• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.69-77
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• 2001

An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.389-394
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• 2008

The purpose of this research was to develop a methodology to determine whether conjunctive surface water and groundwater management could significantly reduce deficits in a river basin with a relatively limited alluvial aquifer. The Geum River basin is one of major river basins in South Korea. The upper region of the Geum River basin is typical of many river basins in Korea where the shape of river basin is narrow with small alluvial aquifer depths from 10m to 20m and where most of the groundwater pumped comes quickly from the steamflow. The basin has two surface reservoirs, Daecheong and Yongdam. The most recent reservoir, Yongdam, provides water to a trans-basin diversion, and therefore reduces the water resources available in the Geum River basin. After the completion of Yongdam reservoir, the reduced water supply in the Geum basin resulted in increasing conflicts between downstream water needs and required instream flows, particularly during the low flow season. Historically, the operation of groundwater pumping has had limited control and is administered separately from surface water diversions. Given the limited size of the alluvial aquifer, it is apparent that groundwater pumping is essentially taking its water from the stream. Therefore, the operation of the surface water withdrawals and groundwater pumping must be considered together. The major component of the conjunction water management in this study is a goal-programmin g based optimization model that simultaneously considers surface water withdrawals, groundwater pumping and instream flow requirements. A 10-day time step is used in the model. The interactions between groundwater pumping and the stream are handled through the use of response and lag coefficients. The impacts of pumping on streamflow are considered for multiple time periods. The model is formulated as a linear goal-programming problem that is solved with the commercial LINGO optimization software package.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.209-220
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• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.325-325
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• 2019

본 연구에서는 안동댐 유역을 대상으로 Soil and Water Assessment Tool(SWAT) 모형을 이용해 하천단면 특성을 고려하여 유량 및 수질(SS, TN, DO)을 모의하였다. 안동댐 유역 내 위치한 도산 및 안동댐 관측소의 실측 유량 자료를 이용하였으며, 낙본B 관측소의 수질 측정 자료를 이용하였다. 본 연구에서는 항공사진을 통해서 안동댐 유역 내 각각의 소유역에 대하여 평균 하천폭과 홍수터폭 자료를 구축하였으며, 이를 실측 자료로 가정하였다. 또한 하천단면 실측 자료를 기반으로 상류 유역 면적에 대한 하천폭 및 홍수터폭 회귀식을 개발하였다. 이렇게 개발된 회귀식을 통해 산정된 하천폭과 홍수터폭을 SWAT 모형에 적용하여 유량 및 수질 모의를 모의하였으며, 하천단면 특성을 고려하기 이전(Scenario 1, S1)과 이후(Scenario 2, S2)의 모의 결과를 비교하여 하천단면 특성 고려에 따른 모의 결과의 차이에 대하여 분석하였다. S1와 S2의 하천폭과 홍수터폭을 비교한 결과 S1이 하천폭과 홍수터폭을 과대 산정하는 것으로 나타났으며, S1의 유속은 S2보다 작게 나타났다. 유량 모의 결과와 실측 자료에 대한 $R^2$와 NSE를 산정한 결과 S1과 S2의 결과는 큰 차이를 나타내지 않았으나, S2가 S1에 비해 상대적으로 첨두유량을 높게 모의하는 경향이 나타났다. 유량 모의 결과와 달리 수질 모의 결과에서는 S1과 S2의 차이가 뚜렷하게 나타났다. SS, TN, DO 모의 결과 모두에서 S2가 S1보다 높은 모의 정확도를 나타내었다. 결론적으로 하천단면 특성이 유량 및 수질 모의 정확도에 영향을 주는 것으로 나타났으며, 특히 하천단면과 관련한 변수들은 수질 모의에 있어서 민감하게 영향을 주는 것으로 판단되었다. 하지만 본 연구는 단일 유역에 대해서만 진행되었기 때문에 연구 결과의 신뢰성을 확보하기 위해서는 본 연구의 연구대상 유역과 다른 유역 특성을 가진 유역들을 대상으로 본 연구의 결과에 대한 재검토가 필요하다.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.11-19
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• 2014

This study is analyze future climate and land cover change affects behaviors for amount of streamflow and sediment discharge within basin. We used the climate forecast data in RCP 4.5 and 8.5 (2011-2100) which is opposite view for each other among RCP scenarios that are discussed for 5th report for IPCC. Land cover map built based on a social economic storyline in RCP 4.5/8.5 using Logistic Regression model. In this study we set three scenarios: one scenario for climate change only, one for land cover change only, one for Last both climate change and land cover change. It simulated amount of streamflow and sediment discharge and the result showed a very definite change in the seasonal variation both of them. For climate change, spring and winter increased the amount of streamflow while summer and fall decreased them. Sediment showed the same pattern of change steamflow. Land cover change increases the amount of streamflow while it decreases the amount of sediment discharge, which is believed to be caused by increase of impervious Surface due to urbanization. Although land cover change less affects the amount of streamflow than climate change, it may maximize problems related to the amount of streamflow caused by climate change. Therefore, it's required to address potential influence from climate change for effective water resource management and prepare suitable measurement for water resource.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.111-120
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• 1999

The relationship between EI Nino-Southern Oscillation(ENSO) and drought in Korea is investigated using the cross correlation analysis. In this paper, Palmer Drought Severity Index(PDSI) is used as an index of drought and nine ENSO indicators are used. To obtain PDSI for Korea, the PDSI equation is derived using monthly precipitation and temperature in Korea. In addition, ENSO composite percentile analyses for PDSI, precipitation and streamflow in Korea are performed to verify the results of the cross correlation. Results of the cross correlation show that the link between drought in Korea and ENSO is statistically significant with 6% of the variance in PDSI for Korea explained by ENSO. The PDSI is negatively correlated with the equatorial Pacific Sea Surface Temperature and the Sea Level Pressure(SLP) at Darwin leading by about 16 months. However, the relationship of the PDSI with the Southern Oscillation Index and the SLP at Tahiti is positive correlation. The ENSO composite percentile analyses show that drought, precipitation and streamflow in Korea are associated with ENSO during 6 months from December of the ENSO ending year