• Journal of Environmental Science International
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• v.23 no.4
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• pp.595-603
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• 2014

Jeju Island, a volcanic island, is the region that shows the biggest rainfall and has a big elevation-specific deviation of precipitation, but Jeju Island River Maintenance Plan doesn't reflect the characteristics of Jeju Island as it only calculates probable precipitation from four weather stations with elevation less than 100m. Therefore, this study uses AWS observational data in four Jeju Island weather stations and other regions to calculate location-specific probable precipitation, review the elevation-probable precipitation correlation in southern and northern regions, and create a probable precipitation map for all regions of Jeju Island, in order to produce better outcomes. This study is expected to be the most basic data to establish a safe Jeju island from flood disaster in preparation for the future climate changes and widely used for Jejudo Basin Dimension Planning, River Maintenance Plan, Pre-Disaster Impact Review, etc.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.29-39
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• 2014

In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu, Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annual maximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of non-stationary analyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed very large increase in the long term projection, while the logistic regression resulted in similar amounts for different target years because the logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showed reasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.141-153
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• 2012

In this study, we estimated probable precipitation amounts at the target year (2020, 2030, 2040) of 55 weather stations in Korea using the 24 hour annual maximum precipitation data from 1973 through 2009 which should be useful for management of agricultural reservoirs. Not only trend tests but also non-stationary tests were performed and non-stationary frequency analysis were conducted to all of 55 sites. Gumbel distribution was chosen and probability weighted moment method was used to estimate model parameters. The behavior of the mean of extreme precipitation data, scale parameter, and location parameter were analyzed. The probable precipitation amount at the target year was estimated by a non-stationary frequency analysis using the linear regression analysis for the mean of extreme precipitation data, scale parameter, and location parameter. Overall results demonstrated that the probable precipitation amounts using the non-stationary frequency analysis were overestimated. There were large increase of the probable precipitation amounts of middle part of Korea and decrease at several sites in Southern part. The non-stationary frequency analysis using a linear model should be applicable to relatively short projection periods.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.241-248
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• 2001

Normally at a flood season the operation of the dam depends on a short range weather forecast that makes many difficulties of the management at a dry season. It is needed to study the pattern of the long period rainfall. The concept of PMP(Probable Maximum Precipitation) was used for designing dam. From the concept, this study is applied the concept of monthly probable maximum precipitation for operating dam. It can be possible to let us know the appropriateness of a limiting water level at a rainy season. For the operation of dam at a dry season this study can predict roughly the flood season's pattern of precipitation by month or period, therfore the prediction of precipitation can rise efficient operation of a dam.

• Atmosphere
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• v.16 no.2
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• pp.55-65
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• 2006

The characteristics of Depth-Area-Duration (DAD) for 50 storms over the Geumgang river basin have been analysed in terms of various storm causes using the precipitation data during the period from 1984 to 2003. Results show that the ratio of the precipitation depth to duration, and the ratio of decrease in the precipitation depth to area are the largest in the case of the tropical cyclone. Storm maximization ratios are in the range 1.03 to 2.66 for the 50 selected heavy precipitation cases over Geumgang river basin, with the largest value for the tropical cyclone case, suggesting that the tropical cyclone could cause heavier precipitation than the other storms. In addition, the 24-hour probable maximum precipitation for the Geumgang river basin is estimated to be about 745 mm in the maximum precipitation area.

• Magazine of the Korean Society of Agricultural Engineers
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• v.23 no.2
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• pp.45-53
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• 1981

Long term precipitation gaging station record (58 years) was analyzed by progressive mean method to compare the estimated effective period of records for computing mean and probable values. Obtained results are as follows: 1. Fifty-eight years precipitation records at Jinju, Gyeong Sang Nam Do was analyzed by double mass analysis method. Result was appeared that the record was consistent with time. 2. The effective period of records for estimating mean values with the departure of 5% or less from the true mean are up to 33 years for annual precipitation, 20 years for annual maximum daily precipitation and 45 years for maximum successive dry days in summer season. 3. To estimate the probable values by Gumbel-Chow method within the departure of 5% level from true value, periods of 51 years, 38 years and 45 years were required for annual precipitation, annual maximum daily precipitation and maximum successive dry days in summer season, respectively.

