• Title/Summary/Keyword: 가상관측소

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Area Rainfall Estimation Error for Each Types of Weather Radar Composite Images (기상레이더 합성영상 종류별 면적강수량 추정오차)

  • Tae-Jeong Kim;Jang-Gyeong Kim;Jae-Hyun Song;Chung-Dea Lee;Hyun-Han Kwon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.310-310
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    • 2023
  • 기상레이더는 강우의 공간분포를 관측하고 강우장 이동특성을 예측하여 집중호우, 태풍 등에 대비할 수 있는 시간을 확보하기 위하여 운용되고 있다. 기상레이더는 전파를 송신하고 대기 중의물체(수상체, 건물 등)에 부딪혀 되돌아오는 신호를 수신하여 강우의 양, 분포, 이동방향 등을 산정할 수 있으며 세부적으로 입체관측(volume scan)을 반복하여 고도각 별로 거리와 방위각에 따라 다양한 합성영상을 산출할 수 있는 특성이 있다. 본 연구는 구름의 수평적 분포를 파악하는데 용이하여 기존에 널리 사용된 CAPPI 합성영상과 최근 현업에서 복잡한 지형으로 인한 오차를 해소하고자 광범위하게 사용되고 있는 다중 고도각 기반 레이더 강수량(hybrid surface rainfall, HSR) 합성영상을 취득하여 수문해석을 위한 유역단위 면적강수량의 추정오차를 검토하였다. HSR 합성영상은 우리나라와 같이 산악지형이 많이 존재하는 경우 지형의 영향을 받지 않아 지면에 가장 가까운 고도각의 관측자료를 사용하므로 지상관측소 강수량과 비교한 결과에서 기존의 CAPPI 합성영상 레이더 강수량과 통계적 효율 기준을 산정하여 레이더 강수의 품질이 개선되는 것을 확인하였다. 최근 환경부에서 추진하고 있는 인공지능(AI) 홍수예보 및 가상모형(Digital Twin)을 활용하여 홍수정보를 생산 및 전달하는 과정에서 유역의 지형적 특성을 현실적으로 고려한 레이더 강수량을 사용함으로 기후변화에 따라 국지적으로 발생하는 집중호우 대응 및 과학적 홍수관리를 실현할 수 있을 것으로 판단된다.

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Application of SWAT Model considering Spatial Distribution of Rainfall (강우의 공간분포를 고려한 SWAT 모형의 적용)

  • JANG, Daewon;KIM, Duckgil;KIM, Yonsoo;Choi, Wooil
    • Journal of Wetlands Research
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    • v.20 no.1
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    • pp.94-104
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    • 2018
  • In general, the rainfall-runoff simulation is performed using rainfall data from meteorological and observational rain gauge stations. However, if we only use rainfall data from meteorological and observational rain gauge stations for runoff simulation of a large watershed, the problem in the reliability of the simulated runoff can be occurred. Therefore, this study examined the influence of the rainfall data on the simulated runoff volume by a Semi-distributed model. For this, we used rainfall data from meteorological stations, meteorological and observational stations, and a spatially distributed rainfall data from hypothetical stations obtained by kriging method. And, we estimated the areal rainfall of each sub-basin. Also the estimated areal rainfall and the observed rainfall were compared and we compared the simulated runoff volumes using SWAT model by the rainfall data from meteorological and observational rain gauge stations and runoff volume from the estimated areal rainfall by Kriging method were analyzed. This study was performed to examine the accuracy of calculated runoff volume by spatially distributed areal rainfall. The analysis result of this study showed that runoff volume using areal rainfall is similar to observed runoff volume than runoff volume using the rainfall data of weather and rain gauging station. this means that spatially distributed rainfall reflect the real rainfall pattern.

