• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.951-960
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• 2007

Window interface to Hydrological Simulation Program-FORTRAN (WinHSPF) developed by the United States Environmental Protection Agency (EPA) was applied to the upstream of Nam-Han river watershed to examine its applicability for loading estimates in watershed scale and to evaluate non-point source control scenarios using BMPRAC in WinHSPF. The WinHSPF model was calibrated and verified for water flow using Ministry of Construction and Transportation (MOCT, 3 stations, 2003~2005) and water qualities using Ministry of Environment (MOE, 5 station, 2000~2006). Water flow and water quality simulation results were also satisfactory over the total simulation period. But outliers were occurred in the time series data of TN and TP at some regions and periods. Therefore, it required more profit calibration process for more various parameters. As a result, all the study was performed within the expectation considering the complexity of the watershed, pollutant sources and land uses intermixed in the watershed. The estimated pollutant load for annual average about $BOD_5$, T-N and T-P respectively. Nonpoint source loading had a great portion of total pollutant loading, about 86.5~95.2%. In WinHSPF, BMPRAC was applied to evaluate non-point source control scenarios (constructed wetland, wet detention ponds and infiltration basins). All the scenarios showed efficiency of non-point source removal. Overall, the HSPF model is adequate for simulating watersheds characteristics, and its application is recommended for watershed management and evaluation of best management practices.

• Journal of Korean Society on Water Environment
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• v.34 no.3
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• pp.328-338
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• 2018

The objective of this study was to evaluate the applicability of a HSPF (Hydrological Simulation Program-Fortran) model for runoff estimation in the Namgang dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input for the HSPF model, which was calibrated and validated using observed runoff data from 2004 to 2015 for three stations (Sancheong, Shinan, Changchon) in the study watershed. Parameters for runoff calibration were selected based on the user's manual and references, and parameter calibration was done by trial and error. The $R^2$ (determination coefficient), RMSE (root-mean-square error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (relative mean absolute error) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within a ${\pm}5%$ error in Sancheong and Shinan, whereas there was a14% error in Changchon. The model performance criteria for calibration and validation showed that $R^2$ ranged from 0.80 to 0.92, RMSE was 2.33 to 2.39 mm/day, NSE was 0.71 to 0.85, and RMAE was 0.37 to 0.57 mm/day for daily runoff. Visual inspection showed that the simulated daily flow, monthly flow, and flow exceedance graph agreed well with observations for the Sancheong and Shinan stations, whereas the simulated flow was higher than observed at the Changchon station.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.101-111
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• 2015

Establishment of appropriate data in certain formats is essential for agricultural water cycle analysis, which involves complex interactions and uncertainties such as climate change, social & economic change, and watershed environmental change. The main objective of this study was to develop web-based Data processing and Model linkage Techniques for Agricultural Water-Resource analysis (AWR-DMT). The developed techniques consisted of database development, data processing technique, and model linkage technique. The watershed of this study was the upper Cheongmi stream and Geunsam-Ri. The database was constructed using MS SQL with data code, watershed characteristics, reservoir information, weather station information, meteorological data, processed data, hydrological data, and paddy field information. The AWR-DMT was developed using Python. Processing technique generated probable rainfall data using non-stationary frequency analysis and evapotranspiration data. Model linkage technique built input data for agricultural watershed models, such as the TANK and Agricultural Watershed Supply (AWS). This study might be considered to contribute to the development of intelligent watercycle analysis by developing data processing and model linkage techniques for agricultural water-resource analysis.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.233-240
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• 2004

Most of hydrological analyses in the field of water resources are launched by gathering and analyzing rainfall data. Several methods have been developed to estimate areal rainfall from point rainfall data and to fill missing or ungaged data. Thiessen and Reciprocal Distance Squared(RDS) methods whose parameters are only dependent on inter-station distance are classical work in hydrology, but these techniques do not provide a continuous representation of the hydrologic process involved. In this study, kriging technique was applied to rainfall analysis in Nakdong river basin in order to complement the defects of these classical methods and to reflect spatial characteristics of regional rainfall. After spatial correlation and semi-variogram analyses were performed to perceive regional rainfall property, kriging analysis was performed to interpolate rainfall data for each grid Thus, these procedures were enable to estimate average rainfall of subbasins. In addition, poor region of rainfall observation was analyzed by spatial interpolation error for each grid and mean error for each subbasin.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.6
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• pp.93-102
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• 2014

