• Title/Summary/Keyword: Observed Rainfall

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Maximum Areal Rainfall of Korea in the 20th Century (20세기 우리나라 관측최대강수량의 특성)

  • Kim, Nam-Won;Won, Yoo-Seung
    • Journal of Korea Water Resources Association
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    • v.37 no.5
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    • pp.425-435
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    • 2004
  • Mainly, observed maximum rainfall has been evaluated by point rainfall, but actually it should be considered by means of average areal rainfall. Average areal rainfall is an estimated value computed through DAD(rainfall Depth-Area-Duration) analysis. By using this value, an average and maximum areal rainfall according to area-duration relationship could be computed. In this study, we assume that the whole Korea region is hydrologically homogeneous, and then analyze using the storm-centered DAD(moving-area DAD) method for the past century data. From this analysis, we evaluate the yearly variation of observed maximum areal rainfall through area-duration relationship. And we also construct an IDF(rainfall Intensity-Duration-Frequency) curve by using the annual time series data which is composed of maximum areal rainfall. The characteristics of IDF and observed maximum areal rainfall is also evaluated.

Estimation of Regional Probable Rainfall based on Climate Change Scenarios (기후변화 시나리오에 따른 지역별 확률강우량)

  • Kim, Young-Ho;Yeo, Chang-Geon;Seo, Geun-Soon;Song, Jai-Woo
    • Journal of the Korean Society of Hazard Mitigation
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    • v.11 no.3
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    • pp.29-35
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    • 2011
  • This research proposes the suitable method for estimating the future probable rainfall based in 2100 on the observed rainfall data from main climate observation stations in Korea and the rainfall data from the A1B climate change scenario in the Korea Meteorological Administration. For all those, the frequency probable rainfall in 2100 was estimated by the relationship between average values of 24-hours annual maximum rainfalls and related parameters. Three methods to estimate it were introduced; First one is the regressive analysis method by parameters of probable distribution estimated by observed rainfall data. In the second method, parameters of probable distribution were estimated with the observed rainfall data. Also the rainfall data till 2100 were estimated by the A1B scenario of the Korea Meteorological Administration. Last method was that parameters of probable distribution and probable rainfall were estimated by the A1B scenario of the Korea Meteorological Administration. The estimated probable rainfall by the A1B scenario was smaller than the observed rainfall data, so it is required that the estimated probable rainfall was calibrated by the quantile mapping method. After that calibration, estimated probable rainfall data was averagely became approximate 2.3 to 3.0 times. When future probable rainfall was the estimated by only observed rainfall, estimated probable rainfall was overestimated. When future probable rainfall was estimated by the A1B scenario, although it was estimated by similar pattern with observed rainfall data, it frequently does not consider the regional characteristics. Comparing with average increased rate of 24-hours annual maximum rainfall and increased rate of probable rainfall estimated by three methods, optimal method of estimated future probable rainfall would be selected for considering climate change.

Runoff Analysis using Spatially Distributed Rainfall Data (공간 분포된 강우를 이용한 유출 해석)

  • Lee, Jong-Hyeong;Yoon, Seok-Hwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.47 no.6
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    • pp.3-14
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    • 2005
  • Accurate estimation of the spatial distribution of rainfall is critical to the successful modeling of hydrologic processes. The objective of this study is to evaluate the applicability of spatially distributed rainfall data. Spatially distributed rainfall was calculated using Kriging method and Thiessen method. The application of spatially distributed rainfall was appreciated to the runoff response from the watershed. The results showed that for each method the coefficient of determination for observed hydrograph was $0.92\~0.95$ and root mean square error was $9.78\~10.89$ CMS. Ordinary Kriging method showed more exact results than Simple Kriging, Universal Kriging and Thiessen method, based on comparison of observed and simulated hydrograph. The coefncient of determination for the observed peak flow was 0.9991 and runoff volume was 0.9982. The accuracy of rainfall-runoff prediction depends on the extent of spatial rainfall variability.

