• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.109-120
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• 2007

The information on flowpath, storage, residence time, and interactions of water and carbon transport in a catchment is the prerequisite to the understanding and predicting of water and carbon cycling in the mountainous landscapes of Korea. In this paper, along with some up-to-date results, we present the principal methods that are currently used in HydroKorea and CarboKorea research to obtain such information. Various catchment hydrological processes have been examined on the basis of the water table fluctuations, the end-member mixing model, the cross correlation analysis, and cosmogenic radioactive isotope activity. In the Gwangneung catchment, the contribution of surface discharge was relatively large, and the changes in the amount, intensity and patterns of precipitation affected both the flowpath and the mean residence time of water. Particularly during the summer monsoon, changes in precipitation patterns and hydrological processes in the catchment influenced the carbon cycle such that the persistent precipitation increased the discharge of dissolved organic carbon (DOC) concentrated in the surface soil layer. The improved understanding of the hydrological processes presented in this report will enable a more realistic assessment of the effects of climate changes on the water resource management and on the carbon cycling in forest catchments.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1429-1433
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• 2010

수공구조물의 설계, 수자원 관리계획의 수립, 재해영향 검토 등을 수행할 때, 재현기간에 따른 확률개념의 강우량, 홍수량, 저수량 등을 산정하여 사용하게 되며, 보통 대상지역의 장기 수문관측 자료를 이용하여 수문사상의 확률분포를 산정한 후 재현기간을 연장하여 원하는 설계빈도에 해당하는 양을 추정하게 된다. 미계측지역 또는 관측자료의 보유기간이 짧은 지역의 경우는 지역빈도 분석 결과를 이용하게 된다. 지역빈도해석을 위해서는 강우자료들의 동질성을 파악하는 것이 가장 기본적인 과정이 되며 이를 위해 통계학적인 범주화분석이 선행되어야 한다. 지점 빈도분석의 수문학적 동질성 판별을 위해 L-moment 방법, K-means 방법에 의한 군집분석 등이 주로 사용되며 관측소 위치좌표를 이용한 공간보간법을 적용하여 시각화하고 있다. 강수량은 시공간적으로 변하는 수문변량으로서 강수량의 시간적인 특성 또한 강수량의 특성을 정의하는데 매우 중요한 요소이다. 이러한 점에서 본 연구를 통해 강수지점의 공간적인 좌표 및 강수량의 양적인 범주화에 초점을 맞춘 기존 지역빈도분석의 범주화 과정에 덧붙여 시간적인 영향을 고려할 수 있는 요소들을 결정하고 이를 활용할 수 있는 범주화 과정을 제시하고자 한다. 즉, 극치강수량의 발생 시기에 대한 정량적인 분석이 가능한 순환통계기법을 이용하여 관측 지점별 시간 통계량을 산정하고, 이를 극치강수량과 결합하여 시 공간적인 특성자료를 생성한 후 이를 이용한 군집화 해석 모형을 개발하는데 연구의 목적이 있다. 분석 과정에 있어서 시간속성의 정량화 및 일반화는 순환통계기법을 사용하였으며, 극치강수량과 발생시점의 속성자료는 각각의 평균과 표준편차를 이용하였다. K-means 알고리즘을 이용해 결합자료를 군집화 하고, L-moment 방법으로 지역화 결과에 대한 검증을 수행하였다. 속성 결합 자료의 군집화 효과는 모의데이터 실험을 통해 확인하였으며, 우리 나라의 58개 기상관측소 자료를 이용하여 분석을 수행하였다. 예비해석 단계에서 100회의 군집분석을 통해 평균적인 centroid를 산정하고, 해당 값을 본 해석의 초기 centroid로 지정하여, 변동적인 클러스터링 경향을 안정화시켜 해석이 반복됨에 따라 군집화 결과가 달라지는 오류를 방지하였다. 또한 K-means 방법으로 계산된 군집별 공간거리 합의 크기에 따라 군집번호를 부여함으로써 군집의 번호순서대로 물리적인 연관성이 인접하도록 설정하였으며, 군집간의 경계선을 추출할 때 발생할 수 있는 오류를 방지하였다. 지역빈도분석 결과는 3차원 Spline 기법으로 도시하였다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.151-161
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• 2009