Generally data loading is a laborous job to develop models. Meteorological data is basic input data for hydrological models, it is provided through websites of Korea Meteorological Administration (KMA). The website of KMA provides daily meteorological observation data with tabular format classified by years, items, stations. It is cumbersome to manipulate tabular format for model inputs such as time series and multi-item or multi-station data. The provider oriented services which broadcast restricted formed information have caused inconvenient processes. Tim O'Reilly introduces "Web 2.0" which focuses on providing a service based on data. The top ranked IT companies such as google, yahoo, daum, and naver provide customer oriented services with Open API (Application Programming Interface). A RESTful web service, typical implementation for Open API, consists URI request and HTTP response which are simple and light weight protocol than SOAP (Simple Object Access Protocol). The aim of this study is to develop a web-based service that helps loading data for human use instead of machine use. In this study, the developed RESTful web service provides Open API for manipulating meteorological data. The proposed Open API can easily access from spreadsheet programs, web browsers, and various programming environments.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.39-50
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• 2020

The objective of this study was to assess the livestock nonpoint source pollutant impact on water quality in Namgang dam watershed using the HSPF (Hydrological Simulation Program-Fortran) model. The input data for the HSPF model was established using the landcover, digital elevation, and watershed and river maps. In order to apply the pollutant load to the HSPF model, the delivery load of the livestock nonpoint source in the Namgang dam watershed was calculated and used as a point pollutant input data for the HSPF model. The hydrologic and water quality parameters of HSPF model were calibrated and validated using the observed runoff data from 2007 to 2015 at Sancheong station. The R² (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. The simulation results for annual mean runoff showed that R² ranged 0.79~0.81, RMSE 1.91~2.73 mm/day, NSE 0.7~0.71 and RMAE 0.37~0.49 mm/day for daily runoff. The simulation results for annual mean BOD for RMSE ranged 0.99~1.13 mg/L and RMAE 0.49~0.55 mg/L, annual mean TN for RMSE ranged 1.65~1.72 mg/L and RMAE 0.55 mg/L, and annual mean TP for RMSE ranged 0.043~0.055 mg/L and RMAE 0.552~0.570 mg/L. As a result of livestock nonpoint pollutant loading simulation for each sub-watersehd using the HSPF model, the BOD ranged 16.6~163 kg/day, TN ranged 27.5~337 kg/day, TP ranged 1.22~14.1 kg/day.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.38 no.3
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• pp.172-183
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• 2005

To assess the macrobenthic community of oligohaline Youngam Lake, which is located at the Youngsan Watershed on the southwest part of Korea, macrobenthic fauna were collected at 45 stations during May, 2002. A total of 16 species of macrofauna were recorded with a mean density of 240 individuals per $m^2$ and a mean biomass of 7.07 g wet weight per $m^2$. Major dominant faunal groups were crustacean arthropods in terms of the number of species and abundance, and polychaete annelids in terms of biomass. The mean grain size was $5.7\;{\phi}$ which was dominated by silt fraction. The hydrological environment of the lake was characterised as an oligohaline environment with a mean surface water temperature of $17.8^{\circ}C$ and a mean salinity of 2.08 psu. The major dominant species were amphipods, Corophium sp. ($31\%$) and Jesogammarus sp. ($25\%$). Lowe. values of species diversity (H') with a mean of 0.81 (less than 1.0 from most stations) reflected the overall poor faunal diversity in this area. Multivariate analysis suggested that this benthic faunal community could be divided into four sub-regions such as the area from lake proper to water channel to the south, the stations located at the entrance and northern water channel, the stations near the dike, and the lake proper area. Freshwater and brackish water species which occurred in each station group were corresponded to the oligohaline salinity regime. Bottom hypoxia appeared in the entrance part of the lake between dyke and lake proper on May, which was resulted from stratification from spring season. These facts imply that marine macrobenthos were severely impacted by low salinity and a consequent hypoxia after embankment of the lake due to the restriction of water circulation.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.383-393
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• 2018

