• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.55-63
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• 2018

This study analyzed the applications of near real-time drought monitoring using satellite rainfall for the Korean Peninsula and un-gaged basins. We used AWS data of Yongdam-Dam, Hoengseong-Dam in Korea area, the meteorological station of Nakhon Rachasima, Pak chong for test-bed to evaluate the validation and the opportunity for un-gaged basins. In addition, we calculated EDI (Effective doought index) using the stations and co-located PERSIANN-CDR, TRMM (Tropical Rainfall Measurement Mission) TMPA (The TRMM Multisatellite Precipitation Analysis), GPM IMERG (the integrated Multi-satellitE Retrievals for GPM) rainfall data and compared the EDI-based station data with satellite data for applications of drought monitoring. The results showed that the correlation coefficient and the determination coefficient were 0.830 and 0.914 in Yongdam-dam, and 0.689 and 0.835 in Hoengseng-Dam respectively. Also, the correlation coefficient were 0.830, 0.914 from TRMM TMPA datasets and compasion with 0.660, 0.660 based on PERSIANN-CDR and TRMM data in nakhon and pakchong station. Our results were confirmed possibility of near real-time drought monitoring using EDI with daily satellite rainfall for un-gaged basins.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.561-574
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• 2016

The purpose of this study is to enhance the quality of APEC Edutainment Exchange Program (AEEP) that was developed for Korean multicultural students and implemented in Philippines. Based on literature review and data analysis, we designed and developed edutainment-based contents for their team projects. The participants of the AEEP which was carried out between Aug 12th and 19th in 2012 were 34 elementary and secondary school students with program coordinators. Data collection included survey, video, interview, report and episodes. The data analysis of AEEP activities revealed the features of global experiential learning and edutainment in the K-pop and cooking projects where the Korean-Philippino students exchanged their cultural activities with joyful cooperation. The data also confirmed the Korean students' positive changes toward multi-cultural understandings and attitudes.

• Korean Journal of Veterinary Research
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• v.50 no.3
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• pp.239-246
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• 2010

Among 203 avian pathogenic Escherichia coli (APEC) isolated from poultry with colibacillosis in korea, 14 isolates were selected from total 68 isolates transferred R plasmid and classified into 5 groups on the basis of antimicrobial minimal inhibitory concentration (MIC) pattern, farm source and O serotype. An association between clonal origin and R plasmid of them was investigated by R plasmid profile, restriction endonuclease analysis and pulsed-field gel electrophoresis (PFGE). The strains that showed the same or very similar antimicrobial MIC pattern, but different farm source and O serotype, revealed different PFGE pattern, which seemed to be different clonal origin. And the strains that showed the same MIC pattern and O serotype, revealed different PFGE pattern, seemed to be originated from different clone. Also the strains showing the same MIC pattern and farm source, but different O serotype, revealed to be different clonal origin. The strains that showed the same or similar MIC pattern, farm source, and O serotype, revealed identical or similar PFGE pattern, which seemed to belong to be one clone. Meanwhile, horizontal transfer of R plasmid seems to be common in APEC with regardless of O serotype and clone of the strains. These results indicate that rapid and accurate epidemiological survey of APEC can be possible by the combination of O serotyping, plasmid profiling and PFGE analysis following the classification of them into groups of antimicrobial drug resistance pattern.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1784-1788
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• 2010

APEC 기후센터(APEC Climate Center, APCC)에서 제공하는 다중모형앙상블(Multi-model Ensemble, MME) 형태의 계절예측정보를 이용하여 3개월 가뭄전망을 수행하였다. APCC MME는 기후예측모형이 가지는 불확실성을 최소화하기 위한 방법으로, 아시아 태평양 지역 내 9개 회원국 16개 기관 21개 기후모형의 계절예측정보를 활용하여, 개별 모형이 가지는 계통오차(Systematic error)를 앙상블 기법을 통하여 상쇄함으로써 최적의 예측자료를 도출한다. 또한, 기후예측 모형이 예측한 대기순환장은 관측 지점변수와 경험적 통계적 관련성을 가지므로, 이를 바탕으로 상세지역의 이상기후에 대한 정보를 도출할 수 있다. 본 연구에서는 가뭄 관리 및 전망을 위한 입력 자료로서, 기상전문 기관인 APEC 기후센터 (APEC Climate Center, APCC)에서 제공하는 전구 규모의 기온 및 강수 전망자료를 기상청 산하 59개 지점의 전망자료로 통계적 규모 축소화 기법을 통해 3개월 예보를 실시하였다. APCC 계절예측자료를 가뭄모니터링시스템의 자료입력 포맷에 따라 적절히 가공한 뒤, 가뭄 관리 및 전망을 위하여 SPI(Standard Precipitation Index) 및 PDSI(Palmer Drought Severity Index)지수의 입력자료로 사용하여 SPI 및 PDSI 지수를 산정하였다. 또한 분위사상법(Quantile Mapping)을 이용하여 총 59개 지점의 과거 월평균 관측값과 최근 2009년에 대한 모의값의 누적확률분포값을 계산하고 모의값의 확률분포를 관측값의 확률분포에 사상시켜 가뭄 전망을 위한 기상변수의 오차를 보정하고자 하였다. 이러한 계절예측정보를 이용하여 가뭄 전망에 대한 신뢰도가 높아진다면, 사전예방 및 피해완화로 가뭄상황에 대한 신속한 대처 및 피해의 경감이 이루어질 수 있을 것이다.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.149-162
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• 2018

