• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.75-77
• /
• 2003

The spatial distribution of snow cover area is a crucial input to models of hydrology and climate in alpine and other seasonally snow covered areas.The objective in our study is to develop a rapidly automatic and high accuracy snow cover mapping algorithm applicable for the Tibetan Plateau which is the most sensitive about climatic change. Monitoring regional snow extent reqires higher temoral frequency-moderate spatial resolution imagery.Our algorithm is based AVHRR and MODIS data and will provide long-term fraction snow cover area map.We present here a technique is based on the multiple endmembers approach and by taking advantages of current approaches, we developed a technique for automatic selection of local reference spectral endmembers.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2012년도 학술발표회
• /
• pp.258-258
• /
• 2012

In frequency analyses of hydrological data, it is necessary for the interested variables to be homogenous and independent. However, recent evidences have shown that the occurrence of extreme hydro-meteorological events is influenced by large-scale climate variability, and the assumption of homogeneity does not generally hold anymore. Therefore, in order to associate the non-homogenous characteristics of hydro-meteorological variables, we propose the parameter estimation method of probability models using meta-heuristic algorithms, specifically harmony search. All the weather stations in South Korea were employed to demonstrate the performance of the proposed approaches. The results showed that the proposed parameter estimation method using harmony search is a comparativealternative for the probability distribution of the non-homogenous hydro-meteorological variables data.

• Communications for Statistical Applications and Methods
• /
• 제25권6호
• /
• pp.619-631
• /
• 2018

Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2021년도 학술발표회
• /
• pp.135-135
• /
• 2021

In water resources management, rainfall prediction with high accuracy is still one of controversial issues particularly in countries facing heavy rainfall during wet seasons in the monsoon climate. The aim of this study is to develop an artificial neural network (ANN) for predicting future six months of rainfall data (from April to September 2020) from daily meteorological data (from 1971 to 2019) such as rainfall, temperature, wind speed, and humidity at Seoul, Korea. After normalizing these data, they were trained by using a multilayer perceptron (MLP) as a class of the feedforward ANN with 15,000 neurons. The results show that the proposed method can analyze the relation between meteorological datasets properly and predict rainfall data for future six months in 2020, with an overall accuracy over almost 70% and a root mean square error of 0.0098. This study demonstrates the possibility and potential of MLP's applications to predict future daily rainfall patterns, essential for managing flood risks and protecting water resources.

• 대한토목학회논문집
• /
• 제32권1B호
• /
• pp.29-39
• /
• 2012

기후변화는 전 세계적으로 많은 관심을 얻고 있으며 수자원 분야에서도 그로 인한 변화에 대응하기 위해 많은 연구를 하고 있다. 본 연구에서는 기존의 강우관측소, 레이더 등을 사용한 강우가 아닌 전 지구적 바람장과 온도, 기후 등의 이동 등을 계산하는 기후모델 WRF-ARW를 이용하여 공간 분포된 강우 자료의 사용가능성을 평가해 보려한다. 이를 위하여 청미천 유역을 격자 형식으로 구분 할 수 있는 분포형 모형인 ModClark은 WRF-ARW의 강우자료를 이용하고, 집중형 모형은 강우관측소 강우자료를 사용하여 이들을 청미천 수위관측소 유출자료와 비교하였다. 대상유역에 대하여 유출모의를 수행한 결과 WRF-ARW의 강우자료를 이용한 분포형 모형의 유출곡선은 관측된 유출곡선과 비교 시 첨두시간과 첨두 유출량이 유사하였으며 전체적인 유출곡선의 경향도 실제 유출곡선의 경향을 추구하는 것을 볼 수 있었다.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2019년도 학술발표회
• /
• pp.155-155
• /
• 2019

The Agricultural Policy/Environmental eXtender (APEX) models have been developed for assessing agricultural management efforts and their effects on soil and water at the field scale as well as more complex multi-subarea landscapes, whole farms, and watersheds. National Academy of Agricultural Sciences, Wanju, Korea, has modified a key component of APEX application, named APEX-Paddy for simulating water quality with considering appropriate paddy management practices, such as puddling and flood irrigation management. Calibration and validation are an anticipated step before any model application. Simple techniques are essential to assess whether or not a parameter should be adjusted for calibration. However, very few study has been done to evaluate the ability of APEX-Paddy to simulate the impact of multiple management scenarios on nutrients loss. In this study, the observation data from experimental fields at Iksan in South Kora was used in calibration and evaluation process during 2013-2015. The APEX auto- calibration tool (APEX-CUTE) was used for model calibration and sensitivity analysis. Four quantitative statistics, the coefficient of determination ($R^2$),Nash-Sutcliffe(NSE),percentbias(PBIAS)androotmeansquareerror(RMSE)were used in model evaluation. In this study, the hydrological process of the modified model, APEX-Paddy, is being calibrated and tested in predicting runoff discharge rate and nutrient yield. Field-scale calibration and validation processes are described with an emphasis on essential calibration parameters and direction regarding logical sequences of calibration steps. This study helps to understand the calibration and validation way is further provided for applications of APEX-Paddy at the field scales.

