• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.428-428
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• 2017

In this study, three optimization techniques efficiency is assessed for calibration of the GR4J model for streamflow simulation in Selmacheon, Boryeong Dam and Kyeongancheon watersheds located in South Korea. The Penman-Monteith equation is applied to estimate the potential evapotranspiration, model calibration, and validation is carried out using the readily available daily hydro-meteorological data. The Shuffled Complex Evolution-University of Arizona(SCE-UA), Uniform Adaptive Monte Carlo (UAMC), and Coupled Latin Hypercube and Rosenbrock (CLHR) optimization techniques has been used to evaluate the robustness, performance and optimized parameters of the three catchments. The result of the three algorithms performances and optimized parameters are within the recommended ranges in the tested watersheds. The SCE-UA and CLHR outputs are found to be similar both in efficiency and model parameters. However, the UAMC algorithms performances differently in the three tested watersheds.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.305-305
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• 2022

A better approach for assessing meteorological drought occurrences is increasingly important in mitigating and adapting to the impacts of climate change, as well as strategies for developing early warning systems. The present study defines meteorological droughts as a period with an abnormal precipitation deficit based on monthly precipitation data of 18 gauging stations for the Han River watershed in the past (1974-2015). This study utilizes a Bayesian parameter estimation approach to analyze the effects of climate change on future drought (2025-2065) in the Han River Basin using the Coupled Model Intercomparison Project Phase 6 (CMIP6) with four bias-corrected general circulation models (GCMs) under the Shared Socioeconomic Pathway (SSP)2-4.5 scenario. Given that drought is defined by several dependent variables, the evaluation of this phenomenon should be based on multivariate analysis. Two main characteristics of drought (severity and duration) were extracted from precipitation anomalies in the past and near-future periods using the copula function. Three parameters of the Archimedean family copulas, Frank, Clayton, and Gumbel copula, were selected to fit with drought severity and duration. The results reveal that the lower parts and middle of the Han River basin have faced severe drought conditions in the near future. Also, the bivariate analysis using copula showed that, according to both indicators, the study area would experience droughts with greater severity and duration in the future as compared with the historical period.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.499-499
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• 2018

Hydro-meteorological extremes are trivial in these days. Therefore, it is important to identify extreme hydrological events in advance to mitigate the damage due to the extreme events. In this context, exploring temporal distribution of sub-daily extreme rainfall at multiple rain gauges would informative to identify different states to describe severity of the disaster. This study proposehidden Markov chain model (HMM) based rainfall analysis tool to understand the temporal sub-daily rainfall patterns over South Korea. Hourly and daily rainfall data between 1961 and 2017 for 92 stations were used for the study. HMM was applied to daily rainfall series to identify an observed hidden state associated with rainfall frequency and intensity, and further utilized the estimated hidden states to derive a temporal distribution of daily extreme rainfall. Transition between states over time was clearly identified, because HMM obviously identifies the temporal dependence in the daily rainfall states. The proposed HMM was very useful tool to derive the temporal attributes of the daily rainfall in South Korea. Further, daily rainfall series were disaggregated into sub-daily rainfall sequences based on the temporal distribution of hourly rainfall data.

• International Journal of Computer Science & Network Security
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• 제21권5호
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• pp.23-30
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• 2021

In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

• International Journal of Aeronautical and Space Sciences
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• 제10권1호
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• pp.91-97
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• 2009

It is undertaken systematization of results of satellite and ground observation parameters characterizing a current condition and climatic variability of two selected geographical areas. One of them covers territory of Azerbaijan and another covers a wide area of Caspian See region. Average values and mean square deviations of following values are investigated: outgoing long wave radiation during a day and night (in nebulosity and cloudless). absorbed within a day of the stream of a sunlight of the system in "a terrestrial surface-atmosphere". degree of a covering by clouds of the selected areas during a day and at night, ground temperature values of air. pressure and speed of a wind. Monthly average values of corresponding parameters create a basis of suggested investigations. It has been presented features of a time course of investigated parameters for each month and year in the whole due to the continuously observations since 1982-2000. The scientific problem consists that there are no existed models which authentically would be cover the main aspects of a realities specified changes: they are identified by economic activities. growth of the population and other features of development of a human society or internal fluctuations of biogeophysical/climatic system. Possibilities of predictability of biosphere and climate changes depend on available timely supervision. adequacy of construction of appropriate models. understanding of mechanisms of direct and feedback influences in such complicated systems.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• 대한토목학회논문집
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• 제12권1호
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• pp.131-140
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• 1992

