• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.67-67
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• 2023

수문관측의 핵심은 강우-유출 관계다. 하천유량 생산을 위해 수많은 지점에서 유량측정을 수행한다. 그러나 유량자료의 신뢰도는 높지 않다. 그리고 댐 유입량 산정에 아무 도움이 되지 않고 있다. 더구나 저수지의 경우는 유입량 자료도 없이 운영되고 있다. 저수지, 댐에 물이 고여 있는데 이를 활용하면 유입량을 계산할 수 있고, 그 지점에서 유량이 얼마인지 고품질로 생산할 수 있다. 여기서는 총저수량 260만m³, 유역면적 3.7km²인 감포댐에 적용하여 저수량 자료를 활용하여 유입량의 신뢰도를 얼마나 개선시킬 수 있는지 분석한 결과는 다음과 같다. 여기서 적용 기간은2020.9.1.~9.14., 2022.9.5.~9.6 등 2개 사상이고, ONE 모형에 의해 10분 단위로 유출량을 모의했다. 모의 방법은 총유량을 같게 하는 방법과 저수위 오차를 최소로 하는 방법 등 두 가지로 했다. 첫째, 2020.9.1.~9.14. 사상은 강우량은 10분 최대 19.0mm, 총 127.0mm였다. 총유량을 같게 하는 경우 유입량은 10분 최대 5.4m³/s, 총 40만m³로 모의돼, 유출률 85.5%로 나타났고, 관측은 10분최대 4.7m³/s, 총 40만m³, 유출률 85.3%로 나타났다. 유량 신뢰도는 RMSE 0.491mm, NSE 0.237, R²는 0.455로 나타났다. 이 경우 저수위 모의 신뢰도는 RMSE 0.600m, NSE 0.158, R²는 0.893로나타났다. 저수량 오차를 최소로 한 경우 유입량은 10분 최대 4.0m³/s, 총 28만m³로 모의돼, 유출률 59.4%로 나타났고, 관측은 10분 최대 4.0m³/s, 총 28만m³, 유출률 85.3%로 나타났다. 유량 신뢰도는 RMSE 0.425mm, NSE 0.430, R²는 0.507로 나타났다. 이 경우 저수위 모의 신뢰도는 RMSE 0.110m, NSE 0.972, R²는 0.995로 높았다. 둘째, 2022.9.5.~9.6. 사상은 강우량은 10분 최대 32.3mm, 총 196.0mm였다. 총유량을 같게 하는 경우 유입량은 10분 최대 64.5m³/s, 총 59만m³로 모의돼, 유출률 81.6%로 나타났고, 관측은 10분 최대 80.1m³/s, 총 59만m³, 유출률 81.6%로 나타났다. 유량 신뢰도는 RMSE 1.832mm, NSE 0.960, R²는 0.984로 나타났다. 이 경우 저수위 모의 신뢰도는 RMSE 0.323m, NSE 0.968, R²는 0.999로나타났다. 저수량 오차를 최소로 한 경우 유입량은 10분 최대 80.1m³/s, 총 66만m³로 모의돼, 유출률 91.6%로 나타났고, 관측은 10분 최대 80.1m³/s, 총 59만m³, 유출률 81.8%로 나타났다. 유량 신뢰도는 RMSE 2.120mm, NSE 0.947, R2는 0.949로 나타났다. 이 경우 저수위 모의 신뢰도는 RMSE 0.153m, NSE 0.993, R²는 0.997로 높았다. 종합하면 저수량 오차가 최소가 되도록 하천 유출량을 모의하면 결과적으로 하천유량의 신뢰도를 향상시키는 것이라 말할 수 있다.

• Atmosphere
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• v.32 no.1
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• pp.61-70
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• 2022

This study evaluates the economic values for the several first precipitation events during Changma period. The selected three years are 2015, 2019, and 2020, where average precipitation amounts across the 58 Korean stations are 12.8, 20.1 and 13.3 mm, respectively. The four categories are used to assess the values including air quality improvement, water resource acquisition/accumulation, drought mitigation, and forest fire prevention/recovery. Economic values for these three years are estimated 50~150 billion won. Among the four factors considered, the effect of air quality improvement is most highly valued, amounting to 70 to 90% of the total economic values. Wet decomposition of air pollution (PM₁₀, NO₂, CO, and SO₂) is the primary reason. The next valuable element is water resource acquisition, which is estimated 9~15 billion won. Effects of drought mitigation and fire prevention are deemed relatively small. This study is the first to estimate the value of the precipitation events during Changma onset. An analysis for more Changma years will be performed to achieve a more reliable estimate.

• Journal of Korean Society of Forest Science
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• v.84 no.4
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• pp.465-478
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• 1995

The objective of this study was to investigate the impacts of large-scale timber harvesting on the environment of a mature hardwood forest. To achieve the objective, the effects of harvesting on forest environmental factors were analyzed quantitatively using the field data measured in the study sites of Seoul National University Research Forests [(Mt.) Paekunsan] for two years(1993-1994) following timber harvesting. The field data include information on vegetation, soil mesofauna, physicochemical characteristics of soil, surface water runoff, water quality in the stream, and hillslope erosion. For comparison, field data for each environmental factor were collected in forest areas disturbed by logging and undisturbed, separately. The results of this study were as follows : The diversity of vegetational species increased in the harvested sites. However, the similarity index value of species between harvested and non-harvested sites was close to each other. Soil bulk density and soil hardness were increased after timber harvesting, respectively. The level of organic matter, total-N, avail $P_2O_5$, CEC($K^+$, $Na^+$, $Ca^{{+}{+}}$, $Mg^{{+}{+}}$) in the harvested area were found decreased. While the population of Colembola spp., and Acari spp. among soil mesofauna in harvested sites increased by two to seven times compared to those of non-harvested sites during the first year, the rates of increment decreased in the second year. However, those members of soil mesofauna in harvested sites were still higher than those of non-harvested sites in the second year. The results of statistical analysis using the stepwise regression method indicated that the diversity of soil mesofauna were significantly affected by soil moisture, soil bulk density, $Mg^{{+}{+}}$, CEC, and soil temperature at soil depth of 5(0~10)cm in the order of importance. The amount of surface water runoff on harvested sites was larger than that of non-harvested sites by 28% in the first year and 24.5% in the second year after timber harvesting. The level of BOD, COD, and pH in the stream water on the harvested sites reached at the level of the domestic use for drinking in the first and second year after timber harvesting. Such heavy metals as Cd, Pb, Cu, and organic P were not found. Moreover, the level of eight factors of domestic use for drinking water designated by the Ministry of Health and Welfare of Korea were within the level of the first class in the quality of drinking water standard. The study also showed that the amount of hillslope erosion in harvested sites was 4.77 ton/ha/yr in the first year after timber harvesting. In the second year, the amount decreased rapidly to 1.0 ton/ha/yr. The impact of logging on hillslope erosion in the harvested sites was larger than that in non-harvested sites by seven times in the first year and two times in the second year. The above results indicate that the large-scale timber harvesting cause significant changes in the environmental factors. However, the results are based on only two-year field observation. We should take more field observation and analyses to increase understandings on the impacts of timber harvesting on environmental changes. With the understandings, we might be able to improve the technology of timber harvesting operations to reduce the environmental impacts of large-scale timber harvesting.