Configuration of soil hydraulic property is an essential component to understand the hydrological processes at the hillslope scale. In this study, we investigated temporal variations in pore development and soil hydraulic properties during the period from March to October in 2008. Characteristics for macropore flow and hydraulic conductivity were measured at two hillslopes: one is the hillslope located at the Buprunsa in Sulmachun watershed, and the other is the hillslope located in Gwangneung Research Forest. Vertical fluxes through macropore were measured using a tension infiltrometer at the depth of surface. The saturated hydraulic conductivities in March, June, July and September were relatively high compared to those in May and October. Temporal variations in several soil hydraulic features could be explained by the differences in vegetation activity and soil moisture content determined by antecedent precipitation. Particularly, the features of macropores had a substantial impact on hydraulic conductivity in the forest hillslope. The temporal nonuniformity of the soil hydraulic properties observed in this study manifests the dynamic features of hydrological processes in the hillslope scale and the experimental results will be useful to understand the internal hydrological processes in the mountainous hillslope.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.41-52
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• 2022

Although domestic public libraries achieved quantitative growth based on the 1st and 2nd comprehensive library development plans, there were some qualitative shortcomings, and various studies have been conducted to improve them. Most of the preceding studies have limitations in that they are limited to social and economic factors and statistical analysis. Therefore, in this study, by applying the spatiotemporal concept to quantitatively calculate the decrease in public library loan demand due to rainfall and heatwave, by clustering areas with high demand for book loan due to weather changes and areas where it is not, factors inside and outside public libraries and After the combination, changes in public library loan demand according to weather changes were analyzed. As a result of the analysis, there was a difference in the decrease due to the weather for each public library, and it was found that there were some differences depending on the characteristics and spatial location of the public library. Also, when the temperature was over 35℃, the decrease in book loan demand increased significantly. As internal factors, the number of seats, the number of books, and area were derived. As external factors, the public library access ramp, cafe, reading room, floating population in their teens, and floating population of women in their 30s/40s were analyzed as important variables. The results of this analysis are judged to contribute to the establishment of policies to promote the use of public libraries in consideration of the weather in a specific season, and also suggested limitations of the study.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.444-444
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• 2021

하천의 오염부하량 관리 계획은 지속적인 모니터링을 통한 자료 구축과 모형을 이용한 예측결과를 기반으로 수립된다. 하천의 모니터링과 예측 분석은 많은 예산과 인력 등이 필요하나, 정부의 담당 공무원 수는 극히 부족한 상황이 일반적이다. 이에 정부는 전문가에게 관련 용역을 의뢰하지만, 한국과 같이 지형이 복잡한 지역에서의 오염부하량 배출 특성은 각각 다르게 나타나기 때문에 많은 예산 소모가 발생 된다. 이를 개선하고자, 본 연구는 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 BOD 및 총인의 부하량 예측 모형을 개발하였다. 합성곱 신경망의 입력자료는 일반적으로 RGB (red, green, bule) 사진을 이용하는데, 이를 그래도 오염부하량 예측에 활용하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이에, 본 연구에서는 오염부하량이 수문학적 조건과 토지이용 등의 변수에 의해 결정된다는 인과관계를 만족시키고자 수문학적 속성이 내재된 수문학적 이미지를 합성곱 신경망의 훈련자료로 사용하였다. 수문학적 이미지는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는데, 여기서 각 grid의 수문학적 속성은 SCS 토양보존국(soil conservation service, SCS)에서 발표한 수문학적 토양피복형수 (curve number, CN)를 이용하여 산출한다. 합성곱 신경망의 구조는 2개의 Convolution Layer와 1개의 Pulling Layer가 5회 반복하는 구조로 설정하고, 1개의 Flatten Layer, 3개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 마지막으로 1개의 Dense Layer가 연결되는 구조로 설계하였다. 이와 함께, 각 층의 활성화 함수는 정규화 선형함수 (ReLu)로, 마지막 Dense Layer의 활성화 함수는 연속변수가 도출될 수 있도록 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 연구의 대상지역은 경기도 가평군 조종천 유역으로 선정하였고, 연구기간은 2010년 1월 1일부터 2019년 12월 31일까지로, 2010년부터 2016년까지의 자료는 모형의 학습에, 2017년부터 2019년까지의 자료는 모형의 성능평가에 활용하였다. 모형의 예측 성능은 모형효율계수 (NSE), 평균제곱근오차(RMSE) 및 평균절대백분율오차(MAPE)를 이용하여 평가하였다. 그 결과, BOD 부하량에 대한 NSE는 0.9, RMSE는 1031.1 kg/day, MAPE는 11.5%로 나타났으며, 총인 부하량에 대한 NSE는 0.9, RMSE는 53.6 kg/day, MAPE는 17.9%로 나타나 본 연구의 모형은 우수(good)한 것으로 판단하였다. 이에, 본 연구의 모형은 일반 ANN 모형을 이용한 선행연구와는 달리 2차원 공간정보를 반영하여 오염부하량 모의가 가능했으며, 제한적인 입력자료를 이용하여 간편한 모델링이 가능하다는 장점을 나타냈다. 이를 통해 정부의 물관리 정책을 위한 의사결정 및 부족한 물관리 분야의 행정력에 도움이 될 것으로 생각된다.

