• 생태와환경
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• 제37권3호통권108호
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• pp.263-271
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• 2004

체류시간이 서로 다른 두 부영양 수계에서 미소먹이망의 생태학적 정보를 파악하고자, 기초적 환경요인과 bacterioplankton 및 nanoplankton의 현존량 및 탄소생체량을 각각 조사하였다. 조사기간동안 두 수계 공히 강우는 주로 7월에서 9월에 집중하였으며, 수온 역시 큰 차이는 없었다. 두 수계의 플랑크톤 군집은 공히 저온기 동안에는 비교적 세포크기가 큰 nanoplankton이 우점한 반면, 고온기 동안에는 소형 bacterioplankton이 높은 현존량을 나타냈다. 그러나 비교적 수계가 안정된 석촌호수에서는 강우에 큰 영향을 받지 않은 반면, 경안천에서 nanoplankton은 현존량은 물론 탄소생체량의 다양한 변화를 보였다. 두 수계의 미세먹이망은 석촌호수에서는 박테리아와 phytoplankton 또는 cyanobacteria간에 밀접한 분포 관계를 보인 반면, 경안천에서는 박테리아와 protist 사이에 뚜렷한 먹이관계를 보였다. 또한 경안천에서 개체수와 탄소생체량간의 비대칭적인 현상이 뚜렷하였다. 따라서 경안천의 미세먹이망은 수온이나 영양물질보다 강우에 의한 빠른 체류시간에 의해 강하게 영향을 받고 있지만, 안정된 수계에 비해 bacterioplankton보다 nanoplankton들의 높은 성장과 종 다양성을 유도하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.158-158
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• 2018

Drought is a recurrent natural hazard in Bangladesh. It has significant impacts on agriculture, environment, and society. Well-timed information on the onset, extent, intensity, duration, and impacts of drought can mitigate the potential drought-related losses. Thus, drought characteristics need to be explained in terms of frequency, severity, and duration. This paper aims to characterize the spatial and temporal pattern of meteorological drought using EDI and illustrated drought severity over Bangladesh. Twenty-seven (27) station-based daily rainfall data for the study period of 1981-2015 were used to calculate the EDI values over Bangladesh. The evaluation of EDI is conducted for 4 sub-regions over the country to confirm the historical drought record-developed at the regional scale. The finding shows that on average, the frequency of severe to extreme drought is approximately 0.7 events per year. As a result of the regional analysis, most of the recorded historical drought events were successfully detected during the study period. Additionally, the seasonal analysis showed that the extreme droughts were frequently hit in northwestern, middle portion of the eastern and small portion of central parts of Bangladesh during the Kharif(wet) and Rabi(dry) seasons. The severe drought was affected recurrently in the central and northern regions of the country during all cropping seasons. The study also points out that the northern, south-western and central regions in Bangladesh are comparatively vulnerable to both extreme and severe drought event. The study showed that EDI would be a useful tool to identify the drought-prone area and time and potentially applicable to the climate change-induced drought evolution monitoring at regional to the national level in Bangladesh. The outcome of the present study can be used in taking anticipatory strategies to mitigate the drought damages on agricultural production as well as human sufferings in drought-prone areas of Bangladesh.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.154-154
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• 2018

To interpret the climate projections for the future as well as present, recognition of the consequences of the climate internal variability and quantification its uncertainty play a vital role. The Korean Peninsula belongs to the Far East Asian Monsoon region and its rainfall characteristics are very complex from time and space perspective. Its internal variability is expected to be large, but this variability has not been completely investigated to date especially using models of high temporal resolutions. Due to coarse spatial and temporal resolutions of General Circulation Models (GCM) projections, several studies adopted dynamic and statistical downscaling approaches to infer meterological forcing from climate change projections at local spatial scales and fine temporal resolutions. In this study, stochastic downscaling methodology was adopted to downscale daily GCM resolutions to hourly time scale using an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). After extracting factors of change from the GCM realizations, these were applied to the climatic statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series which can be considered to be representative of future climate conditions. Further, 30 ensemble members of hourly precipitation were generated for each selected station to quantify uncertainty. Spatial map was generated to visualize as separated zones formed through K-means cluster algorithm which region is more inconsistent as compared to the climatological norm or in which region the probability of occurrence of the extremes event is high. The results showed that the stations located near the coastal regions are more uncertain as compared to inland regions. Such information will be ultimately helpful for planning future adaptation and mitigation measures against extreme events.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.188-188
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• 2016

The Mekong which is one of the world's most significant rivers plays an extremely important role to South East Asia. Lying across six riparian countries including China, Myanmar, Thailand, Laos, Cambodia and Vietnam and being a greatly biological and ecological diversity of fishes, the river supports a huge population who living along Mekong Basin River. Therefore, much attention has been focused on the giant Mekong Basin River, particularly, the soil erosion and sedimentation problems which rise critical impacts on irrigation, agriculture, navigation, fisheries and aquatic ecosystem. In fact, there have been many methods to calculate these problems; however, in the case of Mekong, the available data have significant limitations because of large area (about 795 00 km2) and a failure by management agencies to analyze and publish of developing countries in Mekong Basin River. As a result, the Universal Soil Loss Equation (USLE) model in a GIS (Geographic Information System) framework was applied in this study. The USLE factors contain the rainfall erosivity, soil erodibility, slope length, steepness, crop management and conservation practices which are represented by raster layers in GIS environment. In the final step, these factors were multiplied together to estimate the soil erosion rate in the study area by using spatial analyst tool in the ArcGIS 10.2 software. The spatial distribution of soil loss result will be used to support river basin management to find the subtainable management practices by showing the position and amount of soil erosion and sediment load in the dangerous areas during the selected 56- year period from 1952 to 2007.

