• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.21-21
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• 2018

수자원 시스템의 용수공급의 안정도를 평가하는 지표로 국내에서는 이수안전도 혹은 안전채수량(safety degree for water shortage or safe yield)의 개념이 이용된다. 아울러 공급 측면에서는 기준갈수량, 공급신뢰도, 저수용량 등이 분석되고 있으며, 수요 측면에서는 용수공급 보장일수, 최소 부족량, 갈수 조정기간 및 용수부족에 따른 피해정도 등을 고려하고 있다. 전통적으로 수자원 시스템의 평가는 용수공급 실패기간의 통계적 특성을 분석하여 이루어진다. 용수공급 실패기간으로부터 분석되는 통계적 특성은 용수부족 발생빈도, 용수부족 지곡기간 및 용수부족 총 양 등 세 가지로 정량화되는 것이 일반적이다. 수자원 시스템이 수요를 만족시키는 정도인 신뢰도(reliability), 용수부족 발생 후 얼마나 빨리 회복하는지를 나타내는 회복도(resilience) 및 용수부족의 양적 크기를 나타내는 취약도(vulnerability)의 지표는 앞서 언급된 세 가지 통계 특성으로부터 계산된다. 본 연구에서는 Copula 기반 이변량 빈도해석 개념을 적용하여 댐 용수공급 취약성 평가 방법을 개선한 후, 국내 남강 댐 유역의 용수공급 취약성을 평가해보고자 한다. 이를 위해, 국내외에서 이용되고 있는 용수공급 평가지표들의 특성들을 정리하였다. 다음으로는, 취약성 평가 방법에 Copula 기반 이변량 빈도해석 방법을 적용하는 방법을 제안하였다. 본 연구의 분석은 용수공급 실패 사상을 기준으로 수행되었으며, 용수공급 실패 사상의 발생확률은 포아송 분포, 총 부족량은 대수정규분포로 모의되었다. 최종적으로는 남강 댐의 재현기간별 취약성 평가 결과를 도출하여 본 연구에서 제안한 취약성 평가방법의 적용성을 검증하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.74-79
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• 2002

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.227-232
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• 2002

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.59-64
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 2000.05a
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• pp.151-156
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 2003.05b
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• pp.643-646
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• 2003

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.997-1001
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• 2009

GIS 기반의 HEC-HMS를 이용하여 유량자료가 있는 소하천인 정자천 유역을 대상으로 장기 강우 유출 분석을 하였다. 일반적으로 홍수량 산정은 단기해석으로 분석하나 평 갈수기와 홍수기 때의 하천 유황이 다르기 때문에 매개변수가 불일치할 것이라 생각되고, 이에 대한 보정이 필요한지 판단이 필요하다. 이를 위해 장기 연속모의를 통하여 매개변수의 보정 필요성을 검토하였다. 연구는 수치지도를 조합하여 ARC-VIEW로부터 Map파일 및 Basin파일을 생성하였고, 토지이용도와 토양도를 ARC-VIEW를 이용하여 CN value를 추출하였다. 계산조건중 손실량 산정방법은 SCS Curve Number법으로 하였고, 단위도 방법은 Clark UH법, 하도추적방법은 Muskingum방법, 기저유량산정방법은 Constant monthly로 설정하였다. 유역면적, 도달시간자료, 저류상수 값 등의 추출은 GIS기법을 이용하여 추출하였다. HEC-HMS의 장기 연속모의(Continuous Simulation)로 얻어진 Element Graph를 보면 대략적인 형태가 일치하나 2006년도에 대한 모의에서는 홍수기의 결과만 일치하는 것으로 보이고, 2007년도에 대한 모의에서는 평 갈수기와 홍수기의 그래프 형태가 유사하게 나타났다. 실측 유량보다 유량 값이 약간 크게 산출되어 홍수량 산정에서 볼 때 안정성에 무리가 없다고 판단되지만, 평 갈수기 기간에서 볼 때 연마다 하천의 매개변수가 일치하지 않는다고 생각되며, 홍수 후 유역의 변화로 매개변수가 변화한 것이라 생각된다. 향후 정자천유역의 보다 많은 강우사상과 실측유량을 통해 HEC-HMS의 유출량을 비교 분석하면 보다 더 정확한 해석이 가능할 것이며, 홍수가 빈번한 지역의 경우 유수지의 검토와 저수지의 시간당 방류량을 알 수 있다면 오차의 범위를 줄일 수 있다고 생각된다. 더 나아가 우리나라에 적합한 매개변수와 GIS 프로그램이 개발된다면 보다 쉽고 정확한 해석이 가능할 것이라고 생각된다.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.4
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• pp.223-233
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• 2010

