• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.346-346
• /
• 2023

한국은 기상·수문정보의 예측이 기상 및 기후 측면에서 주도적으로 이루어지고 있다. 그러나 단기 및 중기 수자원 평가 및 분석을 위해 필요한 시공간적 규모, 정확도, 평가체계를 고려한 기상 기후 예측정보의 활용 방안이 마련될 필요가 있다. 이에 본 연구에서는 미래 수자원 평가 및 분석을 위한 방안을 마련하고자 국내 경안천 유역을 대상으로 하천유량을 예측하고 평가하였다. 이를 위해, 우리는 세계기상기구(World Meteorological Organization, WMO)에서 회원국을 대상으로 배포 중인 수자원 평가 도구인 동적수자원평가시스템(Dynamic Water resources Assessment Tool, DWAT)을 경안천 유역에 대하여 구축하고, 과거 관측 기상 및 유량 자료를 이용하여 매개변수를 보정하였다. 앙상블 하천유량 예측을 위해서 전지구적인 기후 패턴과 국내 기상 특성 간의 상관성 분석 후 이를 예측인자로 활용하여 다중회귀모형과 인공신경망 모형으로부터 생성된 1,000개의 앙상블 강우 및 기온 예측정보를 DWAT의 입력자료로 이용하였다. 2022년에 대한 앙상블예측정보를 DWAT의 입력자료로 사용하여 앙상블 하천유량이 예측되었다. 예측된 일-단위 하천유량은 실제 관측유량과 차이를 보이나 이는 예측된 앙상블 강우 및 기온정보의 오차에 기인하는 것으로 보인다. 이러한 결과는 수문 모형 결과의 오차는 강제 자료의 오차에 큰 영향을 받는 한계를 다시 한번 확인시켜준다. 따라서 단기·중기 수자원 평가 및 분석을 월-단위 하천유량으로 변환하여 월별 통계치를 분석하는 방향을 고려할 필요가 있다.

• Journal of Korea Water Resources Association
• /
• v.57 no.5
• /
• pp.333-346
• /
• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1239-1248
• /
• 2021

In this paper, we present FDNN algorithm to perform prediction based on academic understanding. In order to apply prediction based on academic understanding rather than data-dependent prediction to deep learning, we constructed algorithm based on mathematical and hydrology. We construct a model that predicts flow rate of a river as an input of precipitation, and measure the model's performance through K-fold cross validation.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.6B
• /
• pp.579-587
• /
• 2010

The mid-range streamflow forecast was performed using NWP(Numerical Weather Prediction) provided by KMA. The NWP consists of RDAPS for 48-hour forecast and GDAPS for 240-hour forecast. To enhance the accuracy of the NWP, QPM to downscale the original NWP and Quantile Mapping to adjust the systematic biases were applied to the original NWP output. The applicability of the suggested streamflow prediction system which was verified in Geum River basin. In the system, the streamflow simulation was computed through the long-term continuous SSARR model with the rainfall prediction input transform to the format required by SSARR. The RQPM of the 2-day rainfall prediction results for the period of Jan. 1~Jun. 20, 2006, showed reasonable predictability that the total RQPM precipitation amounts to 89.7% of the observed precipitation. The streamflow forecast associated with 2-day RQPM followed the observed hydrograph pattern with high accuracy even though there occurred missing forecast and false alarm in some rainfall events. However, predictability decrease in downstream station, e.g. Gyuam was found because of the difficulties in parameter calibration of rainfall-runoff model for controlled streamflow and reliability deduction of rating curve at gauge station with large cross section area. The 10-day precipitation prediction using GQPM shows significantly underestimation for the peak and total amounts, which affects streamflow prediction clearly. The improvement of GDAPS forecast using post-processing seems to have limitation and there needs efforts of stabilization or reform for the original NWP.