• 문화기술의 융합
• /
• 제9권3호
• /
• pp.811-816
• /
• 2023

기후 위기가 대두되며 최근 한국에서도 기후 재난이 선명하게 체감되고 있다. 특히 2022년 여름에 발생한 태풍 '힌남노'는 가공할만한 위력으로 많은 사람이 위기감을 느끼게 했다. 이러한 상황에서 아동들은 재난 상황에 대한 경험과 대처 능력이 부족하여 작은 위기에도 큰 피해를 받을 가능성이 높다. 본 논문에서는 아동들의 재난 대처 훈련을 지원하는 재난 상황 대처법 학습 애플리케이션을 소개한다. 상황학습이론과 아동 재난안전교육에 대한 연구 결과를 바탕으로 설계된 본 시스템에서는 다양한 에피소드를 제작하여 재난 상황을 접하도록 교육한다. 아동은 에피소드 진행 중 선택지를 고르며 에피소드에 참여할 수 있고, 이는 에피소드 완료후 그림일기에 반영된다. 그림일기 속에 자연스럽게 정보를 제공하여 아동은 재난 상황에서의 대처법에 대해 접할 수있다. 본 시스템을 통해 아동은 본인이 접할 수 있는 재난 상황에서 판단력을 기르고, 성인의 도움 밖에서 기본적인 안전을 확보하는 능력을 지닐 수 있을 것으로 기대된다.

• 분석과학
• /
• 제36권5호
• /
• pp.236-249
• /
• 2023

Carbon dioxide (CO₂) capture and storage is a critical issue for mitigating climate change. Porous aromatic Schiff base complexes have emerged as a promising class of materials for CO₂ capture due to their high surface area, porosity, and stability. In this study, we investigate the potential of Schiff base complexes as an effective media for CO₂ storage. We review the synthesis and characterization of porous aromatic Schiff bases materials complexes and examine their CO₂ sorption properties. We find that Schiff base complexes exhibit high CO₂ adsorption capacity and selectivity, making them a promising candidate for use in carbon capture applications. Moreover, we investigate the effect of various parameters such as temperature, and pressure on the CO₂ adsorption properties of Schiff base complexes. The Schiff bases possessed tiny Brunauer-Emmett-Teller surface areas (4.7-19.4 m²/g), typical pore diameters of 12.8-29.43 nm, and pore volumes ranging from 0.02-0.073 cm³/g. Overall, our results suggest that synthesized complexes have great potential as an effective media for CO₂ storage, which could significantly reduce greenhouse gas emissions and contribute to mitigating climate change. The study provides valuable insights into the design of novel materials for CO₂ capture and storage, which is a critical area of research for achieving a sustainable future.

• Ocean Systems Engineering
• /
• 제14권1호
• /
• pp.85-99
• /
• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• 한국농림기상학회지
• /
• 제24권2호
• /
• pp.83-94
• /
• 2022

농작물 생육 과정에서 서리에 의한 동상해 피해에 능동적으로 대비하기 위해, 지난 21년간(2000~2020) 20개 지역의 서리관측 자료를 이용하여 한국 서리발생의 시공간적 분포 특성을 살폈다. 지역별 서리분포 특성은 서리일수, 첫 서리일, 끝 서리일로 표현하였다. 그리고 이러한 결과의 기후 경향은 Mann-Kendall trend test와 Sen's slope estimator를 수행하여 확인하였다. 한국에서 대부분의 서리는 태백산맥과 소백산맥 서쪽 내륙지방에서 발생한다. 상대적으로 해안지역에 가까울수록 서리 발생일이 적고 첫서리일이 느리며 끝서리일이 빠르다. 동해안지역은 서해안지역보다 서리일수가 적고 첫서리일이 느리며 끝서리일이 빠르다. 남해, 남동해, 도서지역은 거의 서리가 발생하지 않는다. 연간 시계열 추이 분석결과 한국은 기후온난화가 진행됨에도 불구하고, 서리일수가 줄어들거나 첫서리 일이 늦춰지는 경향은 나타나지 않았으며, 끝서리일은 1년에 0.5일씩 늦춰지는 것으로 나타났다.