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기후변화시나리오와 비정상성 빈도분석을 이용한 도시유형별 목표연도 설계강우량 제시 및 치수안전도 변화 전망
정세진,강동호,김병식,Jeung, Se-Jin,Kang, Dong-Ho,Kim, Byung-Sik 한국환경과학회 2020 한국환경과학회지 Vol.29 No.9
Due to recent heavy rain events, there are increasing demands for adapting infrastructure design, including drainage facilities in urban basins. Therefore, a clear definition of urban rainfall must be provided; however, currently, such a definition is unavailable. In this study, urban rainfall is defined as a rainfall event that has the potential to cause water-related disasters such as floods and landslides in urban areas. Moreover, based on design rainfall, these disasters are defined as those that causes excess design flooding due to certain rainfall events. These heavy rain scenarios require that the design of various urban rainfall facilities consider design rainfall in the target years of their life cycle, for disaster prevention. The average frequency of heavy rain in each region, inland and coastal areas, was analyzed through a frequency analysis of the highest annual rainfall in the past year. The potential change in future rainfall intensity changes the service level of the infrastructure related to hand-to-hand construction; therefore, the target year and design rainfall considering the climate change premium were presented. Finally, the change in dimensional safety according to the RCP8.5 climate change scenario was predicted.
데이터 스크린 기법을 이용한 연강수량의 통계적 특성 분석
정세진,임가균,김병식,Jeung, Se-Jin,Lim, Ga-Kyun,Kim, Byung-Sik 한국방재안전학회 2020 한국방재안전학회 논문집 Vol.13 No.3
본 논문에서는 미계측 유역에 적용할 수 있는 갈수지수 산정 회귀모형을 개발하고자 하였다. 30개의 중권역 유역을 대상으로 국가수자원종합관리시스템에서 제공하는 장기유출자료를 이용하여 평균 갈수량과 평균저수량, 지속기간별 빈도별 갈수지수를 산정하였으며 이를 유역특성인자 18개와 기상특성인자 3개와의 상관 분석을 통하여 최종적으로 유역면적, 유역 평균 표고, 유역 평균 경사, 수계 밀도, 유출곡선지수, 연증발산량, 연강수량을 선정하여 다중회귀분석을 수행하여 갈수지수 회귀모형을 개발하였다. 개발된 회귀모형을 평가하기 위하여 10개의 검증유역을 미계측 유역으로 간주하여 평균제곱근오차(RMSE) 와 평균절대오차(MAE)를 이용하여 정확도를 추정하였다. 또한 기존의 평균갈수량 산정 회귀모형과의 비교를 통하여 본 논문에서 개발한 모형의 우수성을 검토하였다. 기존의 미계측 유역의 평균 갈수량 회귀모형과 비교·분석에서 보다 우수한 결과를 나타내었는데 이는 기존의 회귀모형보다 다양한 유역 특성인자와 수문특성인자를 고려하여 회귀모형을 개발하였기 때문인 것으로 판단된다. Hydrological data is very important in understanding the hydrological process and identifying its characteristics to protect human life and property from natural disasters. In particular, hydrological analysis are often performed assuming that hydrological data are stationary. However, recently climate change has raised the issue of climate stationary, and it is necessary to analyze the nonstationary of the climate. In this study, a method to analyze the stationarity of hydrological data was examined using the annual precipitation of 37 meteorological stations with long - term record data. Therefore, in this study, the stationary was determined by analyzing the persistence, trend, and stability using annual precipitation. Overall results showed that a trend was observed in 4 out of 37 stations, stable was investigated at 15 stations, and persistence was shown at 4 stations. In the stationary analysis using the annual precipitation data, 25 stations (67% of 37 stations) were nonstationary.
비정상성 기반 SPIt를 이용한 가뭄의 시·공간적 특성 분석
정세진(Se Jin Jeung),강동호(Dong Ho Kang),김병식(Byung Sik Kim) 위기관리 이론과 실천 2020 Crisisonomy Vol.16 No.12
기상학적 가뭄지수 분석에 자주 이용되는 SPI지수는 정상성 기반 즉 시계열의 확률적인 성질들이시간의 흐름에 따라 변하지 않는 정상성 기반으로 분석이 진행된다. 이는 기후변화와 기후변동 같은시간이 지남에 따라 변화하는 정보를 충분히 반영하기에 한계가 있다. 이에 본 연구에서는 기존의정상성 가정에 근거한 SPI 지수 산정과는 다른 비정상성(Non-stationarity)을 고려할 수 있는 새로운빈도분석 방법인 SPIt를 사용하고자 한다. 먼저 일 강수자료를 이용하여 7일 지속기간의 강수 시계열을 구축하였다. 가뭄지속기간은 월단위와 주단위를 기준으로 3개월의 SPI와 SPIt를 계산하고 과거긴급제한급수지역을 대상으로 각 지수의 재현성를 확인하였다. 또한 전국 기상관측소를 기준으로SPI지수와 SPIt지수를 산정하고 공간분포도를 작성하여 공간적인 재현성을 확인하였다. The SPI index was developed based on the fact that when drought occurs when reduced precipitation causes water shortage relative to the required water demand. However, the SPI index works under the assumption of stationarity or normality in which the probabilistic properties of the time series data do not change over time. It has limitations in reflecting information changing over time sufficiently, such as climate change. In this study, we used SPIt, a new frequency analysis method considering non-stationarity, which is different from the existing SPI index calculation. We first used daily precipitation data to construct the time series data of 7-day precipitation. For the duration of drought, both SPI and SPIt indices for 3 months were calculated on a monthly and weekly basis, and the reproducibility of each index was assessed for the areas experiencing restricted water supply. In addition, both indices were calculated for all national meteorological stations in South Korea, which was used to create a spatial distribution map and confirm their spatial reproducibility.
다중회귀분석을 이용한 미계측 유역의 갈수지수 산정에 관한 연구
임가균,정세진,김병식,채수권,Lim, Ga Kyun,Jeung, Se Jin,Kim, Byung Sik,Chae, Soo Kwon 한국수자원학회 2020 한국수자원학회논문집 Vol.53 No.12
This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.