궤도상 위성의 광학관측가능성 해석을 위한 궤도전파 시뮬레이터 개발

  • Kim, Jae-Hyeok;Jo, Jung-Hyeon;Park, Chan-Deok;Park, Sang-Yeong;Mun, Hong-Gyu;Im, Hong-Seo;Choe, Yeong-Jun;Choe, Jin;Park, Jang-Hyeon
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.2
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    • pp.163.1-163.1
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    • 2012
  • 이 연구는 우주물체에 대한 광학감시 및 추적을 수행하기 위한 선행연구로, 궤도전파 시뮬레이터를 개발하여 궤도상 위성의 광학관측가능성을 분석하고 광학관측 여부를 판단하는 것을 목표로 한다. 연구의 주 내용은 주어진 궤도정보를 바탕으로 하는 태양동기궤도(Sun-Synchronous Orbit; SSO) 위성, Dawn-dusk 위성, 저궤도(Low Earth Orbit; LEO) 위성, 정지궤도(Geostationary Orbit; GEO) 위성 등 궤도상 위성의 추정궤도 전파와 자국위성의 광학관측가능성 분석으로 구성된다. 각각의 궤도전파 정밀도 및 광학관측가능성 분석성능을 확인하기 위해 AGI(Analytical Graphics Incorporated)사의 STK(Satellite Tool Kit) 시뮬레이션 프로그램을 사용하여 개발된 궤도전파 시뮬레이터와 비교하였다. 시뮬레이션 과정에서 광학관측의 제한조건을, 지구반영(penumbra)과 태양직사광(direct sun)에서만 관측하며, 고도(elevation angle)의 최소값은 20도, 태양고도(Sun elevation angle)의 최대값은 -10도로 설정하였다. 광학관측이 이루어지는 가상의 관측소는 임의로 선정하였으며, 기본적인 관측시간은 1년으로 잡고, 계절의 변화에 따른 광학관측가능성 궤적의 변화를 보기위해 춘하추동에 대해서 각각 3일이내의 기간 동안 시뮬레이션을 수행하였다. 결과적으로, 우주물체 광학감시 및 추적을 수행하기 위한 광학관측가능성 분석성능은 궤도전파 시뮬레이터 및 초기궤도요소 정밀도, 좌표변환과정 오차 등의 영향을 받으며, 설정된 제한조건에 따라 광학관측 지속시간의 차이가 발생한다. 연구결과를 통해 궤도상 위성의 궤도를 추정하기 위한 위성의 궤도전파 시뮬레이터를 개발하고, 자국위성의 관측가능성 분석을 통해 광학감시 및 추적시스템의 운영이 원활히 이루어질 수 있도록 한다.

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The Impacts on Flow by Hydrological Model with NEXRAD Data: A Case Study on a small Watershed in Texas, USA (레이더 강수량 데이터가 수문모델링에서 수량에 미치는 영향 -미국 텍사스의 한 유역을 사례로-)

  • Lee, Tae-Soo
    • Journal of the Korean Geographical Society
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    • v.46 no.2
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    • pp.168-180
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    • 2011
  • The accuracy of rainfall data for a hydrological modeling study is important. NEXRAD (Next Generation Radar) rainfall data estimated by WRS-88D (Weather Surveillance Radar - 1988 Doppler) radar system has advantages of its finer spatial and temporal resolution. In this study, NEXRAD rainfall data was tested and compared with conventional weather station data using the previously calibrated SWAT (Soil and Water Assessment Tool) model to identify local storms and to analyze the impacts on hydrology. The previous study used NEXRAD data from the year of 2000 and the NEXRAD data was substituted with weather station data in the model simulation in this study. In a selected watershed and a selected year (2006), rainfall data between two datasets showed discrepancies mainly due to the distance between weather station and study area. The largest difference between two datasets was 94.5 mm (NEXRAD was larger) and 71.6 mm (weather station was larger) respectively. The differences indicate that either recorded rainfalls were occurred mostly out of the study area or local storms only in the study area. The flow output from the study area was also compared with observed data, and modeled flow agreed much better when the simulation used NEXRAD data.