It is necessary to select the appropriate global climate model (GCM) to take into account the impacts of climate change on integrated water management. The objective of this study was to develop the selection technique of representative GCMs for uncertainty in climate change scenario. The selection technique which set priorities of GCMs consisted of two steps. First step was evaluating original GCMs by comparing with grid-based observational data for the past period. Second step was evaluating whether the statistical downscaled data reflect characteristics for the historical period. Spatial Disaggregation Quantile Delta Mapping (SDQDM), one of the statistical downscaling methods, was used for the downscaled data. The way of evaluating was using explanatory power, the stepwise ratio of the entire GCMs by Expert Team on Climate Change Detection and Indices (ETCCDI) basis. We used 26 GCMs based on CMIP5 data. The Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios were selected for this study. The period for evaluating reproducibility of historical period was 30 years from 1976 to 2005. Precipitation, maximum temperature, and minimum temperature were used as collected climate variables. As a result, we suggested representative 13 GCMs among 26 GCMs by using the selection technique developed in this research. Furthermore, this result can be utilized as a basic data for integrated water management.

• Journal of Korean Society of Rural Planning
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• v.23 no.4
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• pp.153-168
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• 2017

The main objective of this study was to assess reference evapotranspiration based on multiple GCMs (General Circulation Models) and estimation methods. In this study, 10 GCMs based on the RCP (Representative Concentration Pathway) 4.5 scenario were used to estimate reference evapotranspiration. 54 ASOS (Automated Synoptic Observing System) data were constructed by statistical downscaling techniques. The meteorological variables of precipitation, maximum temperature and minimum temperature, relative humidity, wind speed, and solar radiation were produced using GCMs. For the past and future periods, we estimated reference evapotranspiration by GCMs and analyzed the statistical characteristics and analyzed its uncertainty. Five methods (BC: Blaney-Criddle, HS: Hargreaves-Samani, MK: Makkink, MS: Matt-Shuttleworth, and PM: Penman-Monteith) were selected to analyze the uncertainty by reference evapotranspiration estimation methods. We compared the uncertainty of reference evapotranspiration method by the variable expansion and analyzed which variables greatly influence reference evapotranspiration estimation. The posterior probabilities of five methods were estimated as BC: 0.1792, HS: 0.1775, MK: 0.2361, MS: 0.2054, and PM: 0.2018. The posterior probability indicated how well reference evapotranspiration estimated with 10 GCMs for five methods reflected the estimated reference evapotranspiration using the observed data. Through this study, we analyzed the overall characteristics of reference evapotranspiration according to GCMs and reference evapotranspiration estimation methods The results of this study might be used as a basic data for preparing the standard method of reference evapotranspiration to derive the water management method under climate change.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.47-58
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• 2018

In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.205-205
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• 2018

전구기후모델은 전 지구 규모에서 일관성 있는 전망 결과를 제공한다. 이를 수자원분야의 활용과 같은 지역 단위의 응용분야에 실질적으로 활용하기 위해서는 상세화 절차가 반드시 필요하며, 상세화 전후의 결과에 대한 평가가 필요하다. 본 연구에서는 전구기후모델을 이용한 상세화 전후의 체계적인 평가를 위한 방법을 제안하고자 한다. 평가방법으로는 과거 재현성 평가와 미래 불확실성 평가를 통해 실시하였다. 과거 재현성 평가는 상세화 이전 전구기후모델의 과거 공간재현성평가와 상세화 된 자료와 ETCCDI를 이용한 Technique for Order of Preference b Similarity to Ideal Solution (TOPSIS)기법으로 평가하였다. 미래 기간의 불확실성 평가는 Katsavounidis approach (KKZ)방법을 통한 미래 불확실성의 설명력을 고려하여 실시하였다. 전구기후모델은 CMIP5에서 제공되는 모형들 중 26를 이용하였고, Representative Concentration Pathways (RCP) 시나리오는 4.5와 8.5를 이용하였고, 기상변수는 강수량, 최대기온, 최저기온을 구축하였다. 상세화는 통계적 상세화방법 중 하나인 Spatial Disaggregation Quantile Delta Mapping (SDQDM)방법을 이용하였다. 과거 재현성평가를 위한 과거기간은 1976년부터 2005년까지의 30년 기간을 사용하였다. 미래 불확실성 평가를 위한 기간은 3개 구간 (2011-2040, 2041-2070, 2071-2099)을 사용하였다. 과거 재현성 평가를 통해 26개 전구기후모델 중 모사력이 부족하다고 판단되는 모델을 제외한 19개 전구기후모델을 선정하였고, 이를 이용하여 미래 불확실성 평가를 실시하였다. 그 결과 각각의 미래기간과 RCP시나리오에서의 미래변동성을 설명하기 위한 전구기후모델의 최소 필요수를 알 수 있었다. 본 연구의 결과를 효율적인 수자원분야의 전구기후모델의 활용이 가능할 것으로 기대된다.

• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.