• Korean Journal of Environmental Agriculture
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• v.31 no.4
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• pp.318-327
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• 2012

BACKGROUND: For Non-Point Source(NPS) loads reduction, pollutant loads need to be quantified for major farming methods. The objective of this study was to evaluate impacts of farming methods on NPS pollutant loads from a paddy rice field during the growing season. METHODS AND RESULTS: The height of drainage outlet, amount of fertilizer, irrigation water quality were considered as farming factors for scenarios development. The control was derived from conventional farming methods and four different scenarios were developed based combination of farming factors. A field scale model, CREAMS-PADDY(Chemicals, Runoff, and Erosion from Agricultural Management Systems for PADDY), was used to calculate pollutant nutrient loads. The data collected from an experimental plot located downstream of the Idong reservoir were used for model calibration and validation. The simulation results agreed well with observed values during the calibration and validation periods. The calibrated model was used to evaluate farming scenarios in terms of NPS loads. Pollutant loads for T-N, T-P were reduced by 5~62%, 8~37% with increasing the height of drainage outlet from 100 mm of 100 mm, respectively. When amount of fertilizer was changed from standard to conventional, T-N, T-P pollutant loads were reduced by 0~22%, 0~24%. Irrigation water quality below water criteria IV of reservoir increased T-N of 9~65%, T-P of 9~47% in comparison with conventional. CONCLUSION(S): The results indicated that applying increased the height of drainage after midsummer drainage, standard fertilization level during non-rainy seasons, irrigation water quality below water criteria IV of reservoir were effective farming methods to reduce NPS pollutant loads from paddy in Korea.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.4
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• pp.71-80
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• 2009

Although desire for living without hazardous damages grows these days, threats from natural disasters which we are currently exposed to are quiet different from what we have experienced. To cope with this changing situation, it is necessary to assess the characteristics of the natural disasters. Therefore, the main purpose of this research is to suggest a methodology to estimate the potential property loss and assess the flood risk using a regional regression analysis. Since the flood damage mainly consists of loss of lives and property damages, it is reasonable to express the results of a flood risk assessment with the loss of lives and the property damages that are vulnerable to flood. The regional regression analysis has been commonly used to find relationships between regional characteristics of a watershed and parameters of rainfall-runoff models or probability distribution models. In our research, however, this model is applied to estimate the potential flood damage as follows; 1) a nonlinear model between the flood damage and the hourly rainfall is found in gauged regions which have sufficient damage and rainfall data, and 2) a regression model is developed from the relationship between the coefficients of the nonlinear models and socio-economic indicators in the gauged regions. This method enables us to quantitatively analyze the impact of the regional indicators on the flood damage and to estimate the damage through the application of the regional regression model to ungauged regions which do not have sufficient data. Moreover the flood risk map is developed by Flood Vulnerability Index (FVI) which is equal to the ratio of the estimated flood damage to the total regional property. Comparing the results of this research with Potential Flood Damage (PFD) reported in the Long-term Korea National Water Resources Plan, the exports' mistaken opinions could affect the weighting procedure of PFD, but the proposed approach based on the regional regression would overcome the drawback of PFD. It was found that FVI is highly correlated with the past damage, while PFD does not reflect the regional vulnerabilities.

