Reliable terrestrial rainfall observations from satellites at finer spatial resolution are essential for urban hydrological and microscale agricultural demands. Although various traditional "top-down" approach-based satellite rainfall products were widely used, they are limited in spatial resolution. This study aims to assess the potential of a novel "bottom-up" approach for rainfall estimation, the parameterized SM2RAIN model, applied to the C-band SAR Sentinel-1 satellite data (SM2RAIN-S1), to generate high-spatial-resolution terrestrial rainfall estimates (0.01° grid/6-day) over Central South Korea. Its performance was evaluated for both spatial and temporal variability using the respective rainfall data from a conventional reanalysis product and rain gauge network for a 1-year period over two different sub-regions in Central South Korea-the mixed forest-dominated, middle sub-region and cropland-dominated, west coast sub-region. Evaluation results indicated that the SM2RAIN-S1 product can capture general rainfall patterns in Central South Korea, and hold potential for high-spatial-resolution rainfall measurement over the local scale with different land covers, while less biased rainfall estimates against rain gauge observations were provided. Moreover, the SM2RAIN-S1 rainfall product was better in mixed forests considering the Pearson's correlation coefficient (R = 0.69), implying the suitability of 6-day SM2RAIN-S1 data in capturing the temporal dynamics of soil moisture and rainfall in mixed forests. However, in terms of RMSE and Bias, better performance was obtained with the SM2RAIN-S1 rainfall product over croplands rather than mixed forests, indicating that larger errors induced by high evapotranspiration losses (especially in mixed forests) need to be included in further improvement of the SM2RAIN.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.163-173
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• 2022

Climate change is a key factor that greatly influences changes in the biological seasons and geographical distribution of species. In the ecological field, the BioClimatic predictor (BioClim), which is most related to the physiological characteristics of organisms, is used for vulnerability assessment. However, BioClim values are not provided other than the future period climate average values for each GCM for the Shared Socio-economic Pathways (SSPs) scenario. In this study, BioClim data suitable for domestic conditions was produced using 1 km resolution SSPs scenario detailed data produced by Rural Development Administration, and based on the data, a species distribution model was applied to mainly grow in southern, Gyeongsangbuk-do, Gangwon-do and humid regions. Appropriate habitat distributions were predicted every 30 years for the base years (1981 - 2010) and future years (2011 - 2100) of the Acer pictum subsp. mono. Acer pictum subsp. mono appearance data were collected from a total of 819 points through the national natural environment survey data. In order to improve the performance of the MaxEnt model, the parameters of the model (LQH-1.5) were optimized, and 7 detailed biolicm indices and 5 topographical indices were applied to the MaxEnt model. Drainage, Annual Precipitation (Bio12), and Slope significantly contributed to the distribution of Acer pictum subsp. mono in Korea. As a result of reflecting the growth characteristics that favor moist and fertile soil, the influence of climatic factors was not significant. Accordingly, in the base year, the suitable habitat for a high level of Acer pictum subsp. mono is 3.41% of the area of Korea, and in the near future (2011 - 2040) and far future (2071 - 2100), SSP1-2.6 accounts for 0.01% and 0.02%, gradually decreasing. However, in SSP5-8.5, it was 0.01% and 0.72%, respectively, showing a tendency to decrease in the near future compared to the base year, but to gradually increase toward the far future. This study confirms the future distribution of vegetation that is more easily adapted to climate change, and has significance as a basic study that can be used for future forest restoration of climate change-adapted species.

• Korean Journal of Environment and Ecology
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• v.37 no.4
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• pp.289-301
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• 2023

Forests within watersheds are essential in maintaining ecosystems and are the central infrastructure for constructing an ecological network system. However, due to indiscriminate development projects carried out over past decades, forest fragmentation and land use changes have accelerated, and their original functions have been lost. Since a forest's structural pattern directly impacts ecological processes and functions in understanding forest ecosystems, identifying and analyzing change patterns is essential. Therefore, this study analyzed structural changes in the forest landscape according to the time-series land cover changes using the FRAGSTATS model for the dam watershed of the Geum River upstream. Land cover changes in the dam watershed of the Geum River upstream through land cover change detection showed an increase of 33.12 square kilometers (0.62%) of forests and 67.26 square kilometers (1.26%) of urbanized dry areas and a decrease of 148.25 square kilometers (2.79%) in agricultural areas from the 1980s to the 2010s. The results of no-sampling forest landscape analysis within the watershed indicated landscape percentage (PLAND), area-weighted proximity index (CONTIG_AM), average central area (CORE_MN), and adjacency index (PLADJ) increased, and the number of patches (NP), landscape shape index (LSI), and cohesion index (COHESION) decreased. Identification of structural change patterns through a moving window analysis showed the forest landscape in Sangju City, Gyeongsangbuk Province, Boeun County in Chungcheongbuk Province, and Jinan Province in Jeollabuk Province was relatively well preserved, but fragmentation was ongoing at the border between Okcheon County in Chungcheongbuk Province, Yeongdong and Geumsan Counties in Chungcheongnam Province, and the forest landscape in areas adjacent to Muju and Jangsu Counties in Jeollabuk Province. The results indicate that it is necessary to establish afforestation projects for fragmented areas when preparing a future regional forest management strategy. This study derived areas where fragmentation of forest landscapes is expected and the results may be used as basic data for assessing the health of watershed forests and establishing management plans.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.419-429
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• 2023

The objective of this study was to determine the management water level of an estuary reservoir considering three aspects: the water use, flood control and water quality, and to use a robust decision-making to consider uncertainty due to climate change. The watershed-reservoir linkage model was used to simulate changes in inflow due to climate change, and changes in reservoir water level and water quality. Five management level alternatives ranging from -1.7 El.m to 0.2 El.m were evaluated under the SSP1, 2, 3, and 5 scenariosof the ACCESS-CM2 Global Climate Model. Performance indicators based on period-reliability were calculated for robust decision-making considering the three aspects, and regret was used as a decision indicator to identify the alternatives with the minimum maximum regret. Flood control failure increased as the management level increased, while the probability of water use failure increased as the management level decreased. The highest number of failures occurred under the SSP5 scenario. In the water quality sector, the change in water quality was relatively small with an increase in the management level due to the increase in reservoir volume. Conversely, a decrease in the management level resulted in a more significant change in water quality. In the study area, the estuary reservoir was found to be problematic when the change in water quality was small, resulting in more failures.