• 대기
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• 제23권2호
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• pp.187-204
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• 2013

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.

• 생태와환경
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• 제53권1호
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• pp.91-101
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• 2020

본 연구에서는 특별관리해역인 시화호 유역의 산업단지 하천에 강우 시 비점오염의 형태로 유입되는 중금속의 유출 특성 파악 및 오염원 파악을 하천 토구를 통해 배출되는 강우유출수 내 용존 및 입자성 중금속(Cr, Co, Ni, Cu, Zn, As, Cd, Pb)을 조사하였다. 용존성 Co와 Ni은 강우 초반에 고농도로 유출된 후 시간에 따라 감소하는 결과를 보였으나, 대부분의 원소는 조사시기별 강우량 및 유량 변화에 따라 각각 다른 특징을 보였다. 입자성 중금속의 경우, 시간에 따른 부유물질의 농도 변화와 유사한 경향을 보였다. 강우유출수 내 존재하는 중금속 중 Co, Ni, Zn는 용존 상태로 유출되는 비율이 높았고, Cr, Cu, Pb은 입자상 유출 비율이 상대적으로 높았다. 입자 상태로 유출되는 중금속의 인위적 오염도를 평가하기 위해 농집지수를 계산한 결과, Cu, Zn, Cd은 very highly polluted에 해당하는 심각한 오염수준으로 나타났다. 연구지역인 3간선수로 유역 인근의 도로먼지 중 125 ㎛ 이하에서의 중금속 농도와 비교한 결과, 강우유출수 내 Cu, Zn, Cd의 중금속이 금속제조관련 시설에서 절삭 혹은 가공 중에 발생하여 산업시설 표면에 축적되어 있는 금속물질이 강우유출수와 함께 수환경으로 유출된 것을 알 수 있었다. 강우유출수 내 총중금속 평균 유출부하량은 1회 강우 시 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 g으로 금속제조와 관련된 산업시설이 주로 존재하는 유역의 특성을 잘 반영한 것으로 판단된다.

• 한국초지조사료학회지
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• 제36권3호
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• pp.205-214
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• 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.

• 한국토양비료학회지
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• 제49권5호
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• pp.420-428
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• 2016

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.

• 한국습지학회지
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• 제11권2호
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• pp.67-76
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• 2009

비점오염원에 의한 4대강의 오염부하율은 2004년 기준으로 22~37 %로 나타났으며, 2020년에는 60 % 이상으로 증가할 것으로 예상되고 있다. 이는 토지이용의 고도화에 따른 비점오염물질의 유출이 증가하기 때문이며, 지속적인 점오염원 관리와 더불어 비점오염원 관리가 이루어지지 않을 시에는 하천의 수질개선을 기대할 수 없다. 따라서 환경부는 수질오염총량관리제를 도입하여 수생태계의 입장에서 수질개선 정책을 펼치고 있으며, 비점오염원 관리에 관심을 쏟고 있다. 이러한 비점오염원은 강우시 발생되어 유역의 특성 및 다양한 강우인자들의 영향을 받아 불확실성이 매우 크기에 오염물질별 EMC 및 부하량 산정이 매우 어렵다. 따라서 본 연구는 모니터링 지점으로 국도와 주차장을 선정하여 최근 3년 동안 모니터링을 수행하였으며, 오염물질별 EMC산정과 함께 모니터링 지점에 대한 강우특성을 파악하였다. 또한 산정된 EMC를 강우계급별로 나누어 EMC를 재 산정하였다. 그 결과, TSS의 평균 EMC는 강우계급이 높아질수록 감소하는 경향을 나타내었으며, 대부분 10 mm 이하의 강우에서 유출되는 것으로 나타났다. 이러한 결과는 국내의 강우특성이 반영된 EMC를 산정하여 제시함으로써 비점오염저감시설의 효율적 규모 산정에 활용될 수 있을 것으로 기대된다.

• 전기학회논문지
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• 제63권4호
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• pp.526-533
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• 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.

• 한국농공학회논문집
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• 제54권6호
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• pp.89-99
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• 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.