Appropriateness analysis of design rainfall factors using the rainfall data of an inundated flood events (침수 홍수사상의 강우자료를 활용한 설계강우 요소의 적정성 분석)

  • Yu, Byeong-Wook;Kim, Seon-Ho;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.53 no.4
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    • pp.237-247
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    • 2020
  • The purpose of this study is to analyze whether design rainfall and hyetograph, which are the main elements of design rainfall, can properly reflect the those of observed rainfalls through inundated rainfall events. The target areas were selected at seven large cities with high damages regarding to the flooding. Comparative analysis between probability and observed rainfall shows that 57% of the cases, in which rainfall amount through the IDF curve is estimated lower than the observed rainfall, do not properly reflect the observed rainfalls. In particular, this trend is exacerbated by the cases in low return period and the rain type of typhoon or frontal rain. The comparative results of rainfall intensity formula showed that the Talbot and Japanese formula were stable in the short- and long-term return periods, respectively. The comparison of hyetograph results also showed that the Mononobe method properly reflects the maximum rainfall intensity and the Huff method properly reflects the shape of rainfall pattern.

A study on the rainfall runoff from paddy fields in the small watershed during Irrigation period (관개기관중 답유역에서의 강우유출량 추정에 관한 연구)

  • 김채수
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.24 no.4
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    • pp.99-108
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    • 1982
  • This thesis aims to estimate the rainfall runoff from paddy field in a small watershed during irrigation period. When the data observed at the proposed site are not available, the Monthly Runoff Equation of Korean Rivers which was derived from data observed under the following assumptions is used to study the water balance. a. Monthly base flow was assumed as 10. 2mm even if these is no mouthly rainmfall. b. Monthly comsumption of rainfall was ranged from 100 to 2OOmm without relation to the rainfall depth. However, the small watershed which consists mainly of paddy fields encounters severe droughts and accordingly the baseflow is negligible. Under the circumstances the author has developed the following equation called "Flood Irrigation Method for Rainfall Runoff "taking account of the evapotranspiration, precipitation, seepage, less of transportation, etc. R= __ A 7000(1 +F) -5n(n+1)+ (n+1)(Pr-S-Et)] where: R: runoff (ha-m) A: catchment area (ha) F: coefficient of loss (o.o-0. 20) Pr: rainfall (mm) S: seepage Er: evapotranspiration (mm) To verify the above equation, the annual runoff ratio for 28 years was estimated using the Monthly Runoff Equation of Korean Rivers the Flood Irrigation Method and the Complex Hydrograph Method based on meteorological data observed in the Dae Eyeog project area, and comparison was made with data observed in the Han River basin. Consequently, the auther has concluded that the Flood Irrigation Method is more consi- stent with the Complex Hydrograph Method and data observed than the Monthly Runoff Equation of Korean Rivers.

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An intercomparison of GMS image data and observed rainfall data (GMS 영상자료와 관측강수량 자료의 비교)

  • 서애숙;이미선;김금란;이희훈
    • Korean Journal of Remote Sensing
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    • v.10 no.1
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    • pp.1-14
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    • 1994
  • The purpose of this study is to find the relationship between GMS image data and hourly observed rainfalls data. Heavy rainfall cases over South Korea on 10th September 1990 and on 29th July 1993 were selected for studying of the relationship between the image data and reinfalls. First, image data were converted to TBB(Temperature of Black Body) and albedo and then these values were extracted for the pixels closest to the surface observation station to correlate with the rainfall data. Horizontal distribution of TBB and albedo tells roughly rainfall regions. The correlation between rainfall and TBB is found to be very low in quantitative analysis. The weak relationship between the brighter albedo and the higher rainfall probability is observed. This study suggests that the TBB values are useful in classifying rain areas and for heavy rainfalls the albedo values are more useful than the TBB. Low linear correlation between the fields may be attributed to the neglect of cloud types in this study.

Estimation of Design Rainfall Considering the Change of the Number of Years for Observed Data (관측년수변화를 고려한 설계강우량 산정)

  • Ryoo, Kyong-Sik;Lee, Soon-Hyuk;Hwang, Man-Ha;Lee, Sang-Jin
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2005.10a
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    • pp.284-287
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    • 2005
  • The objective of this study is to check into variation trends of design rainfall according to change of the number of years for observed data. To make comparative study of the relation between design rainfall and recorded year, this study was used maximum rainfall for 24-hr consecutive duration at Gangneung, Seoul, Incheon, Chupungnyeong, Pohang, Daegu, Jeonju, Ulsan, Gwangju, Busan, Mokpo and Yeosu rainfall stations. The tests for Independence, Homogeneity and detection of outliers were used Wald-Wolfowitz's test, Mann-Whitney's test and Grubbs and Beck test respectively. To select appopriate distribution, the distribution of genaralized pareto(GPA), generalized extreme value(GEV), generalized logistic(GLO), lognormal and pearson type 3 distribution is judged by L-moment ratio diagram and Kolmogorov-Smirnov (K-S) test. Design rainfall was estimated by at-site frequency analysis using L-moments and Generalized extreme value(GEV) distribution according to change of the number of years for observed data. Through the comparative analysis for design rainfall induced by L-moments and GEV distribution, relationship between design rainfall and recorded year is provided.