The regional frequency analysis is the method which uses not only sample of target station but also sample of neighborhood stations in which are classified as hydrological homogeneous regions. Consequently, identification of homogeneous regions is a very important process in regional frequency analysis. In this study, homogeneous regions for regional frequency analysis of precipitation were identified by the self-organizing map (SOM) which is one of the artificial neural network. Geographical information and hourly rainfall data set were used in order to perform the SOM. Quantization error and topographic error were computed for identifying the optimal SOM map. As a result, the SOM model organized by $7{\times}6$ array with 42 nodes was selected and the selected stations were classified into 6 clusters for rainfall regional frequency analysis. According to results of the heterogeneity measure, all 6 clusters were identified as homogeneous regions and showed more homogeneous regions compared with the result of previous study.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.457-457
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• 2012

말라리아는 매개체에 의한 전염병으로써 국내에서는 이미 1970년대에 사라진 것으로 알려져 있다. 하지만 1990년대에 재발생하여 2000년대 초반까지 경기도와 강원도 북부지역에서 환자가 증가하는 양상을 보였다. 사람에게서 발병하는 말라리아는 4종으로 알려져 있으나 우리나라의 경우 이 중 오로지 삼일열 원충감염에 의한 것으로 밝혀졌다(질병관리 본부, 2010). 기후변화는 질병의 발생에 영향을 미칠 수 있는 중요한 요인 중 하나로써 매개체에 의한 질병의 경우 기후요소는 매개체의 번식과 활동에 적지않은 영향을 미친다. 특히 말라리아의 경우 병원균을 가진 개체수와 모기에 물리는 횟수, 감염된 모기의 수, 그 모기에 사람이 물리는 횟수와 관계가 있으나 기온과 강수량, 습도의 변화 등 기후 및 수문학적 요소와도 밀접한 관계를 가지는 것으로 밝혀졌다(Lindsay & Birley, 1996; 박윤형 외, 2006; 신호성, 2011 재인용). 본 연구의 목적은 한반도 기후-수문학적 환경특성 및 변화를 파악하고 지역적 말라리아 발생과의 상관관계를 도출하며 이를 기반으로 하여 말라리아 발생의 변동을 예측하는 것이다. 분석에 사용된 데이터는 말라리아 발생자료의 경우, 질병관리 본부에서 제공하는 2001년 1월~2011년 12월 까지의 약 16000건의 발병자료가 포함 되었고 분석의 시간 단위는 2WEEKS 이며 전국 251개의 시군구에서 발생한 전염병을 합산하였다. 기상자료의 경우 기상청 기후자료 관리 시스템에서 제공하는 동일 기간대의 평균기온, 최고(최저)기온, 강수량, 신적설, 평균 해면기압, 평균 이슬점 온도, 평균 상대습도, 평균풍속, 평균운량, 일조시간 자료를 활용하였다. 본 연구에 사용된 AWS(Automatic Weather Station)자료의 경우 기본적으로 point 형태의 관측자료이고, 분석기간 동안의 개수에서도 차이가 있기 때문에 공간 내삽기법인 kriging을 활용하여 행정구역과 zonal하는 방법으로 재가공 하였다. 지역의 수문학적 특성의 경우 10*10 DEM을 기반으로 ESRI ArcGIS 소프트웨어의 ArcHydro 기능을 이용 하여 유역을 생성하는 방법을 채택하였다. 본 연구에서는 통계적 모형을 기본으로 기후 및 수문 특성과 말라리아 발생간의 상관관계를 분석하였으며 시계열 자료의 특성상 포아송 분포의 Generalized Estimation Equation 과 Generalized Linear Model을 이용한다(Baccini 외, 2008; 신호성, 2011). 또한 말라리아 잠복시간의 지연효과 및 전염병의 계절 영향을 반영하기 위하여 Fourier transform 을 적용 하였다.