다목적댐의 유입량 예측과 더불어 유출량의 이용율을 극대화 하면서 홍수 피해를 극소화 시킬 수 있는 방류량을 결정할 수 있는 실시간(實時間) 홍수제어(洪水制御) 문제에 있어서는 수문(水文) 및 기상자료 등 많은 정보의 실시간(實時間) 온라인 취득과 컴퓨터를 사용한 분석이 필수적이다. 입수된 자료의 정확한 분석으로부터 내용이 압축된 컬러 그래픽 등 사람과 컴퓨터간의 대화매체를 도입하면 홍수방류를 결정할 수 있는 책임자에게 분석된 정보를 보다 쉽고 신속하게 전달할 수 있다. 개발된 PC-REFCON은 개인용 컴퓨터를 주축으로 한 실시간 홍수예측 및 저수지 운영을 위한 쇄신된 의사결정 지원 시스템으로서, 자료의 실시간 취득과 가공을 위한 데이타 베이스와 유입량 예측과 댐 방류량 결정을 위한 모형을 포함하였을 뿐 아니라 지금까지와는 전혀 새로운 차원으로 모든 정보를 그래픽과 테이블로 제공하여 주는 대화형 시tm템으로 구성되었다. PC-REFCON은 1992년부터 우리나라의 9개 전 다목적댐 저수지를 홍수시에 실시간으로 홍수량 예측과 방류량을 결정할 수 있는 시스템으로 이용될 것이다.

• 한국대기환경학회지
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• 제5권2호
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• pp.55-71
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• 1989

This study was carried out to determine the ozone concentration to behaviour and the factors to be influenced the variation of its concentration in the ambient air in Seoul. Measurements of ozone concentrations were made at 10 monitoring station to take care of SIHE (Seoul Institute of Health & Environment) during December 1987 to November 1988, also measured the hourly average concentration of sulfur dioxide, total suspended particulate, nitrogen oxide $(NO & NO_2)$, carbon monoxide, hydro carbon $(n-CH_4 & THC)$ and meteorological factors, that is, temperature, humidity, wind velocity wind direction and ultraviolet intensity etc, for the same period at same place. The basis of the data obtained were analyzed statistically along with the various data. The results were as follows; 1. The annually arithmetic mean concentration of ozone for the 10 sites during one years was 10.0 ppb and ranged from 3.1 $\pm$ 4.5ppb at the Kuro industrial complex to 17.2 $\pm$ 18.7 ppb at the Ssangmun site. 2. The frequency of hours on which oxidant concentrations exceeded the present short term standard of ozone (100 ppb) were 78 times. 3. The diurnal patterns of hourly ozone concentrations in Seoul area was a typical bi-modal variation which have 4 to 5 a.m. peak and 3. to 4 p.m peak. 4. The time ozone of highest ozone concentration in a whole day and hight was 1 to 5 p.m and 90.9 percent of appearence rate. 5. The diurnal patterns of hourly ozone concentrations in Seoul were on the whole the order of daytime from 5.8ppb to 28.7 ppb evening from 1.7 to 18.7 ppb night time from 1.9 to 9.3 ppb daybreak from 1.4ppb according to measuring sites, and the highest that observed at the Ssangmun area while the lowest was the Kuro industrial complex monitor sites. 6. The weekly variation of ozone concentration was the higher level ozone concentration in the day of the week occured sunday-monday and weekend but the decrease were observed from wednesday to thursday.

