• Journal of Korea Water Resources Association
• /
• v.56 no.2
• /
• pp.75-89
• /
• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.310-310
• /
• 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.

• Journal of Korea Water Resources Association
• /
• v.45 no.7
• /
• pp.729-741
• /
• 2012

Among the methods of precipitation data acquisition, a rain gauge station has a distinctive advantage of direct measurement of rainfall itself, but multiple stations should be installed in order to obtain areal precipitation data required for hydrological analysis. On the other hand, a rainfall radar may provide areal distribution of rainfall in real time though it is an indirect measurement of radar echoes on rain drops. Rainfall radars have been shown useful especially for forecasting short-term localized torrential storms that may cause catastrophic flash floods. CAPPI (Constant Altitude Plan Position Indicator), which is one of the several types of radar rainfall image data, has been provided on the Internet in real time by Korea Meteorological Administration (KMA). It is one of the most widely available rainfall data in Korea with fairly high level of confidence as it is produced with bias adjustment and quality control procedures by KMA. The objective of this study is to develop an improved way to extract quantitative rainfall data applicable to even very small watersheds from CAPPI using CIVCOM, which is a new image processing method based on a vector-based scheme proposed in this study rather than raster-based schemes proposed by other researchers. This study shows usefulness of CIVCOM through comparison of rainfall data produced by image processing methods including traditional raster-based schemes and a newly proposed vector-based one.

• Food Science of Animal Resources
• /
• v.25 no.4
• /
• pp.365-372
• /
• 2005

This study was carried out to investigate the Physiochemical Properties of loin and rump in the native horse meat from Jeju. In the analysis of chemical composition of loin and rump, the result showed $72.2\%\;and\;73.8\%$ in moisture content $20.1\%\;and\;21.2\%$ in crude protein, $2.42\%\;and\;3.08\%$ in crude Int and $0.13\%\;and\;0.14\%$ in crude ash respectively. Glutamic acid was 3,275mg/100g and 3,577mg/100g in loin and rump each and it had highest result in amino acid analysis. K content was 388.0mg/100g which showed highest result in mineral analysis and next contents were P>Na>Mg>Ca. Oleic acid had highest result in fatty acid composition which were $62.64\%\;and\;63.77\%$ in loin and rump respectively. Cholesterol content of loin and rump were 43.25 and 43.57 mg/100g but showed no significant differences to the part. pH of loin and rump were 5.60 and 5.75 which had no significant differences. Loin had Higher result than that of rump with no significant differences in WHC and springiness of texture analysis. Redness of rump was higher than that of loin. In the sensory evaluation, there were significant differences in the color and odor. Loin had higher result than that of rump in the overall palatability but showed no significant differences. With the result of this experiment native horse meat from Jeju could be understood as good meat resources.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.4
• /
• pp.211-217
• /
• 2004

The instrument used in this study consists of a lkg capacity loadcell and a Imm tipping bucket rain gauge. There are two signals: one is the weight of the water in the tipping bucket and the other is the pulse from the reversing mechanism of the tipping bucket. The loadcell measures the weight of water with a 0.0lmm resolution up to 1mm rainfall and the bucket reverses beyond 1mm. From this point, a pulse signal generates and the loadcell starts measuring the weight again. A field test was carried out with the range of rainfall intensity from 42mm/h to 250mm/h. The result shows an error range from -2.2% to + 2.6% in 12 measurement cases with a rainfall of l00mm or more. This result satisfies the WMO recommendation for rainfall intensity instrumentation which allows a 5% range. In a field experiment during 17 to 19 August, 2004, more than 100mm/h rainfall intensity was observed by this instrument, confirming that our instrument has a sufficient capacity of rainfall intensity measurement under extreme conditions like Jangma (Bai-u season). Compared with existing commercial models which employ a water drop measurement method, our method can give a practical solution for diagnostic check of remote rain gauges using two independent signals.