• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.277-280
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• 2002

An artificial neural network model was developed to analyze and forecast real time river runoff from the Naju watershed, in Korea. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$ is great than 0.99) for calibration data sets. Increasing the time horizon for validation data sets, thus making the model suitable for flood forecasting, decreases the accuracy of the model. The resulting optimal EBPN models for forecasting real time runoff consists of ten rainfall and four and ten runoff data (ANN0410 and ANN1010 models). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$ is great than 0.92).

• Journal of Astronomy and Space Sciences
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• v.27 no.3
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• pp.213-220
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• 2010

As an observation instrument of the longest record of tropospheric water vapor, radiosonde data provide upper-air pressure (geopotential height), temperature, humidity and wind. However, the data have some well-known elements related to inaccuracy. In this article, radiosonde precipitable water vapor (PWV) at Sokcho observatory was compared with global positioning system (GPS) PWV during each summertime of year 2007 and 2008 and the biases were calculated. As a result, the mean bias showed negative values regardless of the rainfall occurrence. In addition, on the basis of GPS PWV, the maximum root mean square error (RMSE) was 5.67 mm over the radiosonde PWV.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.38-41
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• 1998

Due to the increasing demand to multimedia services over wireless communication network, LMDS(Local Multipoint Distribution Service) has been proposed as an alternate approach for broadband wireless access network. But LMDS, Which uses the mmwavelength radio spectrum, has been limited for unknown microwave frequency characteristics. In this paper, we analyze the parameters related to the system design on 28GHz frequency: Propagation path loss and rainfall attenuation. Based on these analytical results, the proper cell size in Korea is determined. We also analyze the bit error rate and frame loss rate for various kinds of digital modulation schemes(QAM 4, 16, 64, 256). Finally, we apply to ㅍ service to evaluate a call blocking rate, efficiency and channel capacity.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.102-114
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• 2003

The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.6
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• pp.75-82
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• 1997

Today's wireless communication needs the super-high speed for picture transmission as well as voice. The optical communication with the very wide bandwidth is suitable for this demand. To fulfill the optical wireless communication, however, the atmospheric attenuation in rainy weather condition must be overcome. In the optical satellite up-link communication between geo-satellite and earth station, the factors of attenuation are turbulence, pointing error, scattering, and so on. The most serious factor for these is the scattering by rain. Under the weather conditiion of rain and cloud, in this paper, the atmospheic attenuation which affects the optical satellite up-link communication was considered, and the optimum idameter of the optical satellite transmitting antenna in the earth station versus elevation angles, data rates and rainfall rates was presented.

• Proceedings of the Korea Water Resources Association Conference
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• 1997.05a
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• pp.186-191
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• 1997

인공위성을 이용한 강우관측은 지상에서의 강우관측과는 달리 넒은 지역의 관측을 가능하게 하고 또한 해양에서의 강우까지도 관측할 수 있다는 장점이 있다. 그러나 이러한 강우관측도 몇가지 문제점을 포함하고 있는데 그 하나로서 관측오차 문제를 들 수 있다. 이것은 관측된 강우가 공간적으로는 연속이지만 시간적으론 불연속이기 때문에 발생하는 구조적인 문제로서 강우의 시간적-공간적 통계특성과 관측계획에 따라 각각 다르게 정량화 된다. 본 논문에서는 인공위성을 이용한 강우 관측시 발생하는 관측오차의 추정식을 소개하고 두개의 다차원 강우모형을 사용하여 적용해 보았다. 현재까지의 관측오차 추정은 강우의 2차원 통계특성만을 고려하기 때문에 모형의 매개변수들이 이 특성에 맞추어 적절히 추정된 경우, 모델에 따른 차이는 크지 않은 것으로 밝혀졌다. 앞으로 이러한 단점은 2차원 이상의 통계특성을 고려하는, 궁극적으로는 강우의 확률밀도함수를 고려할 수 있는 관측오차 추정식의 개발을 통해 개선될 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.22-22
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• 2018

본 연구에서는 수문학적 가뭄을 분석하기 위해 두가지 지수를 개발하여 소개하고자 한다. 첫번째는, 물수지식을 기반으로 산정된 Water Budget-based Drought Index(WBDI)로 강우와 증발산의 차이를 이용하여 산정한다. 두 번째는 에너지 수지식을 기반으로 산정된 Energy-based Water Deficit Index(EWDI)로 에너지 수지 기반의 증발산, 태양복사에너지와 토양수분 등을 이용하여 산정한다. 두가지 지수 모두 인공위성 영상 자료를 활용하였다. WBDI 산정을 위한 강수량 자료는 Tropical Rainfall Measuring Mission(TRMM)과 Global Precipitation Mission(GPM)를 활용하였으며, 증발산 자료는 Moderate Resolution Imaging Spectroradiometer (MODIS) 자료를 활용하였다. EWDI 산정에 필요한 입력자료는 모두 MODIS 자료를 활용하였다. 산정된 두 가뭄지수의 수문학적 가뭄 분석을 위해 자연유출지점인 6개 지점을 선정하여 유출량 자료와 비교하였다. 유출량 자료를 활용하여 Error matrix 기법을 적용하여 두 수문학적 가뭄지수의 우리나라에서의 적용성을 파악하였다.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Journal of Soil and Groundwater Environment
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• v.17 no.6
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• pp.119-128
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• 2012

The applicability and accuracy of Revised Universal Soil Loss Equation (RUSLE) model on the estimation of soil loss at impacted area of shooting range was tested to further the understanding of soil erosion at shooting ranges by using RUSLE. At a shooting range located in northern Kyunggi, the amount of soil loss was estimated by RUSLE model and compared with that estimated by Global Positioning System-Total Station survey. As results, the annual soil loss at a study site (202 m long by 79 m wide) was estimated to be 2,915 ton/ha/year by RUSLE and 3,058 ton/ha/year by GPS-TS survey, respectively. The error between two different estimations was less than 5%, however, information on site conditions should be collected more to adjust model coefficients accurately. At the study shooting range, sediments generated by rainfall was transported from the top to near the bottom of the sloping face through sheet erosion as well as rill erosion, forming a gully along the direction of the storm water flow. Coarser fractions of the sediments were redeposited in the limited area along the channel. Distribution characteristics of explosive compounds in soil before and after summer monsoon rainfall in the study area were compared with the erosion patterns. Soil sampling and analyses results showed that the dispersion of explosive compounds in surface soil was consistent with the characteristics of soil erosion and redeposition pattern of sediment movements after rainfalls.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.8 s.99
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• pp.848-854
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• 2005

The attenuation due to rain has been recognized as one of the major causes of unavailability of radio communication systems operating above about 10 GHz. To design radio links for telecommunications and to evaluate attenuation due to rainfall, it is important to have a good prediction model for rain attenuation such as a model for drop-size distribution of rainfall(DSD), a theoretical model for specific rain attenuation, and an empirical model fur effective path length through rain. In this paper, the extended generalized gamma distribution for drop-size distribution, based on the measurements in Chnugnam National University, is proposed as a new DSD model, and predicted specific attenuation characteristics using proposed DSD model and rain attenuation values in the 44 GHz satellite path using ITU-R effective path length model, are analysed. The predicted attenuation levels are also compared. It is found that an accurate prediction method for DSD is very important to reduce the prediction error in the local satellite path.