• Journal of the Korean earth science society
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• v.33 no.1
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• pp.39-48
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• 2012

In this study, a statistical estimation of probable precipitation and an analysis of its return period in Busan were performed using long-term precipitation data (1973-2007) collected from the Busan Regional Meteorological Administration. These analyses were based on the method of probability weighted moments for parameter estimation, the goodness-of-fit test of chi-square ($x^2$) and the probability plot correlation coefficient (PPCC), and the generalized logistics (GLO) for optimum probability distribution. Moreover, the spatial distributions with the determination of probable precipitation were also investigated using precipitation data observed at 15 Automatic Weather Stations (AWS) in the target area. The return periods for the probable precipitation of 245.2 and 280.6 mm/6 hr with GLO distributions in Busan were estimated to be about 100 and 200 years, respectively. In addition, the high probable precipitation for 1-, 3-, 6-, and 12-hour durations was mostly distributed around Dongrae-gu site, all coastal sites in Busan, Busanjin and Yangsan sites, and the southeastern coastal and Ungsang sites, respectively.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.804-806
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• 2003

Probable Maximum Precipitation (PMP) is essential in the design of hydraulic structures such as dams, weirs and flood control structures. Up to the present, PMP has been derived from any proper single storm which can have a large error. PMP values should be evaluated from many historic heavy storm events from all over the country. Since this can be done at the spots of storm occurring and the calculated PMP from all spots in the country can be correlated. The objectives of this study are therefore to evaluate PMP from historic heavy storm data from 1972 to 2000 by using meteorological method, then to correlate and to present the results using GIS. The maximized rainfall depths can be calculate from depth of heavy rainfall and dew point temperature, and then can be analyzed for each rainfall duration to obtain spatial rainfall distribution by using GIS. The depth-area-duration relationship of maximized rainfall can be obtained and this helps to develop enveloped curves . The results from this study are a set of contour maps of PMP for each rainfall duration for all over the country and the depth-area-duration relationships for the area of 100 to 50,000 km.$^{2}$ at duration of 1, 2 and 3 days.

• Water for future
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• v.13 no.3
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• pp.77-81
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• 1980

Probable Maximum Precipitation values for seven heavy stroms during the period from 1966 to 1976 are derived, using the manual for W.M.O P.M.P analysis of strom precipitation. The hydrometeoroogical and the statistical methods are consisted of the procedure of P.M.P. estimation in this study. It is possible to draw P.M.P curves from the view points of area and strom durations. A comparison has been made between the P.M.P values of Nakding River basin and the results of this paper. For a storm period of 24 hours, the P.M.P value at the maximum station is 762 mm and the moistrue maximization ratio are within the range 1.17 to 1.41 for the seven selected stroms.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.235-235
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• 2016

댐이나 홍수방지시설과 같은 대규모 수공구조물의 설계 및 평가에는 주로 가능최대강수량(Probable Maximum Precipitation, PMP)가 적용되고 있다. 이러한 PMP의 산정은 관측자료의 정상성 가정을 기반으로 하기 때문에 기후변화와 같은 비정상성을 고려할 수 없다. 본 논문에서는 이러한 문제를 극복하기 위해 대기 프로세스의 비정상성 효과를 반영할 수 있는 물리적 기반의 수치 기상 모형(Numerical Weather Model)을 이용하여 최대강수량(Maximum Precipitation, MP)을 산정하는 접근법을 제시하고자 한다. 사례 연구로 대상 극한 강우사상을 식별하고, 식별된 사상들은 지역 대기 모형 중 하나인 WRF를 이용하여 재현된다. 이때, 한국 내의 약 650개의 AWS 자료와 NCEP에서 제공하는 전세계 기상관측자료 및 해수면 온도 자료를 사용하여 초기조건과 경계조건을 개선하고, 총 강수량과 강우의 공간적인 분포를 재현하기 위한 최적 물리옵션을 찾기 위해 다양한 수치실험이 수행된다. 최종적으로 재현된 극한 강우사상은 모형의 경계조건과 수분 최대화의 통해 최대화되어 물리적으로 가능한 최대 강수량을 산정하게 된다. 본 연구는 제한된 강우사상을 대상으로 최대 강수량을 산정하였기 때문에 추후 다양한 강우사상에 대한 연구와 강우의 최대화에 대한 보완이 필요하지만, 정상성 가정에 의존하지 않는 극한 강우사상 산정에 잠재적인 대안이 될 것이라 기대된다.