• 한국토양비료학회지
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• 제41권5호
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• pp.310-317
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• 2008

포화추출액중 전기전도도는 $1.0\sim28.4dS\;m^{-1}$의 범위로 평균 $4.8dS\;m^{-1}$를 나타내어 매우 높은 농도로 염류가 집적되고 있었다. 전기전도도 $4dS\;m^{-1}$ (포화추출액 조건으로 환산)를 초과한 경우가 전체의 55%를 차지하고 있었다. 복분자 비가림하우스 재배토양 중 전기전도도와 각각의 무기이온과의 단순상관관계를 조사한 결과, 전기전도도와 염소 ($r=0.85^{**}$), 질산 ($r=0.94^{**}$), 인산 ($r=0.88^{**}$), 황산 ($r=0.84^{**}$) 이온과 같은 음이온과 고도의 유의성 있는 정(+)의 상관관계를 나타내었고, 마그네슘 ($r=0.41^*$), 칼슘 ($r=0.38^*$), 칼리 ($r=0.47^*$) 이온과 같은 양이온과는 유의성 있는 정(+)의 상관관계를 나타내었다. 비가림 하우스형 복분자 재배토양 중에 함유되어 있는 염류집적 유발물질을 제거하는데 있어 작업의 편이성, 농업용수의 절감 및 처리시간 등을 고려하였을 때 용탈법보다 수세법이 더 효과적인 것으로 나타났다.

• 한국습지학회지
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• 제7권3호
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• pp.75-85
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• 2005

산업단지 조성은 포장율의 증가를 의미하며, 다량의 비점오염물질이 강우시 유출되게 된다. 이러한 비점오염물질의 처리 및 저감을 위해서는 저류지 건설 등이 대안이 될 수 있기에 최근 환경부는 홍수조절용 우수저류조를 비점오염물질 처리용 저류조로의 전환을 꾀하고 있다. 2005년도에 비점오염원 관리 방안이 법제화됨으로써, 향후 신규개발 지역에서는 비점오염물질 관리를 위한 최적관리방안이 필수화 될 것이다. 본 연구지역의 토지이용은 산업단지 조성지역으로 제 1차 제조업 및 금속산업, 섬유 및 화학제품 제조업 등의 업종이 주를 이루고 있다. 산업단지 조성은 인근 수계에 심각한 비점오염물질 부하량을 증가시킨다. 따라서 본 연구는 산업단지에서의 비점오염물질 처리 및 저감을 위하여 저류지 또는 습지 조성을 위하여 추진되었으며, 비점오염물질 관리를 위한 적정 저류지 용량 산정은 강우량 해석, 유출량 해석 및 비점오염물질 유출해석 등을 통하여 적정 용량을 산정할 수 있다. 연구지역의 일 평년, 최근 10년간, 최근 2년간 및 5년간의 강우량 자료를 통계 분석한 결과 초기 강우현상을 고려하지 않을 경우 발생빈도 80% 이상의 강우에 대한 적정 강우량은 10mm로 나타났다. 초기강우 현상을 고려하여 산정한 누적강우량 기준은 4-5mm 사이로 산정되었으며, 연구지역에서의 적정 저류지 용량은 안전율을 고려하여 $12,000m^3$으로 결정되었다. 연구지역에서 연간 유출되는 비점오염물질의 양은 TSS가 435ton/yr, COD가 238ton/yr, TKN이 8,518kg/yr 그리고 TP가 1,816kg/yr로 나타났다. 저류지에서의 비점오염물질 저감량은 TSS가 78.3ton/yr, BOD가 20.4ton/yr, COD가 128.6ton/yr, TKN이 4.6ton/yr 그리고 TP가 980kg/yr의 저감량을 보였다. 저류지의 연간 퇴적물량은 78.3ton/yr로 나타났으며, 연간 퇴적율은 $6.53kg/m^2-hr$로 산정되었다.

• 한국철도학회논문집
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• 제8권4호
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• pp.308-313
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• 2005

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.