• Nuclear Engineering and Technology
• /
• v.26 no.1
• /
• pp.126-139
• /
• 1994

Best-estimate thermal-hydraulic codes, CATHARE2 V1.2 and RELAP5/MOD3, hate been assessed against the BETHSY 6.2 tc six-inch cold leg break loss-of-coolant accident (LOCA) test. Main objective is to analyze the overall capabilities of the two codes on physical phenomena of concern during the small break LOCA i.e. two-phase critical flow, depressurization, core water level de-pression, loop seal clearing, liquid holdup, etc. The calculation results show that the too codes predict well both in the occurrences and trends of major two-phase flow phenomena observed. Especially, the CATHARE2 calculations show better agreements with the experimental data. However, the two codes, in common, show some deviations in the predictions of loop seal clearing, collapsed core water level after the loop seal clearing, and accumulator injection behaviors. The discrepancies found from the comprision with the experimental data are larger in the RELAP5 results than in the CATHARE2. To analyze the deviations of the two code predictions in detail, several sensitivity calculations have been performed. In addition to the change of two-phase discharge coefficients for the break junction, fine nodalization and some corrections of the interphase drag term are made. For CATHARE2, the change of interphase drag force improves the mass distribution in the primary side. And the prediction of SG pressure is improved by the modification of boundary conditions. For RELAP5, any single input change doesn't improve the whole result and it is found that the interphase drag model has still large uncertainties.

• Journal of Animal Science and Technology
• /
• v.49 no.3
• /
• pp.359-368
• /
• 2007

Holstein cows(n=12) were assigned to one of three diets containing control diet and diets containing a microbial culture, 50ml(T1) and 100ml(T2) SDN(R)(amicrobial culture), per day. The basal diet containing concentrate mixture, corn silage and timothy hay were fed midlactating cows for 12 weeks. Milk production tended to be higher for cows fed T2 diet (20.8kg/day) than fed T1(19.7kg/d) and control diet (19.2kg/day).  There was a tendency of an increase in 4% FCM for cows fed T2 diet(19.6kg/day) than T1(18.8kg/d) and control diet(18.4kg/day). Milk components were not found to be different between cows fed control diet and SDN(R) diets. There was a tendency an increase in milk protein for cows fed control diet(3.43%) compared with microbial diets, T1 and T2(3.08% and 3.20%). However, milk protein production was not significantly different between control diet(0.65kg/d) and T1(0.61kg/d) or T2(0.67kg/d). Somatic cell counts for cows fed T1(72,000) and T2(60,000/ml) were lower than cows fed control diet (108,000/ml) (P<0.05). In conclusion, the cows that were fed diets containing SDN(R) as a microbial culture resulted a tendency of an increase in milk production and a reduction of somatic cell counts which indicates improved milk quality and hygiene.

• Journal of Wetlands Research
• /
• v.25 no.2
• /
• pp.99-110
• /
• 2023

Non-point source (NP) pollutants in an agricultural landuse are discharged from a large area compared to those in other land uses, and thus effective source control measures are needed. To develop appropriate control measures, it is necessary to quantify discharge load of each source and evaluate the degree of water quality improvement by implementing different options of the control measures. This study used Hydrological Simulation Program-FORTRAN (HSPF) to quantify pollutant discharge loads from different sources and effects of different control measures on water quality improvements, thereby supporting decision making in developing appropirate pollutant control strategies. The study area is the Gyeseong river watershed in Changnyeong county, Gyeongsangnam-do, with agricultural areas occupying the largest proportion (26.13%) of the total area except for the forest area. The main pollutant sources include chemical and liquid fertilizers for agricultural activities, and manure produced from small scale livestock facilities and applied to agriculture lands or stacked near the facilities. Source loads of chemical fertilizers, liquid fertilizers and livestock manure of small scale livestock facilities, and point sources such as municipal wastewater treatment plants (WWTPs), community WWTPs, private sewage treament plants were considered in the HSPF model setup. Especially, NITR and PHOS modules were used to simulate detailed fate and transport processes including vegitation uptake, nutrient deposition, adsorption/desorption, and loss by deep percolation. The HSPF model was calibrated and validated based on the observed data from 2015 to 2020 at the outlet of the watershed. The calibrated model showed reasonably good performance in simulating the flow and water quality. Five Pollutants control scenarios were established from three sectors: agriculture pollution management (drainge outlet control, and replacement of controlled release fertilizers), livestock pollution management (liquid fertilizer reduction, and 'manure management of small scale livestock facilities) and private STP management. Each pollutant control measure was further divided into short-term, mid-term, and long-term scenarios based on the potential achievement period. The simulation results showed that the most effective control measure is the replacement of controlled release fertilizers followed by the drainge outlet control and the manure management of small scale livestock facilities. Furthermore, the simulation showed that application of all the control measures in the entire watershed can decrease the annual TN and TP loads at the outlet by 40.6% and 41.1%, respectively, and the annual average concentrations of TN and TP at the outlet by 35.1% and 29.2%, respectively. This study supports decision makers in priotizing different pollutant control measures based on their predicted performance on the water quality improvements in an agriculturally dominated watershed.