• Environmental Engineering Research
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• v.15 no.4
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• pp.191-195
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• 2010

This study was carried out to investigate the important factors relating to runoff and pollutant loads in a plot unit located in an agricultural area. Of the precipitation parameters, such as total precipitation, days since last rainfall (ADD, the rainfall was more than 10mm) and average rainfall intensity on runoff, the strongest effect was obtained due to total precipitation, but the rainfall intensity showed a slightly positive correlation. It was expected that both variables, i.e. total precipitation and rainfall intensity, would lead to the generation of greater runoff. In contrast, runoff was negatively correlated with ADD, which is understandable because more infiltration and less runoff would be expected after a long dry period. The TSS load varied greatly, between 75.6 and $5.18{\times}10^4g$, per event. With the exception of TN, the TSS, BOD, COD and TP loads were affected by runoff. The correlations of these items were proportional to the runoff volume, with correlation coefficients (r) greater than 0.70, which are suitable for use as NPS model data. The TSS load showed very good relationships with organics (BOD & COD) and nutrients (TN & TP), with correlation coefficients greater than 0.79. Therefore, the removal of TSS is a promising factor for protecting water basins.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.3
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• pp.373-381
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• 2006

The catalytic combustion of toluene was investigated on the Cu-Mn oxide catalysts prepared by the deposition-precipitation method. Experiment of toluene combustion was performed with a fixed bed flow reactor in the temperature range of $100{\sim}280^{\circ}C$. Among the catalysts, 1.29Cu/Mn showed the most activity at $260^{\circ}C$. The deposition-precipitation method may be showed the potential to enhance the activity of catalysts. The catalysts were characterized by BET, scanning electron microscopy (SEM), temperature-programmed reduction (TPR), X-ray photoelectron spectroscopy (XPS) and X-ray diffraction (XRD) techniques. On the basis of catalyst characterization data, the results showed that the surface of catalysts by deposition-precipitation method had uniform distribution and smaller particle size, which enhanced the reduction capability of catalysts. The XRD results showed that $Cu_{1.5}Mn_{1.5}O_{4}$ spinel phase was made by deposition-precipitation method, and increased catalyst activity and redox characteristic. It was assumed that the reduction step of $Cu_{1.5}Mn_{1.5}O_{4}$ spinel phase progressed $Cu_{1.5}Mn_{1.5}O_{4}\;to\;CuMnO_{2},\;and\;Cu_{2}O\;to\;CuMn_{2}O_{4}\;and\;Cu$.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.41-53
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• 2014

The special observation using Radiosonde was performed to investigate precipitation events over the east coast of Korea during the winter season from 5 January to 29 February 2012. This analysis focused on the various indices to describe the characteristics of the atmospheric instability. Equivalent Potential Temperature (EPT) from surface (1000 hPa) to middle level (near 750 hPa) was increased when the precipitation occurred and these levels (1000~750 hPa) had moisture enough to cause the instability of atmosphere. The temporal evolution of Convective Available Potential Energy (CAPE) appeared to be enhanced when the precipitation fell. Similar behavior was also observed for the temporal evolution of Storm Relative Helicity (SRH), indicating that it had a higher value during the precipitation events. To understand a detailed structure of atmospheric condition for the formation of precipitation, the surface remote sensing data and Automatic Weather System (AWS) data were analyzed. We calculated the Total Precipitable Water FLUX (TPWFLUX) using TPW and wind vector. TPWFLUX and precipitation amount showed a statistically significant relationship in the north easterly winds. The result suggested that understanding of the dynamical processes such as wind direction be important to comprehend precipitation phenomenon in the east coast of Korea.

• 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.

• Water for future
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• v.14 no.4
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• pp.53-72
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• 1981

In this study, South Korea is divided into 5 zones and is studied about the analysis of time-regional distribution of previpitation frequency and rainfall intensity in Korea. In the previpitation frequency analysis, the basic data groups of 39 stations were selected. The diagram of previpitation frequency was drawn, and the time-regional distribution of precipitation frequency was analized. In the rainfall intensity analysis, the basic data groups of 36 stations were selected. The probable rainfall, I-D-F curve, and regression equation between 24hr. and 10min.-18hr. areal depth were obtained. The results of this study are following; 1) The precipitation class of max. recurrence probability in every season except summer was commonly (1) 1-5mm, (2) 0.1-1mm, (3) 5-10mm in order. 2) The zone of max. recurrence frequency owing to the precipitation class was zone II in precipitation frequency of below 20mm, zone IV in precipitation frequency of 30-40mm, zone I in precipitation frequency of above 70mm for a year. 3) The recurrence probability of precipitation in Korea can be represented to the equation of exponential function; $$W(x)=e^{\alpha+\beta}$$ 4) The first and third zones were expected heavy rain for the short and long duration. 5) The I.D.F. curves were drawn, and established that the time interval for the least deviation of I.D.F curve is 10~40min., 40min. -4hr., 4~24hr. 6) The regression equations of areal mean depth between 24hr. and 10min.-18hr. for each zone were obtained. 7)The probable rainfall of 36 points were calculated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.128-135
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• 2015

