This study analyzed the synoptic distribution and vertical structure about four cases of precipitation occurrences using NCEP/NCAR reanalysis data and upper level data of winter intensive observation to be performed by National Institute of Meteorological Research at Bukgangneung, Incheon, Boseong during 63days from 4 JAN to 6 MAR in 2012, and Observing System Experiment (OSE) using 3DVAR-WRF system was conducted to examine the precipitation predictability of upper level data at western and southern coastal regions. The synoptic characteristics of selected precipitation occurrences were investigated as causes for 1) rainfall events with effect of moisture convergence owing to low pressure passing through south sea on 19 JAN, 2) snowfall events due to moisture inflowing from yellow sea with propagation of Siberian high pressure after low pressure passage over middle northern region on 31 JAN, 3) rainfall event with effect of weak pressure trough in west low and east high pressure system on 25 FEB, 4) rainfall event due to moisture inflow according to low pressures over Bohai bay and south eastern sea on 5 MAR. However, it is identified that vertical structure of atmosphere had different characteristics with heavy rainfall system in summer. Firstly, depth of convection was narrow due to absence of moisture convergence and strong ascending air current in middle layer. Secondly, warm air advection by veering wind with height only existed in low layer. Thirdly, unstable layer was limited in the narrow depth due to low surface temperature although it formed, and also values of instability indices were not high. Fourthly, total water vapor amounts containing into atmosphere was small due to low temperature distribution so that precipitable water vapor could be little amounts. As result of OSE conducting with upper level data of Incheon and Boseong station, 12 hours accumulated precipitation distributions of control experiment and experiments with additional upper level data were similar with ones of observation data at 610 stations. Although Equitable Threat Scores (ETS) were different according to cases and thresholds, it was verified positive influence of upper level data for precipitation predictability as resulting with high improvement rates of 33.3% in experiment with upper level data of Incheon (INC_EXP), 85.7% in experiment with upper level data of Boseong (BOS_EXP), and 142.9% in experiment with upper level data of both Incheon and Boseong (INC_BOS_EXP) about accumulated precipitation more than 5 mm / 12 hours on 31 January 2012.
Stormwater runoff is known as a major non-point water pollution source that transports heavy metals, which have accumulated in road surface, to stream and coastal area. Dissolved and particulate metals in stormwater runoffs have been investigated to understand the outflow characteristics of heavy metals during rainfall events and to identify their pollution sources. The concentration of dissolved Co and Ni decreased after the outflow with high concentrations at the beginning of the rainfall, and other metals showed different characteristics depending on the rainfall and rate of discharge. Particulate metals showed a similar trend with the temporal variation of suspended solids concentration in stormwater runoffs. The results of geo-accumulation index (Igeo) indicated that the stormwater runoffs from industrial region were very highly polluted with Cu, Zn and Cd. As a result of comparing the metal concentrations of <125 ㎛ for road dust near the study area, Cu, Zn and Cd were originated from inside of metal manufacturing facilities rather than traffic activities at road surface and these metals accumulated on the surface area of facilities were transported to the water environments during stormwater event. The average discharged amounts of heavy metals for one rainfall event were Cr 128 g, Co 12.35 g, Ni 98.5 g, Cu 607.5 g, Zn 8,429.5 g, As 6.95 g, Cd 3.7 g, Pb 251.75 g, indicating that metal runoff loads in the stormwater runoffs are closely related to surrounding industry types.
Peng, Jing Lun;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
Journal of The Korean Society of Grassland and Forage Science
/
v.36
no.3
/
pp.205-214
/
2016
The objective of this study was to construct a forage rye (FR) dry matter yield (DMY) estimation model based on climate data by locations in South Korea. The data set (n = 549) during 29 years were used. Six optimal climatic variables were selected through stepwise multiple regression analysis with DMY as the response variable. Subsequently, via general linear model, the final model including the six climatic variables and cultivated locations as dummy variables was constructed as follows: DMY = 104.166SGD + 1.454AAT + 147.863MTJ + 59.183PAT150 - 4.693SRF + 45.106SRD - 5230.001 + Location, where SGD was spring growing days, AAT was autumnal accumulated temperature, MTJ was mean temperature in January, PAT150 was period to accumulated temperature 150, SRF was spring rainfall, and SRD was spring rainfall days. The model constructed in this research could explain 24.4 % of the variations in DMY of FR. The homoscedasticity and the assumption that the mean of the residuals were equal to zero was satisfied. The goodness-of-fit of the model was proper based on most scatters of the predicted DMY values fell within the 95% confidence interval.