• 한국수자원학회논문집
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• 제54권10호
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• pp.835-848
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• 2021

제주도는 지질 및 수문계의 특이성으로 인해 수문기상인자 분석을 통한 수문 분석 및 효율적인 물관리가 필수적이다. 하지만 수문기상인자의 지상관측자료는 주변 환경에 의한 영향이 크게 작용하여 공간적인 대표성을 띄기 힘들며, 이를 극복하기 위해 원격탐사 방법이 사용된다. 본 연구에서는 제주도에서 기존에 다른 지역들에서 적용성이 검증된 바 있는 MOD16 증발산량, Global Land Data Assimilation System (GLDAS) 증발산량, GLDAS 토양수분, Advanced SCATerometer(ASCAT) 토양수분 산출물들의 적용성을 평가하였다. 증발산의 경우 강수량과의 총량 비교 및 플럭스타워 증발산량 관측자료와의 비교를 시행하였고, 토양수분의 경우 6개 토양수분 관측소의 관측자료와 비교하였다. 그 결과 증발산량의 경우 연 강수량의 57%가 증발산량으로 산출되었고, MOD16 증발산량과 GLDAS 증발산량의 상관계수는 0.759로 양호한 값이 산출되었으나, 플럭스타워 증발산량 데이터와 MOD16 증발산량의 상관계수는 0.289, GLDAS 증발산량과의 상관계수는 0.434로 상대적으로 적합성이 낮게 나타났다. 토양수분의 경우 GLDAS 자료의 경우 모든 지점에서 지점자료와 비교하였을 때 RMSE 값은 0.05 미만의 값을 나타냈고, 상관계수의 유의성 검정 결과 통계적으로 유의미한 결과를 얻었다. 하지만 위성자료의 경우 월각지점에서 0.05 이상의 RMSE 값이 나타났고, 세화, 한동 지점에서 상관성이 없다는 상관계수의 유의성 검정 결과를 확인하였다. 이는 제주도에 설치된 증발산량 및 토양수분 센서의 품질관리 및 공간대표성을 띄는 면단위 센서가 충분히 제공되지 않아 위와 같은 결과가 나타나는 것으로 판단된며 더불어 지점 자료의 관리 및 위성, 재분석 자료의 경우 관측 픽셀이 해안과 인접할 시 나타나는 오차로 추정된다. 본 연구를 통해 기존 수문기상인자 지상관측 자료의 개선 필요성을 역셜하고, 이를 통해 제주도에서의 효율적인 물관리 를 위한 기반을 구축하고자 한다.

• 한국습지학회지
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• 제20권2호
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• pp.105-115
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• 2018

수문기상자료의 빈도해석은 풍수해에 따른 대응 및 시설물의 설계기준에 있어 중요한 요소 중 하나이다. 일반적으로 수문기상자료에 대한 빈도해석의 경우 관측자료는 통계적으로 정상성을 가진다고 가정하고, 확률분포의 매개변수를 고려하는 매개변수적 방법을 적용하고 있다. 이러한, 매개변수적 빈도해석을 위해서는 신뢰성 있는 충분한 자료의 수집이 필요하지만, 강수량과 다르게 적설량의 경우 계절적 특성과 함께 최근에는 기후변화로 인한 적설량 관측일수 및 평균 최심신적설량이 감소하기 때문에 부족한 자료에 대한 문제점을 보완할 필요가 있다. 이에 본 연구에서는 매개변수 빈도해석 방법과 부족한 자료의 문제점을 보완할 수 있는 표본 재추출 기법인 Bootstrap방법과 SIR(Sampling Importance Resampling)알고리즘을 적용하여 적설량의 빈도해석을 실시하였다. 58개 기상관측소에 대해 재추출된 일 최대 최심신적설량 자료를 이용한 비매개변수적 빈도해석을 통해 확률적설량을 산정하고 이를 비교 분석하였다. 빈도별 확률적설량의 증감률을 검토한 결과 매개변수적 빈도해석과 비매개변수적 빈도해석에서 증감률을 나타내는 지점들이 대부분 일치하는 것으로 나타났다. 확률적설량은 관측 자료와 Bootstrap방법에서 -19.2%~3.9%, Bootstrap방법과 SIR알고리즘에서 -7.7%~137.8% 정도의 차이를 보였다. 표본 재추출 기법은 관측표본이 적은 적설량의 빈도해석 및 불확실성 범위의 제시가 가능함을 확인할 수 있었고, 이는 여름철 태풍과 같이 계절적 특성을 지닌 다른 자연재난의 해석에도 적용될 수 있을 것으로 판단된다.