• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.265-276
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• 2008

The observed data of enough period need for design of hydrological works. But, most hydrological data aren't enough. Therefore in this paper, hourly precipitation generated by nonhomogeneous Markov chain model using variable Kernel density function. First, the Kernel estimator is used to estimate the transition probabilities. Second, wet hours are decided by transition probabilities and random numbers. Third, the amount of precipitation of each hours is calculated by the Kernel density function that estimated from observed data. At the results, observed precipitation data and generated precipitation data have similar statistic. Also, rainfall mass curve is derived by calculated transition probabilities for generation of hourly precipitation.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.595-604
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• 2005

Precipitation simulation for making the data size larger is an important task for hydrologic analysis. The simulation can be divided into two major categories which are the parametric and nonparametric methods. Also, precipitation simulation depends on time intervals such as daily or hourly rainfall simulations. So far, Markov model is the most favored method for daily precipitation simulation. However, most models are consist of state transition probability by using the homogeneous Markov chain model. In order to make a state vector, the small size of data brings difficulties, and also the assumption of homogeneousness among the state vector in a month causes problems. In other words, the process of daily precipitation mechanism is nonstationary. In order to overcome these problems, this paper focused on the nonparametric method by using uni-variate and multi-variate when simulating a precipitation instead of currently used parametric method.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.135-144
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• 2011

Direct parameter estimation method is verified with various models based on Neyman-Scott rectangular pulse model (NSRPM). Also, newly modified NSRPM (NMSRPM) that uses normal distribution is developed. Precipitation data observed by Korea Meteorological Administration (KMA) for 47 years is applied for parameter estimation. For model performance verification, we used statistics, wet ratio and precipitation accumulate distribution of precipitation generated. The comparison of statistics indicates that absolute relative error (ARE)s of the results from NSRPM and modified NSRPM (MNSRPM) are increasing on July, August, and September and ARE of NMNSRPM shows 10.11% that is the smallest ARE among the three models. NMNSRPM simulates the characteristics of precipitation statistics well. By comparing the wet ratio, MNSRPM shows the smallest ARE that is 16.35% and by using the graphical analysis, we found that these three models underestimate the wet ratio. The three models show about 2% of ARE of precipitation accumulate probability. Those results show that the three models simulate precipitation accumulate probability well. As the results, it is found that the parameters of NSRPM, MNSRPM and NMNSRPM are able to be estimated by the direct parameter estimation method. From the results listed above, we concluded that the direct parameter estimation is able to be applied to various models based on NSRPM. NMNSRPM shows good performance compared with developed model-NSRPM and MNSRPM and the models based on NSRPM can be developed by the direct parameter estimation method.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.1
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• pp.27-35
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• 2017

This research was to elucidate the generation method of daily precipitation data from monthly data. We applied a combined method of Markov chain and gamma distribution function using 4 specific parameters of ${\alpha}$, ${\beta}$, p(W/W) and p(W/D) for generation of daily rainfall data using daily precipitation data for the past 30 years which were collected from the country's 23 meteorological offices. Four parameters, applied to use for the combination method, were calculated by maximum likelihood method in location of 23 sites. There are high correlations of 0.99, 0.98 and 0.98 in rainfall days, rainfall probability and mean amount of daily rainfall between measured and simulated data in case of those parameters. In case of using parameters estimated from monthly precipitation, correlation coefficients in rainfall days, rainfall probability and mean amount of daily rainfall are 0.84, 0.83 and 0.96, respectively. We concluded that a combination method with parameter estimation from monthly precipitation data can be applied, in practical purpose such as assessment of climate change in agriculture and water resources, to get daily precipitation data in Korea.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.1 no.1
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• pp.74-82
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• 2020

Predictions of suitable habitat areas can provide important information pertaining to the risk assessment and management of alien plants at early stage of their establishment. Here, we predict the invasion potential of Muhlenbergia capillaris (pink muhly) in South Korea using five bioclimatic variables. We adopt four models (generalized linear model, generalized additive model, random forest (RF), and artificial neural network) for projection based on 630 presence and 600 pseudo-absence data points. The RF model yielded the highest performance. The presence probability of M. capillaris was highest within an annual temperature range of 12 to 24℃ and with precipitation from 800 to 1,300 mm. The occurrence of M. capillaris was positively associated with the precipitation of the driest quarter. The projection map showed that suitable areas for M. capillaris are mainly concentrated in the southern coastal regions of South Korea, where temperatures and precipitation are higher than in other regions, especially in the winter season. We can conclude that M. capillaris is not considered to be invasive based on a habitat suitability map. However, there is a possibility that rising temperatures and increasing precipitation levels in winter can accelerate the expansion of this plant on the Korean Peninsula.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.537-537
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• 2015