Spatio-temporal variations of long-term water qualities (COD, SS, $Chl-{\alpha}$, N-related nutrients (TN, TDN, $NO_3^-$, $NH_4^+$), P-related nutrients (TP, TDP, $PO_4^{3-}$)) at two stations (St. SD, St. GG) in the Geumgang Reservoir were investigated from August 2001 to July 2008. Statistical methods such as t-test, factor analysis, and multi-regression analysis were applied to the water quality data in the reservoir as well as mass balances on TP. From the temporal comparisons of the water qualities between 2002 and 2007, average concentrations of $NH_4^+$, $PO_4^{3-}$, and TDP gradually decreased down by 60%, 24%, 52% in 2007. However, those of TP and $Chl-{\alpha}$ increased to 99% and 423% during the period. From the spatial comparisons between the two stations, St. GG showed higher concentrations for all of the N- and P-related nutrients than in St. SD, while opposite result for the $Chl-{\alpha}$. The factor analysis showed that "the seasonal variations of N- and P-related nutrients" were the two dominant factors occupying 49% of total variances of water qualities. Based on this result, multi-regression analysis executed for the two most influential parameters (TP and $Chl-{\alpha}$) focusing on the seasonal variations of these parameters: SS and $Chl-{\alpha}$ has contributed decisively to the concentrations of TP during the wet and dry season, respectively. On the other hand, COD and TP has been important for the $Chl-{\alpha}$ during the wet and dry season, respectively. From the established mass balances of TP loadings in the Geumgang Reservoir, Other Sources (60%) occupied the greatest contribution and Fluvial Input (38%) and Sediment (1%) during the wet season. However, both Fluvial Water (48%) and Other Sources (47%) supplied comparable amount of inputs and Sediment (5%) showed significantly increased input during the dry seasons. Recently especially during the dry winter seasons, migrating bird's excretion was estimated to contribute up to 8% of total TP input and 21% of Other Sources.

• Water for future
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• v.24 no.1
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• pp.119-128
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• 1991

This study was focused on establishing the concepts of the instream flow to prevent the problems for the conceptual ambiguity and the difference in the instream flow estimation methods. The average drought flow is defined as the flow required to guarantee the minimum function of the river such as prevention of drying. The environmental control flow is defined as the flow required to control optimal river environment, the flow required for navigation, prevention of sea water-intrusion, protection of river management facilities, conservation of water Quality, fishing, prevention of river mouth closure, control of groundwater level, protection of animals and plants, and landscape. The average drought flow was obtained by flow duration analysis for the natural flows in the Han River at Indo-Bridge gaging station. When considering the 9 factors related to environment conservation, the conservation of water quality was proved to be most important. The pollutants for the river flows were estimated and the water qualities were forecasted. After comparing the water qualities in the future and water quality standards, there quired optimal dilution flow was estimated. The average drought flow and environmental control flow are all non-consumptive flows. Therefore larger flow between them, i.e., Max. (average drought flow, environmental control flow) can be the instream flow. The river management flow can be added to the flows for water utilization in the downstream. The results from this study are expected to be very helpful in the systematic river management on the other main rivers in Korea.