In this study, we develop the very short-term precipitation forecasting model as well as classifier based on polynomial radial basis function neural networks by using AWS(Automatic Weather Station) and KLAPS(Korea Local Analysis and Prediction System) meteorological data. The polynomial-based radial basis function neural networks is designed to realize precipitation forecasting model as well as classifier. The structure of the proposed RBFNNs consists of three modules such as condition, conclusion, and inference phase. The input space of the condition phase is divided by using Fuzzy C-means(FCM) and the local area of the conclusion phase is represented as four types of polynomial functions. The coefficients of connection weights are estimated by weighted least square estimation(WLSE) for modeling as well as least square estimation(LSE) method for classifier. The final output of the inference phase is obtained through fuzzy inference method. The essential parameters of the proposed model and classifier such ad input variable, polynomial order type, the number of rules, and fuzzification coefficient are optimized by means of Particle Swarm Optimization(PSO) and Differential Evolution(DE). The performance of the proposed precipitation forecasting system is evaluated by using KLAPS meteorological data.

• Journal of Korea Water Resources Association
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• v.49 no.3
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• pp.197-205
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• 2016

Recently, natural hazards have occurred frequently due to climate change. The research need for predicting variability and tendency of precipitation and temperature has been increased. However, it is difficult to determine the characteristics of precipitation and temperature within a confidence range since they change due to complex factors with choppy and too many components. If their characteristics having more than one component are decomposed, then it can be useful for determining the variation of such characteristics more accurately. In this study, Korean precipitation and temperature were decomposed and their Intrinsic Mode Function (IMF) were extracted from Empirical Mode Decomposition (EMD). Finally, the characteristics of Korean precipitation and temperature data were analyzed in terms of periodicity and tendency.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.1017-1028
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• 2009

NSRPM (Neyman-Scott Rectangular Pulse Model) is one of the common model for generating future precipitation time series in stochastical hydrology. There are 5 parameters to compose the NSRPM model for generating precipitation time series. Generally parameter estimation using moment has some problems related with increased objective functions and shows different results in accordance with random variable generating models. In this study, direct parameter estimation method was proposed to cover with disadvantages of parameter estimation using moment. To apply the direct parameter estimation, generating stochastical data variance in accordance with numbers of precipitation events of NSRPM was done. Both kinds of methods were applied at the Cheongju gauge station data. Precipitation time series were generated using 4 different random variable generator, and compared with observed time series to check the accuracies. As a results, direct method showed more stable and better results.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.310-310
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• 2018

Generally, precipitation measurement were conducted with various authrities. Among these, the MOLIT conduct the hydrological survey for the water resource management such as flood and low-flow forecasting, drought countermeasure, streamflow management. There is totally 424 observatory were existed and each precipitation measurement were obtained and quality assuranced with 10-min interval. It could be arranged or estimated with nearby observatory and radar reflectivity when the total amount of precipitation are existed. The objective of the study is therefore to suggest the method to estimate missing data with rain radar reflectivity. To validate suggested method, 50 observartory were obtained, and the efficiency were analyzed with estimated and observed precipitation. As the result of the study, the suggested method has reliability, and can be used as a method for quality assurance.

• Atmosphere
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• v.28 no.4
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• pp.443-455
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• 2018

Nowcasting algorithms using weather radar data are mostly based on extrapolating the radar echoes. We estimate the echo motion vectors that are used to extrapolate the echo properly. Therefore, understanding the general characteristics of these motion vectors is important to improve the performance of nowcasting. General characteristics of radar-based motions are analyzed for warm season precipitation over Jeju region. Three-year summer season data (June~August, 2011~2013) from two radars (GSN, SSP) in Jeju are used to obtain echo motion vectors that are retrieved by Variational Echo Tracking (VET) method which is widely used in nowcasting. The highest frequency occurs in precipitation motion toward east-northeast with the speed of $15{\sim}16m\;s^{-1}$ during the warm season. Precipitation system moves faster and eastward in June-July while it moves slower and northeastward in August. The maximum frequency of speed appears in $10{\sim}20m\;s^{-1}$ and $5{\sim}10m\;s^{-1}$ in June~July and August respectively while average speed is about $14{\sim}15m\;s^{-1}$ in June~July and $8m\;s^{-1}$ in August. In addition, the direction of precipitation motion is highly variable in time in August. The speed of motion in Lee side of the island is smaller than that of the windward side.