For more than 50 years, satellite images have been used to monitor crop growth. Currently, unmanned aerial vehicle (UAV) imagery is being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study refers to the derivation of growth estimating equation for highland Kimchi cabbage using UAV derived normalized difference vegetation index (NDVI) and agro-meteorological factors. Anbandeok area in Gangneung, Gangwon-do, Korea is one of main districts producing highland Kimchi cabbage. UAV imagery was taken in the Anbandeok ten times from early June to early September. Meanwhile, three plant growth parameters, plant height (P.H.), leaf length (L.L.) and outer leaf number (L.N.), were measured for about 40 plants (ten plants per plot) for each ground survey. Six agro-meteorological factors include average temperature; maximum temperature; minimum temperature; accumulated temperature; rainfall and irradiation during growth period. The multiple linear regression models were suggested by using stepwise regression in the extraction of independent variables. As a result, $NDVI_{UAV}$ and rainfall in the model explain 93% of the P.H. and L.L. with a root mean square error (RMSE) of 2.22, 1.90 cm. And $NDVI_{UAV}$ and accumulated temperature in the model explain 86% of the L.N. with a RMSE of 4.29. These lead to the result that the characteristics of variations in highland Kimchi cabbage growth according to $NDVI_{UAV}$ and other agro-meteorological factors were well reflected in the model.
The contribution of pollutant loadings from non-point source (NPS) to the four major rivers in Korea exceeded 22~37 % of the total loadings in 2004 and is expected to reach 60 % in 2020. Most of NPS loadings are coming from urban areas, especially from paved areas. Because of high imperviousness rate, many types of NPS pollutant are accumulating on the surface during dry periods. The accumulated pollutants are wash-off during a storm and highly degrading the water quality of receiving water bodies. For this reason, the Korean Ministry of Environment (MOE) developed the Total Maximum Daily Load (TMDL) program to protect the water quality by managing the point source and NPS loadings. NPS has high uncertainties during a storm because of the characteristics of rainfall and watershed areas. The rainfall characteristics can affect on event mean concentrations (EMCs), mass loadings, flow rate, etc. Therefore, this research was performed to determine EMCs for rainfall ranges from transportation landuses such as road and parking lot. Two sites were monitored over 45 storm events during the 2006/06 through 2008/10 storm seasons. Mean TSS EMCs decrease as rainfall ranges increase and highest at less than 10mm rainfall. The results of this study can be used to determine the efficient scale of BMP facility considering specific rainfall range.
Kim, Hyun-Myung;Oh, Sung-Kwun;Kim, Yong-Hyuk;Lee, Yong-Hee
The Transactions of The Korean Institute of Electrical Engineers
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v.63
no.4
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pp.526-533
/
2014
In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.
Journal of The Korean Society of Agricultural Engineers
/
v.54
no.6
/
pp.89-99
/
2012
An upland monitoring was conducted for about 4 years with respect to the water and quality of rainfall-runoff. The objective was to characterize of runoff and nonpoint source (NPS) pollution from a sandy field with 4.5 % in slope under balloonflower (2008-2010) and potato (2011) cultivation. Balloonflower was cultivated without any surface cover but potato was grown under plastic mulching. Runoff rate, EMCs and NPS pollution loads were estimated. The first flush effect was evaluated, and the correlation coefficient among the selected water quality indices were analyzed. Average rainfall size was higher by 2.3 mm when balloonflower was cultivated but average runoff rate was higher by 0.02 when potato was cultivated due to the plastic mulching. EMCs monitored from balloonflower field were higher than potato field except SS and TN, but all NPS pollution loads of potato field were 2.1~22.9 times greater than balloonflower field because of larger runoff volume. As a result of first flush effects, balloonflower and potato field were more influenced by increasing of accumulated rainfall and rainfall intensity rather than first flush. In the result of correlation analysis, there were no evident correlations between runoff and water quality indices. However, there were obvious correlations between SS and the other indices except TN. As a result of this study, it was thought that perennial balloonflower crop could help reduce runoff and NPS pollution loads but annual crop with plastic mulching increase them.
