• Ocean and Polar Research
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• 제38권4호
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• pp.331-338
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• 2016

Many studies using tracers have been conducted to understand a physical process in a system. Rain-on-snow could accelerate snowmelt processes, which influences the hydrological process in both temperate and polar regions. Hydrological and ecological conditions will be affected by the amount and timing of discharge reaching the bottom of a snowpack. The discharge consists of the rain-on-snow, pore water penetrating into the snowpack and natural meltwater. In this study, after a rain-on-snow experiment, we conducted an isotopic hydrograph separation to distinguish rainwater and pore water from meltwater. Using the isotopic data of snow and meltwater from Lee et al. (2010), two components were separated based on the assumption that rainwater and pore water are new water and natural meltwater is old water. After the second rain-on-snow experiment, the maximum contributions of rainwater and pore water reached up to 69% of the discharge and then decreased. During the study period, the measured total discharge was 4153 L and 40% (based on hydrogen isotope) of rainwater and pore water was calculated in the discharge, which is not consistent with what Lee et al. (2016) calculated using chemical separation (63%). This inconsistency can be explained by how an end-member was defined in both approaches. The contributions of artificial rainonsnow and pore water to melwater discharge range between the two methods. This study will suggest a mixing calculation from isotopic compositions of the Southern Ocean.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.134-134
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• 2021

Precipitation is a crucial component of water cycle and play a key role in hydrological processes. Traditionally, gauge-based precipitation is the main method to achieve high accuracy of rainfall estimation, but its distribution is sparsely in mountainous areas. Recently, satellite-based precipitation products (SPPs) provide grid-based precipitation with spatio-temporal variability, but SPPs contain a lot of uncertainty in estimated precipitation, and the spatial resolution quite coarse. To overcome these limitations, this study aims to generate new grid-based daily precipitation using Automatic weather system (AWS) in Korea and multiple SPPs(i.e. CHIRPSv2, CMORPH, GSMaP, TRMMv7) during the period of 2003-2017. And this study used a machine learning based Random Forest (RF) model for generating new merging precipitation. In addition, several statistical linear merging methods are used to compare with the results of the RF model. In order to investigate the efficiency of RF, observed data from 64 observed Automated Synoptic Observation System (ASOS) were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the random forest model showed higher accuracy than each satellite rainfall product and spatio-temporal variability was better reflected than other statistical merging methods. Therefore, a random forest-based ensemble satellite precipitation product can be efficiently used for hydrological simulations in ungauged basins such as the Mekong River.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.147-147
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• 2022

In January 2021 heavy flood affected South Kalimantan with causing many casualties. The heavy rainfall is predicted to be generated due to the ENSO (El Nino-Southern Oscillation). The weak La-Nina mode appeared to generate more convective cloud above the warmed ocean and result in extreme rainfall with high anomaly compared to past historical rainfall event. Subsequently, the antecedent soil moisture distribution showed to have an important role in generating the flood response. Saturated flow and infiltration excess mainly contributed to the runoff generation due to the high moisture capacity. The hydro-meteorological processes in this event were deeply analyzed using the coupled atmospheric model of Weather Research and Forecasting (WRF) and the hydrological model extension (WRF-Hydro). The sensitivity analysis of the flood response to the SST anomaly and the soil moisture capacity also compared. Result showed that although SST and soil moisture are the main contributors, soil moisture have more significant contribution to the runoff generation despite of anomaly rainfall occurred. Model performance was validated using the Global Precipitation Measurement (GPM) and Soil Moisture Operational Products System (SMOPS) and performed reasonably well. The model was able to capture the hydro-meteorological process of atmosphere and hydrological feedbacks in the extreme weather event.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.28-28
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• 2023