• Journal of Korean Society of Forest Science
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• v.86 no.4
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• pp.489-501
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• 1997

This research was conducted to analyze the influence of the environmental factors on water quality such as pH, dissolved oxygen, and electrical conductivity of rainfall, throughfall, soil water(A and B layer), and stream water quality at a small forested watershed. Rainfall, throughfall, soil water(A and B layer), and stream water were sampled at the study sites in Kwanak Arboretum, Seoul National University in Mt. Kwanak for 14 months(Jul. 1, 1996~Aug. 31, 1997). Average rainfall pH value was 6.06(ranged from 5.02 to 6.60). Acid rain frequency(less than pH 5.6) was 16.7%. The lowest rainfall pH value was 5.02. Average of pH values in hydrological processes were decreasing in the following order, stream water>soil water [Prunus serrulata var, spontanea(B layer>A layer)]>throughfall(Prunus serrulata var. spontanea)>soil water [Carpinus laxiflora(B layer >A layer)]>throughfall(Carpinus laxiflora)>rainfall>soil water [Pinus rigida(B layer>A layer)]>throughfall(Pinus rigida). pH values of throughfall in Prunes serrulata var. spontanea and Carpinus laxiflora were higher in Pines rigida. Average of dissolved oxygen values in hydrological processes were decreasing in the order, stream water>throughfall(Carpinus laxiflora>Prunus serrulata var, spontanea>Pines rigida)>rainfall>soil water [Prunes serrulata var. spontanea(A layer)>Pines rigida(A layer)>Carpinus laxiflora(A layer)>Prunes serrulata var. spontanea(B layer)>Pines rigida(B layer)>Carpinus laxiflora(B layer)]. And average electrical conductivity values in hydrological processes were decreasing in the order, soil water (B layer>A layer)>throughfall(Pinus rigida>Prunes serrulata var, spontanea>Carpinus laxiflora)>stream water>rainfall. Multiple regression equations of electrical conductivity and $Mg^{2+}$, $Na^+$, total amount of cation, total amount of ion, and no. of before non-rain days in rainfall, throughfall, soil and stream water shows high significance(Multi R; 0.84).

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.431-440
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• 2017

The 2016 Gyeongju Earthquake ($M_L$ 5.8) (occurred on September 12, 2016) and the 2017 Pohang Earthquake ($M_L$ 5.4) (occurred on November 15, 2017) caused unprecedented damages in South Korea. It is necessary to establish basic data related to earthquake-induced mountainous sediment-related disasters over worldwide. In this study, we analyzed previous international studies on the earthquake-induced mountainous sediment-related disasters, then classified research areas according to research themes using text-mining and co-word analysis in VOSviewer program, and finally examined spatio-temporal research trends by research area. The result showed that the related-researches have been rapidly increased since 2005, which seems to be affected by recent large-scale earthquakes occurred in China, Taiwan and Japan. In addition, the research area related to mountainous sediment-related disasters induced by earthquakes was classified into four subjects: (i) mechanisms of disaster occurrence; (ii) rainfall parameters controlling disaster occurrence; (iii) prediction of potential disaster area using aerial and satellite photographs; and (iv) disaster risk mapping through the modeling of disaster occurrence. These research areas are considered to have a strong correlation with each other. On the threshold year (i.e., 2012-2013), when cumulative number of research papers was reached 50% of total research papers published since 1987, proportions per unit year of all research areas should increase. Especially, the proportion of the research areas related to prediction of potential disaster area using aerial and satellite photographs is highly increased compared to other three research areas. These trends are responsible for the rapidly increasing research papers with study sites in China, and the research papers examined in Taiwan, Japan, and the United States have also contributed to increases in all research areas. The results are could be used as basic data to present future research direction related to mountainous sediment-related disasters induced by earthquakes in South Korea.