• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.105-105
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• 2020

전 세계적으로 기후변화에 따른 기온상승 및 강수량 증가, 호우일수 증가 등 이상기후로 인해 다양한 형태의 자연재해가 발생하고 있으며, 이로 인해 우리나라에서도 폭우, 풍랑, 가뭄, 대설 등으로 인한 자연재해 발생이 증가하고 있다. 특히 우리나라는 연평균 강수량 1,300mm의 대부분의 강우가 하절기인 6 ~ 9월에 태풍 및 집중호우를 동반하여 발생하기 때문에 연강수량의 60%이상이 여름철에 집중된다. 이러한 여름철에 집중된 강우로 인해 홍수 및 범람 피해가 여름철에 급증하고 있으며, 2차 피해인 산사태 및 토석류 피해 또한 급증하고 있는 추세이다. 토석류는 집중호우 시 자연산지의 취약한 사면이 붕괴되어 유출수와 함께 급경사의 계류로 붕괴된 토석이 유출되면서 토석류로 전이 및 발전하여 계류하부의 주택 및 농경지를 매몰하여 피해를 발생시킨다. 특히 토석류는 유출수와 함께 토석이 급경사의 계류를 따라 빠른 속도로 이동하고 퇴적 시작점에서 높이의 6배까지 이동하여 인명피해 등 큰 피해를 발생시키는 특성이 있다. 이러한 토석류 피해로 인한 피해와 손실을 최소화하기 위해서는 토석류 발생 시 피해 규모를 예측하여야하며, 또한 하부 구조물의 손실을 정량적으로 해석하여 방재정책의 우선순위를 수립하여야 한다. 따라서 본 논문에서는 강우로 인한 토석류 발생시 하부 구조물의 손실을 정량적으로 해석하기 위하여 토사재해 손실·손상함수를 개발하여, 함수를 탑재한 토사재해 피해액 산정모형인 DELET(DEbris flow Loss Estimation Tool) 모형을 개발하였다. DELET를 이용하여 실제 토석류 피해가 발생한 피해지역에 적용하여 토사재해 피해 구조물의 손실을 평가하였다.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.3
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• pp.178-184
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• 2014

In this study, monitoring method which is more economic and easier in maintenance comparing to existing monitoring system was scrutinized for application to sewer intercepting chamber of 10.2 ha basin area by estimating CSOs (Combined Sewer Overflows) quantity and quality with 2 rainfall events using electrical conductivity data and civil research model. The result showed that determination coefficient of flow estimation by EC (Electrical Conductivity) dilution ratio and observed data was over 0.86 for all cases and the accuracy of estimation was improved from 0.5 to 0.8 for determination coefficient ($R^2$) and from 54.1% to 68.5% for accumulation frequency of relative error by considering antecedent dry days and rainfall duration. CSOs water quality estimation results by civil research model showed that determination coefficients were 0.64~0.97 for BOD and 0.70~0.95 for SS.

• The Journal of Engineering Geology
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• v.20 no.4
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• pp.401-407
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• 2010

This study was carried out to produce the characteristics of pollutant loads caused by a cherry tree plot as a nonpoint sources(NPS) unit in agricultural areas. The relationship between rainfall and runoff didn't show a good coefficient with 0.5. Despite precipitation amount was less than 20 mm, runoff occurred with $0.5\;m^3$ because of high rainfall intensity of 8.8 mm/hr. In contrast, runoff was not occurred when precipitation amount was 47.4 mm in one case. In that case the primal effect on runoff was not precipitation amount. Correlation between load of pollutants such as BOD, COD, TN and TP and runoff' volumes showed significantly positive values which were more than r = 0.92 for all pollutants except SS(r = 0.71). SS could be a proper factor for estimating pollutant loads of BOD, COD, TN and TP because of a high correlation more than r = 0.73 between SS load and pollutant loads of BOD, COD, TN and TP. Both Organics and nutrient pollutants could be reduced if we control SS in runoff. The highest concentration of TN was detected in the event which was affected by fertilization activities directly. Therefore fertilization must be considered as a function of impact parameters on TN load in agricultural areas.