Most countries worldwide are finding it difficult to make decisions regarding the utilization of water resources and the ecological flow protection of rivers because of serious water shortages and global climate warming. To overcome this difficulty, accurate ecological flow processes and protected ecological objectives are required. Since the introduction of the concept, ecological flow calculations have been developed for more than 60 years. This technical development has always been dominated by countries such as the United States, Australia, and the United Kingdom. The technical applications, however, vary substantially worldwide. Some countries, for instance, did not readjust the method because of a lack of understanding of the ecological effect or because they failed to achieve elaborate scheduling. Mostly, readjustments were not made because the users could not make their choices from among numerous methods for ecological flow. This paper presents three research results based on a systematic review of 240 methods with clear connotation boundaries. First, the ecological flow algorithm was developed along with the scientific and technological progress in the river ecosystem theory, ecohydrological relationship, and characterization and simulation of hydrological and hydrodynamic processes. In addition, the basis of the method has evolved from the hydrological process of the ecosystem, hydraulics-habitat conditions, and social development interference to whole ecosystem simulation. Second, 240 methods were classified into 50 sub-categories to evaluate their advantages and disadvantages according to the ecological flow algorithms of hydrology, hydraulics, habitat, and other comprehensive methods. According to this evaluation, 60% of the methods were not suitable for further application, including the method based on the percentage of natural runoff. Furthermore, the applicability of the remaining methods was presented according to the evaluation based on the aspects of allocation of water resources, water conservancy project scheduling, and river ecological evaluation. Third, In the future, most developing countries should strengthen the guarantee of high-standard ecological flow via a coordination mechanism for the ecological flow guarantee established under a sustainable framework or via an ecological protection pattern at the national level according to the national system. Concurrently, a reliable ecological flow demand process should also be established on the basis of detailed investigation and research on the relationship between river habitats, ecological hydrology, and ecological hydraulics. This will ensure that the real-time evaluation of ecological flow forces the water conservancy project scheduling and accurate allocation of water.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.529-534
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• 2009

Climate models, both global and regional, have increased in sophistication and are being run at increasingly higher resolutions. The Land Surface Models (LSMs) coupled to these climate models have evolved from simple bucket models to sophisticated Soil-Vegetation-Atmosphere Transfer (SVAT) schemes needed to support complex linkages and processes. However, some underpinnings of terrestrial hydrologic parameterizations so crucial in the predictions of surface water and energy fluxes cause model errors that often manifest as non-linear drifts in the dynamic response of land surface processes. This requires the improved parameterizations of key processes for the terrestrial hydrologic scheme to improve the model predictability in surface water and energy fluxes. The Common Land Model (CLM), one of state-of-the-art LSMs, is the land component of the Community Climate System Model (CCSM). However, CLM also has energy and water biases resulting from deficiencies in some parameterizations related to hydrological processes. This research presents the implementation of a selected set of parameterizations and their effects on the runoff prediction. The modifications consist of new parameterizations for soil hydraulic conductivity, water table depth, frozen soil, soil water availability, and topographically controlled baseflow. The results from a set of offline simulations are compared with observed data to assess the performance of the new model. It is expected that the advanced terrestrial hydrologic scheme coupled to the current CLM can improve model predictability for better prediction of runoff that has a large impact on the surface water and energy balance crucial to climate variability and change studies.

• 대한지하수환경학회지
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• 제2권1호
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• pp.38-47
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• 1995

이 연구에서는 삼척탄전 내에 위치하는 폐탄광인 동해탄광을 대상으로 산성 광산폐수의 중화 처리를 위한 각종 기초자료를 제시하고자 하였다. 산성 광산폐수의 측정시기에 따른 변화양상을 관찰한 결과 갈 수기에는 각종 잠재적 유독성 원소들의 함량이 증가하며, pH가 하락하여 수질이 악화되는 경향을 보였다. 공업용 소석회는 처리효율 및 경제성을 고려할 경우 산성 광산폐수의 처리를 위한 최적의 중화제로 판단되며, 평형 모델링 결과 중화처리과정에서 Fe는 FeOOH의 형태로, Al은 Al(OH)$_3$, 의 형태로 침전되는 것으로 추정된다. GIS를 이용하여 동해탄광일대 산성 광산폐수 처리시설의 위치를 제시하였으며 수문학적 자료를 이용하여 최대강우량 및 첨두유량을 계산하였다.

• 한국농공학회지
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• 제32권E호
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• pp.33-46
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• 1990

Abstract Over 700/0 of the rural land area in Korea is mountainous and small watersheds provide most of the water resources for agricutural use. To provide an appropriate tool for the agricultural water resource development project, SNUA2, a mathematical model for simulating the physical processes governing the precipitation-runoff relationships and predicting the storm and long-term runoff quantities from the small mountainous watersheds was developed. The hydrological characteristics of small mountainous watersheds were reviewed to select appropriate theories for the simulation of the runoff processes, and a deterministic and distributed model was developed. In this, subsurface flows are routed by solving Richard's two dimensional equation, the dynamics of soil moisture contents are simulated by the consideration of phenological factors of canopy plants and surface flows are routed by solving the kinematic wave theory by numerical analysis. As a result of an application test of the model to the Sanglim watershed, peak flow rates of storm runoff were over-estimated by up to 184.2%. The occurence time of peak flow and total runoff volume of storm runoffs simulated were consistent with observed values and the annual runoff volumes were simulated in the error range of less than 5.8%.