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A Selection of the Point Rainfall Process Model Considered on Temporal Clustering Characteristics (시간적 군집특성을 고려한 강우모의모형의 선정)

  • Kim, Kee-Wook;Yoo, Chul-Sang
    • Journal of Korea Water Resources Association
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    • v.41 no.7
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    • pp.747-759
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    • 2008
  • This study, a point rainfall process model, which could represent appropriately observed rainfall data, was to select. The point process models-rectangular pulses Poisson process model(RPPM), Neyman-Scott rectangular pulses Poisson process model(NS-RPPM), and modified Neyman-Scott rectangular pulses Poisson process model(modified NS-RPPM)-all based on Poisson process were considered as possible rainfall models, whose statistical analyses were performed with their simulation rainfall data. As results, simulated rainfall data using the NS-RPPM and the modified NS-RPPM represent appropriately statistics of observed data for several aggregation levels. Also, simulated rainfall data using the modified NS-RPPM shows similar characteristics of rainfall occurrence to the observed rainfall data. Especially, the modified NS-RPPM reproduces high-intensity rainfall events that contribute largely to occurrence of natural harzard such as flood and landslides most similarly. Also, the modified NS-RPPM shows the best results with respect to the total rainfall amount, duration, and inter-event time. In conclusions, the modified NS-RPPM was found to be the most appropriate model for the long-term simulation of rainfall.

Comparison of Cloud Top Height Observed by a Ka-band Cloud Radar and COMS (Ka-band 구름레이더와 천리안위성으로 관측된 운정고도 비교)

  • Oh, Su-Bin;Won, Hye Young;Ha, Jong-Chul;Chung, Kwan-Young
    • Atmosphere
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    • v.24 no.1
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    • pp.39-48
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    • 2014
  • This study provides a comparative analysis of cloud top heights observed by a Ka-band cloud radar and the Communication, Ocean and Meteorological Satellite (COMS) at Boseong National Center for Intensive Observation of severe weather (NCIO) from May 25, 2013 (1600 UTC) to May 27. The rainfall duration is defined as the period of rainfall from start to finish, and the no rainfall duration is defined as the period other than the rainfall duration. As a result of the comparative analysis, the cloud top heights observed by the cloud radar have been estimated to be lower than that observed by the COMS for the rainfall duration due to the signal attenuation caused by raindrops. The stronger rainfall intensity gets, the more the difference grows. On the other hand, the cloud top heights observed by the cloud radar have been relatively similar to that observed by the COMS for the no rainfall duration. In this case, the cloud radar can effectively detect cloud top heights within the range of its observation. The COMS indicates the cloud top heights lower than the actual ones due to the upper thin clouds under the influence of ground surface temperature. As a result, the cloud radar can be useful in detecting cloud top heights when there are no precipitation events. The COMS data can be used to correct the cloud top heights when the radar gets beyond the valid range of observation or there are precipitation events.

Comparison Study of Rainfall Data Using RDAPS Model and Observed Rainfall Data (RDAPS 모델의 강수량과 실측강수량의 비교를 통한 적용성 검토)

  • Jeong, Chang-Sam;Shin, Ju-Young;Jung, Young-Hun;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.44 no.3
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    • pp.221-230
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    • 2011
  • The climate change has been observed in Korea as well as in the entire world recently. The rainstorm has been gradually increased and then the damage has been grown. It is getting important to predict short-term rainfall. The Korea Meteorological Administration (KMA) generates numerical model outputs which are computed by Global Data Assimilation and Prediction System (GDAPS) and Regional Data Assimilation and Prediction System (RDAPS). The KMA predicts rainfall using RDAPS results. RDAPS model generates 48 hours data which is organized 3 hours data accumulated at 00UTC and 12UTC. RDAPS results which are organized 3 hours time scale are converted into daily rainfall to compare observed daily rainfall. In this study, 9 cases are applied to convert RDAPS results to daily rainfall data. The MAP (mean areal precipitation) in Geum river basin are computed by using KMA which are 2005 are used. Finally, the best case which gives the close value to the observed rainfall data is obtained using the average absolute relative error (AARE) especially for the Geum River basin.