This study was carried out to investigate the factors of desalinization of the rainfall interception culture soils of Rubus sp. in Gochang-gun, Jeollabuk-do. Soil samples were collected from 85 different sites of the rainfall interception culture soils of Rubus sp. in Gochang-gun, Jeollabuk-do. The electrical conductivity in paste saturation of rainfall interception culture soils ranged from $1.0\sim28.4dS\;m^{-1}$ (average: $4.8dS\;m^{-1}$) and salt affected soil which EC was higher than $4dS\;m^{-1}$, covered nearly 55% of all field surveyed. Salts in rainfall interception culture soils were accumulated by increasing the cultivation period. Electrical conductivity in rainfall interception culture soils was positively correlated with water soluble anions such as chloride ion ($r=0.85^{**}$), nitrate ion ($r=0.94^{**}$), phosphate ion ($r=0.88^{**}$), and sulfate ion ($r=0.84^{**}$), respectively. As a result of desalinization experiments carried out by water management practices, the rinsing method was more effective than leaching method.
The Construction of industrial complex areas means the increase of imperviousness rate and the increase of nonpoint pollutant emissions during a rainfall. Generally the retention basin can become the alternative for removing and controling these nonpoint pollutants. Recently Ministry of Environment are trying to change the purpose of retention basins from flooding control to nonpoint pollutant control. In order to propel the stormwater management program, administration plan of stormwater management is enacted in Spring, 2005. Hereafter, in a newly developing area, the best management practices should be established to control the nonpoint pollutant. Landuses of the research area are classified to the categories of the 1st manufacturing industry, metal industry, fiber and chemical product manufacturing industry, etc. Therefore, this research was performed to understand washed-off characteristics of stormwater and to suggest the controling method of nonpoint pollutants. The optimum capacity of the retention basin can be determined by analyzing the relationships among data of rainfall, runoff, washed-off pollutants from the areas. The rainfall analysis using the data of normal year, recent 2, 5 and 10 years shows that the 80% rainfall frequency was occurred on 10mm accumulated rainfall, but which is not considered the first flush effect. However, by considering the first flush effect, the appropriate treatment capacity of rainfall can be decreased to 4-5mm accumulated rainfall. Using the criteria, the optimum capacity of retention basin is determined to $12,000m^3$ in the research area. The washed-off nonpoint pollutant loading from the areas have beeb calculated to 435ton/yr for TSS, 238ton/yr for COD, 8,518kg/yr for TKN and 1,816kg/yr for TP. The mass of 78.3ton/yr for TSS, 20.4ton/yr for BOD, 128.6ton/yr for COD, 4.6ton/yr for TKN and 980kg/yr for TP can be reduced by constructing the retention basin. The sediment accumulation rate is also calculated by $6.53kg/m^2-hr$.
In order to successfully propel the stormwater management program, administration plan of stormwater management is enacted in Spring, 2005. Hereafter, in a newly developing area such as a railway station, the best management practices should be established to control the nonpoint pollutant. Construction of a railway station means the increasing of imperviousness rate and lots of nonpoint pollutant emissions during rainfall. Therefore this research was performed to determine the pollutant EMC and to suggest the possible best management practice for treating nonpoint pollutants from a railway station. The $95\%$ confidence intervals of pollutant EMC were ranged to 69.4-115.2mg/L for TSS, 132.7-190.4mg/L for COD, 5.4-15.1ug/L for Oil & Grease, 4.9-12.4mg/L for TKN and 568.4-620.1ug/L for TP. The first flush criteria was ranged to 5-10mm accumulated rainfall using dynamic EMCs, Also laboratory reactor testing was performed. It shows that Zeolite media is useful for removing the washed-off pollutants from a railway station, especially for metal ions.
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