• 대한원격탐사학회지
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• 제33권1호
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• pp.47-60
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• 2017

The permafrost active layer plays an important role in permafrost dynamics. Ecological patterns, processes, and water and ice contents in the active layer are spatially and temporally complex depending on landscape heterogeneity and local-scale variations in hydrological processes. Although there has been emerging interest in the application of optical remote sensing techniques to permafrost environments, optical sensors are significantly limited in accessing information on near surface geo-cryological conditions. The primary objective of this study was to investigate capability of L-band SAR data for monitoring spatio-temporal variability of permafrost ecosystems and underlying soil conditions. This study exploits information from different polarimetric SAR observables in relation to permafrost environmental conditions. Experimental results show that each polarimetric radar observable conveys different information on permafrost environments. In the case of the dual-pol mode, the radar observables consist of two backscattering powers and one correlation coefficient between polarimetric channels. Among them, the dual-pol scattering powers are highly sensitive to freeze/thaw transition and can discriminate grasslands or ponds in thermokarst area from other permafrost ecosystems. However, it is difficult to identify the ground conditions with dual-pol observables. Additional backscattering powers and correlation coefficients obtained from quad-pol mode help understanding seasonal variations ofradar scattering and assessing geo-cryological information on soil layers. In particular, co-pol coherences atHV-basis and circular-basis were found to be very usefultools for mapping and monitoring near surface soil properties.

• 한국산림과학회지
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• 제86권1호
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• pp.56-68
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• 1997

본 연구는 산지 물순환 과정별 수질변화를 추적하여 계류수질의 형성 과정 및 산림의 환경적 정화기능을 평가하고자 실시하였다. 팔공, 용성 및 대동의 3개 조사지에서 한 단위강우에 대한 임외우, 수관통과우, 수간류, 낙엽층류 및 계류수, 그리고 장기 계류수를 대상으로 하여 각각의 유출수량과 pH, 전기전도도, 용존산소량 및 용존원소의 농도변화를 분석한 결과는 다음과 같다. 1. 계류수의 pH, 용존산소량은 유출수량의 증가에 따라 값이 상승하였으나, 전기전도도는 값이 낮아지는 것으로 나타났다. 2. 수간류 및 수관통과우의 pH는 임외우에 비해 경시적으로 낮은 값을 나타내며, EC는 강우초기에 높은 값, 그 이후는 강우시간의 경과와 함께 값이 낮아지는 경시적 변화를 보였다. 낙엽층류의 pH는 임외우에 비해 낮은 값, EC는 높은 값을 나타냈다. 계류수에 있어서 pH 동태는 강우초기에 높은 값을 나타내고 강우시간이 경과함에 따라 큰 폭으로 떨어지다가 강우종료 및 그 이후에는 초기 수준 또는 그 이상의 값으로 회복하였으나, EC는 거의 반대의 경향이 있었다. 낙엽층류 및 계류수의 DO는 강우시간의 경과에 따라 값이 점차 낮아졌으나, 임외우, 수간류 및 수관통과우에서는 경시적으로 뚜렷한 경향이 없었다. 3. 수간류 및 수관통과우에 있어서 pH는 소나무에 비해 상수리나무가 높았으나, EC는 낮은 값을 나타내었다. 양이온 총량은 상수리나무에 비해 소나무의 수간류에서 높은 값을 나타냈다. 4. 물순환의 각 과정에 있어서 pH는 낙엽층류<임내우(수간류+수관통과우)<임외우<계류수의 순으로, DO는 낙엽층류<임내우<임외강우<계류수, 그리고 EC는 임외우<계류수<임내우<낙엽층류의 크기 순으로 나타났다. 양이온 총량은 임외우<임내우<낙엽층<계류수의 크기 순으로 나타났다. 5. EC는 팔공조사지에 비해 용성조사지에서 전체적으로 높은 값을 나타내어 팔공계류수가 수질이 더 깨끗한 것으로 나타났다. 그리고 장기 계류수에 있어서 pH, DO, EC 및 양이온 총량은 월별로 각각 독특한 경시적 변화를 보였다.