• 한국수자원학회논문집
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• 제52권3호
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• pp.173-185
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• 2019

한반도는 지형학적 요건으로 인하여 태풍과 관련된 재난이 매년 발생하여 막대한 피해를 유발하고 있다. 태풍 내습시 폭풍해일과 집중호우가 동시에 발생한다면 해안지역의 침수피해는 더욱 증가할 것으로 사료된다. 이러한 관점에서 태풍과 폭풍해일의 상호의존성을 정량적으로 규명하는 것은 해안지역의 재해분석에 필수적이다. 본 연구에서는 Bayesian 기법을 기반으로 절점기준을 초과하는 임계값의 초과확률을 산정하기 위하여 Poisson 분포와 Generalized-Pareto 분포를 이용한 Poisson-GP 폭풍해일 빈도해석 기법을 개발하였다. 본 연구를 통하여 개발된 Poisson-GP 폭풍해일 빈도해석 기법은 설계해수면의 불확실성을 정량적으로 제시하였으며 해안지역의 폭풍해일 관련 방재기술 향상에 기여할 것으로 판단된다.

• Journal of Ginseng Research
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• 제43권4호
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• pp.654-665
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• 2019

Background: Panax ginseng Meyer has widely been used as a traditional herbal medicine because of its diverse health benefits. Amounts of ginseng compounds, mainly ginsenosides, vary according to seasons, varieties, geographical regions, and age of ginseng plants. However, no study has comprehensively determined perturbations of various metabolites in ginseng plants including roots and leaves as they grow. Methods: Nuclear magnetic resonance ($^1H$ NMR)-based metabolomics was applied to better understand the metabolic physiology of ginseng plants and their association with climate through global profiling of ginseng metabolites in roots and leaves during whole growing periods. Results: The results revealed that all metabolites including carbohydrates, amino acids, organic acids, and ginsenosides in ginseng roots and leaves were clearly dependent on growing seasons from March to October. In particular, ginsenosides, arginine, sterols, fatty acids, and uracil diphosphate glucose-sugars were markedly synthesized from March until May, together with accelerated sucrose catabolism, possibly associated with climatic changes such as sun exposure time and rainfall. Conclusion: This study highlights the intrinsic metabolic characteristics of ginseng plants and their associations with climate changes during their growth. It provides important information not only for better understanding of the metabolic phenotype of ginseng but also for quality improvement of ginseng through modification of cultivation.

• 대기
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• 제29권3호
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• pp.269-282
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• 2019

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

• 한국지반환경공학회 논문집
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• 제20권4호
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• pp.23-29
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• 2019

최근의 기후변화는 산지가 많은 우리나라에서 토석류를 발생시켜 하류에 많은 재난을 야기하였다. 산지에서 발생한 토석류는 퇴적과 침식을 반복하며 하류로 이동하고, 유동화된 토사-물 혼합물 형태로 나타난다. 이처럼 강한 운동성의 토석류를 해석하기 위하여 연속방정식 및 운동량 방정식을 적용하였고, 퇴적 및 침식에 관한 속도식은 세립사가 포한된 수정형을 적용하였다. 본 연구는 산지 상류부에서 발생 가능한 퇴적토사량의 변화에 대한 하류부에서의 토석류 거동을 분석한 것이다. 조립토사의 포설 길이 변화에 따른 수로 하류단에서 토사체적농도를 분석해 보면, 공급유량이 많고 포설길이가 길수록 토사농도의 고저차가 크게 나타났고, 변곡점 발생 시점도 빨라진 것을 알 수 있다. 본 연구의 결과는 급경사의 비탈사면에서의 침식 및 퇴적 가능 여부를 알 수 있는 침식-퇴적 속도를 판단하여 토석류 재해에 대한 대책을 세우는 데 좋은 정보를 제공할 것이다.

• 한국농공학회논문집
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• 제61권1호
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• pp.145-159
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• 2019

A good number of drought indices have been introduced and applied in different regions for monitoring drought conditions, but some of those are region-specific and have limitations for use under other climatic conditions because of the inherently complex characteristics of drought phenomenon. Standardized Precipitation Index (SPI) indices are widely used all over the world, including Bangladesh. Although newly developed, studies have demonstrated The Effective Drought Index (EDI) to perform better compared to SPIs in some areas. This research examined the performance of EDI to the SPI for detecting drought events throughout 35 years (1981 to 2015) in Bangladesh. Rainfall data from 27 meteorological stations across Bangladesh were used to calculate the EDI and SPI values. Results suggest that the EDI can detect historical records of actual events better than SPIs. Moreover, EDI is more efficient in assessing both short and long-term droughts than SPIs. Results also indicate that SPI3 and the EDI indices have a better capability of detecting drought events in Bangladesh compared to other SPIs; however, SPI1 produced erroneous estimates. Therefore, EDI is found to be more responsive to drought conditions and can capture the real essence of the drought situation in Bangladesh. Outcomes from this study bear policy implications on mitigation measures to minimize the loss of agricultural production in drought-prone areas. Information on severity level and persistence of drought conditions will be instrumental for resource managers to allocate scarce resources optimally.

• 농업과학연구
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• 제47권4호
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.