In recent decades, the independence and identical distribution (iid) assumption for extreme events has been shown to be invalid in many cases because long-term climate variability resulting from phenomena such as the Pacific decadal variability and El Nino-Southern Oscillation may induce varying meteorological systems such as persistent wet years and dry years. Therefore, in the current study we propose a new parameter estimation method for probability distribution models to more accurately predict the magnitude of future extreme events when the iid assumption of probability distributions for large-scale climate variability is not adequate. The proposed parameter estimation is based on a metaheuristic approach and is derived from the objective function of the rth power probability-weighted sum of observations in increasing order. The combination of two distributions, gamma and generalized extreme value (GEV), was fitted to the GEV distribution in a simulation study. In addition, a case study examining the annual hourly maximum precipitation of all stations in South Korea was performed to evaluate the performance of the proposed approach. The results of the simulation study and case study indicate that the proposed metaheuristic parameter estimation method is an effective alternative for accurately selecting the rth power when the iid assumption of extreme hydrometeorological events is not valid for large-scale climate variability. The maximum likelihood estimate is more accurate with a low mixing probability, and the probability-weighted moment method is a moderately effective option.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1762-1766
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• 2006

In order to protect properties and human lives from disasters such as heavy rainfall, rational Probability Maximum Flood(PMF) estimation procedures for existing dam basins are recently required. This study analyzes the Probable Maximum Flood(PMF) as a part of a counterplan for disaster preventions of hydraulic structures such as dams, according to recent unfavorable weather conditions. In this study, an improvement method of parameter estimation was proposed, being estimated as an appropriate method for application to the unit hydrograph, the time of concentration and storage constant corresponding to the discharge of flood were considered differently when estimating PMF in Hoengseong dam basin.

• Journal of the Korean association of regional geographers
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• v.1 no.1
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• pp.45-60
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• 1995

The purpose of this study is to classify the Korean precipitation regions on the basis of the characteristics of extratropical cyclonic precipitation. From now on, extratropical cyclone is called cyclone in short. By using factor analysis and Ward method in cluster analysis, precipitation regions on the basis of the characteristics of cyclonic precipitation are classified The principal data used in this study are daily precipitation records obtained from 60 weather stations of the Korea Meteorological Service during the ten years($1981{\sim}1990$), and weather charts published by the Japan Meteorological Agency. The results obtained in this study are summarized as follows: (1) In the factor analysis using 43 variables which have relation to the extratropical cyclonic precipitations, They are seven factors whose eigenvalues are above 1.0. This explains 86 percent of total amount. The first factor explains the characteristics of precipitation in the middle-west area and its contribution degree has the highest 10.9 percent. (2) According to the cluster analysis method of Ward, extratropical cyclonic precipitation regions are classified seven macro regions(such as Kyungki and North Youngseo, Youngdong and Ullungdo, Hoseo and South Youngseo, Honam and Northwest Chejudo, Southeast Chejudo, North Youngnam, and South Youngnam), 22 meso regions. (3) The characteristics of precipitation regions have relations to the path of cyclone, the direction of air inflow and the strike of mountain ranges. As the conclusion, the Central China Low brings much precipitation in the southern coast and southern area of Korea as moving to the northeastward. The North China Low moves eastward and brings much precipitation in the western area of the Taeback mountain ranges. The probability of extratropical cyclonic precipitation is the lowest in the inland of Yeongnam and the eastern coastal areas which belong to the rain shadow region. Namely, The seasonal and spatial characteristics of precipitation are closely associated with the path of cyclone and the direction of air inflow according to its passage, and the strike of mountain ranges.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.709-722
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• 2007

The floods of Korea happens periodically during summer. The cause of heavy rain that provokes floods can be classified into typhoon and localized downpour. The typhoon happens in the tropical region. It causes one of the worst damage to Korea by extreme rainfall and strong wind. Usually, it is known that the flood damage by the typhoon is larger than that by the localized downpour. Therefore, this study classified rainfall events into typhoon events and localized downpour events based on the cause. Through statistical analyses of the rainfall data, this study investigated special quality of the rainfall during the time of typhoon. In analysis results, probability Precipitation calculated by the typhoon events were exposed bigger than that calculated by all rainfall events.

• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.11-18
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• 2016

It is very important to decide probability precipitation that is used as hydraulic structure design and target rainfall for urban disaster prevention. Especially, National Emergency Management Agency (NAMA) announced target rainfall from probability precipitation in korea on city and district level. It make use to performance evaluation of disaster prevention and planning of development for disasters prevention capacity target. In this study was calculated target rainfall that is duration 1~3 hour based unit of gu (borough) by point and regional frequency analysis using rainfall data of Surface Synoptic Stations (SSS) and Automatic Weather Stations (AWS). The result of this study can utilized as a reference to related business such as disaster capability assessment and achievement of prevention capacity target against disasters. And it also will be contribute to establishment of prevention capacity target against disasters.