Performance Test of Hypocenter Determination Methods under the Assumption of Inaccurate Velocity Models: A case of surface microseismic monitoring (부정확한 속도 모델을 가정한 진원 결정 방법의 성능평가: 지표면 미소지진 모니터링 사례)

  • Woo, Jeong-Ung;Rhie, Junkee;Kang, Tae-Seob
    • Geophysics and Geophysical Exploration
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    • v.19 no.1
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    • pp.1-10
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    • 2016
  • The hypocenter distribution of microseismic events generated by hydraulic fracturing for shale gas development provides essential information for understanding characteristics of fracture network. In this study, we evaluate how inaccurate velocity models influence the inversion results of two widely used location programs, hypoellipse and hypoDD, which are developed based on an iterative linear inversion. We assume that 98 stations are densely located inside the circle with a radius of 4 km and 5 artificial hypocenter sets (S0 ~ S4) are located from the center of the network to the south with 1 km interval. Each hypocenter set contains 25 events placed on the plane. To quantify accuracies of the inversion results, we defined 6 parameters: difference between average hypocenters of assumed and inverted locations, $d_1$; ratio of assumed and inverted areas estimated by hypocenters, r; difference between dip of the reference plane and the best fitting plane for determined hypocenters, ${\theta}$; difference between strike of the reference plane and the best fitting plane for determined hypocenters, ${\phi}$; root-mean-square distance between hypocenters and the best fitting plane, $d_2$; root-mean-square error in horizontal direction on the best fitting plane, $d_3$. Synthetic travel times are calculated for the reference model having 1D layered structure and the inaccurate velocity model for the inversion is constructed by using normal distribution with standard deviations of 0.1, 0.2, and 0.3 km/s, respectively, with respect to the reference model. The parameters $d_1$, r, ${\theta}$, and $d_2$ show positive correlation with the level of velocity perturbations, but the others are not sensitive to the perturbations except S4, which is located at the outer boundary of the network. In cases of S0, S1, S2, and S3, hypoellipse and hypoDD provide similar results for $d_1$. However, for other parameters, hypoDD shows much better results and errors of locations can be reduced by about several meters regardless of the level of perturbations. In light of the purpose to understand the characteristics of hydraulic fracturing, $1{\sigma}$ error of velocity structure should be under 0.2 km/s in hypoellipse and 0.3 km/s in hypoDD.

Improvement of the Method using the Coefficient of Variation for Automatic Multi-segmentation Method of a Rating Curve (수위-유량관계곡선의 자동구간분할을 위한 변동계수 활용기법의 개선)

  • Kim, Yeonsu;Kim, Jeongyup;An, Hyunuk;Jung, Kwansue
    • Journal of Korea Water Resources Association
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    • v.48 no.10
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    • pp.807-816
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    • 2015
  • In general, the water stage-discharge relationship curve is established based on the assumptions of linearity and homoscedasticity. However, the relationship between the water stage and discharge is affected from geomorphological factors, which violates the basic assumptions of the water stage-discharge relationship curve. In order to reduce the error due to the violations, the curve is divided into several sections based on the manager's judgement considering change of cross-sectional shape. In this research, the objective-splitting criteria of the curve is proposed based on the measured data without the subjective decision. First, it is assumed that the coefficient of variation follows the normal distribution. Then, if the newly calculated coefficient of variation is outside of the 95% confidential interval, the curve is divided. Namely, the groups is divided by the characteristics of the coefficient of variation and the reasonable criteria is provided for establishing a multi-segmented rating curve. To validate the proposed method, it was applied to the data generated by three artificial power functions. In addition, to confirm the applicability of the proposed method, it is applied to the water stage and discharge data of the Muju water stage gauging station and Sangegyo water stage gauging station. As a result, it is found that the automatically divided rating curve improves the accuracy and extrapolation accuracy of the rating curve. Finally, through the residual analysis using Shapiro-Wilk normality test, it is confirmed that the residual of water stage-discharge relationship curve tends to follow the normal distribution.

A Spatial Interpolation Model for Daily Minimum Temperature over Mountainous Regions (산악지대의 일 최저기온 공간내삽모형)

  • Yun Jin-Il;Choi Jae-Yeon;Yoon Young-Kwan;Chung Uran
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.2 no.4
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    • pp.175-182
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    • 2000
  • Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

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