• Current Research on Agriculture and Life Sciences
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• v.5
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• pp.106-111
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• 1987

The susceptibility of 8 chrysanthemum varieties to Apelenchoides ritzemabosi, Shuhonothikara and Sagakiku were resistant by 11.7% and 14.5% each infested leaf, Sinrokusiogio, Dangonanako and Sintoa were susceptible as above 50%, Gold wave and Tenju were modertae by 24 to 26%. Percentage of infested leaf was positively correlated with the number of epidermal hair but not with leaf area, leaf thickness, stomatal size, number of stomata and length of epidermal hair. In effect of watering method, Polyethylene film cover plot was lowest by 9.4%, next conventional watering plot by 50%, Conventional watering and spray plot was the highest by 62%. The infested leaf rate was closely related with a number of rainy days than the amount of rainfall. Effect of chemical soil treatment, Temik showed the lowest infested leaf rate by 5%. There was no significant difference between the chemicals except Temik, but these are markedly effective in compare to control.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.5
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• pp.751-757
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• 2011

The monitoring technique based on electrical conductivity (EC) can provide researchers with some advantages in maintenance management and is cost-effective as compared with existing CSOs monitoring. In this study, the flow rate estimation using EC data was executed in two sites where storm overflow chamber had installed. In the result of A-site, R2 of second order multinomial between dilution ratio of EC and observed flow rate was showed the range of 0.68 ~ 0.77. And $R^{2}$ of B-site was 0.62 ~ 0.81. On the other hand, cumulative frequency of A-site was 43.4 ~ 52.2% in the relative error level of under 20%. And B-site was 10.1 ~ 46.5%. The flow rate estimation formula was improved through consideration of some parameters including antecedent dry days and rainfall duration. And difference between estimated flow rate and observed flow rate in total rainfall event was very small.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1610-1614
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• 2010

최근 기후변화로 인한 우리나라 호우일수(80mm이상/일)의 증가, 강우강도의 증가에 따른 개별 홍수에 의한 재해규모가 증가하고 있는 현실에서 전통적인 빈도해석기법을 이용한 설계 강우량 산정과 적용에는 한계가 있다. 그러나 우리나라에서는 아직도 비정상성을 고려한 빈도해석기법이 표준화되어 있지 않고 있으며, 전통적인 빈도해석기법에 의존하여 실무에 활용되고 있는 실정이다. 따라서 본 연구에서는 기후변화에 따른 우리나라 강수 극치사상의 변동특성을 분석하고자 하였다. 연구 대상지역으로 기상청에서 운영하는 기상관측소 중에서 90년 이상의 장기 강수자료가 구축되어 있는 서울, 부산, 인천, 대구, 강릉, 목포 등 여섯 곳을 선정하였다. 선정된 6개 기상관측소의 강수자료를 이용하여, 비모수적 선형추세분석기법인 Mann-Kendall 검정을 수행하였다. 본 연구를 통하여 얻어진 결과는 우리나라의 전통적인 설계 강우량 산정기법 개선에 대한 필요성 인식과 설계 강우량 산정에 대한 새로운 접근방향 제시와 이에 따른 제도적 개선 요구에 대한 기초자료로 활용될 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.231-231
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• 2012

격자 기반의 분포형 모형은 격자로 분할된 유역의 임의 지점에 대해서 유출량을 계산할 수 있는 장점이 있다. 분포형 모형을 이용한 기존의 유출해석에서는 유역의 최하류 지점을 대상으로 모형을 보정하는 단일지점 모형보정 기술이 적용되어 왔다. 단일지점을 대상으로 모형을 보정할 경우, 보정 대상 지점에서 멀리 떨어져 있는 격자 일수록 유출해석 결과와 관측 유량의 오차가 커질 수 있다. 본 연구에서는 소유역으로 분할된 유역에 대해서 소유역별로 모형을 보정할 수 있는 다지점 보정기술을 이용해서 유출해석을 수행하였다. 유역내 여러 지점에 대해서 모형을 보정할 경우, 소유역 및 최하류 지점에 대한 유출해석 결과를 향상시킬 수 있다. 이러한 다지점 보정기술은 유역내 여러 지점에 대한 유출량을 계산할 때 효과적으로 적용될 수 있으며, 분포형 모형을 이용한 홍수예보시스템 구축시, 대상 유역내 다수의 지점에 대해 실시간 유출해석을 손쉽게 수행하는 데 적용될 수 있을 것이다.