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제1장 서론 16

제2장 연구 지역 18

제3장 연구 방법 20

3.1. 관측 자료 수집 20

3.1.1. 현장 관측 20

3.2. 수치모델 구축 21

3.2.1. 모델 개요 21

3.2.2. 격자 구성 22

3.2.3. 초기 조건 및 경계 조건 24

3.2.4. 바람장 및 해면기압 입력조건 27

3.2.5. 해저면 경계 입력 조건 27

3.2.6. 해저질 입력 조건 30

3.2.7. 수층 내 부유사 이동 (Suspended sediment transport) 33

3.2.8. 소류사 수송(Bed load transport) 35

3.2.9. 퇴적물 입력 파라미터 36

제4장 연구 결과 43

4.1. 수치모델 검증 43

4.1.1. 조위 44

4.1.2. 유속 45

4.1.3. 염분 46

4.1.4. 파랑 검증 53

4.1.5. 부유사 검증 57

4.1.6. 퇴적률 75

제5장 토의 77

5.1. 외부적 요인 78

5.2. 내부적 요인 85

제6장 결론 96

참고 문헌 98

표목차

Table 1. Setup details for ADCP and CTD observations 20

Table 2. Erosion rate parameter (E0), settling velocities (Ws) and critical shear stress (τcr) used in previous and this studies. All these studies used parameter was based on CSTMS sediment transport model.[이미지참조] 40

Table 3. Sediment parameters for sensitivity tests of sediment transport model. Input and output parameters from C1 to C10. Input parameters included erosion... 41

Table 4. Statistic result for model-data comparision associate with the tide level 44

Table 5. Statistic results for model-data comparison associate with each station current and salinity. 51

Table 6. Model validation of significant wave height at 6 wave buoy. 54

Table 7. The location, period, and observation time of the mooring stations which acquire turbidity and SSC. 57

Table 8. OBS-derived SSC relation equation and the correlation coefficient at 5 mooring stations. 58

Table 9. Model validation of suspended sediment concentration at 5 mooring stations. 62

Table 10. Model validation of spatial suspended sediment concentration at Gyeonggi Bay. 72

Table 11. Net suspended sediment transport at 6 regions during summer and winter in 2020 80

그림목차

Figure 1. Distribution of harbor facilities around the International Ferry Terminal. 19

Figure 2. Schematic diagram of instruments configuration at mooring station. (a) The TRBM from the side view to represent the position of the surface layer and the lower... 21

Figure 3. Study site on Gyeonggi Bay and International Ferry Terminal (IFT), Republic of Korea. (a) The coastline and depth contours (m) relative to the MSL (Mean Sea... 23

Figure 4. Daily discharge rates in 2020, which are model entered. (a) discharge rates at Han river bridge in Han river, (b) discharge rates at... 25

Figure 5. (a) and (b). Distribution of particle size sediment ratio in bottom sediment layers. (a) ratio of sand, (b) ratio of silt (c) ratio of clay 32

Figure 6. Changes in the shear stress and erosion flux from bed according to critical shear stress and erosion rate parameter. (a) Erosion parameter... 38

Figure 7. C1~C10 sediment parameter sensitive test during winter in 2020. The parameter that best reproduces the peak of the suspended sediment... 42

Figure 8. Comparison of tide level between observation (blue dot) and model (red lines) results at ST1-ST8 winter in 2020. 47

Figure 9. Comparison of tide level between observation (blue dot) and model (red lines) results at ST1-ST8 summer in 2020. 48

Figure 10. Comparison of current velocity between Observation (blue line) and model (red line) at M1 mooring station winter in 2020. 49

Figure 11. Comparison of current velocity between Observation (blue line) and model (red line) at M2 mooring station winter in 2020. 49

Figure 12. Comparison of current velocity between Observation (blue line) and model (red line) at M1 mooring station summer in 2020. 50

Figure 13. Comparison of current velocity between Observation (blue line) and model (red line) at M3 mooring station summer in 2020. 50

Figure 14. Comparison of observation (blue line) and model (red line) salinity time series of winter in 2020 (M1, M2 mooring station). 52

Figure 15. comparison of observation (blue line) and model (red line) salinity time series of summer in 2020 (M1, M3 mooring station). 52

Figure 16. The Location of wave buoy deployed around the Gyeonggi-Bay by the Korea Meteorological Agency (KMA). The wave model was... 54

Figure 17. Comparison of significant wave hight between observation (blue line) and model (red line) results at 6 wave buoy during winter in 2020. 55

Figure 18. Comparison of significant wave hight between observation (blue line) and model (red line) results at 6 wave buoy during summer in 2020. 56

Figure 19. The mooring station where the observation SSC data was obtained. (a) Gyeonggi Bay, (b) The Yeongjong island entire area... 58

Figure 20. Linear regression analysis of water sample SSC and turbidity at 5 mooring station. 59

Figure 21. Linear regression analysis of water sample SSC and turbidity at 5 mooring station. (a) M1 mooring station, (b) M2 mooring station, (c)... 62

Figure 22. Comparison of SSC between observation (blue line) and model results (red line) surface and bottom layer at M1 mooring station: (a)... 64

Figure 23. Comparison of SSC between observation (blue line) and model results (red line) surface and bottom layer at M1 mooring station: (a)... 65

Figure 24. Bottom SSC distribution in numerical model. (a) maximum flood tide, (b) high tide, (c) maximum ebb tide, (d) low tide 67

Figure 25. Comparison of SSC between observation (blue line) and model results (red line) surface layer at M3 mooring station: (a) spring tide... 68

Figure 26. Comparison of SSC between observation (blue line) and model (red line) at M4 mooring station: (a) spring tide during in 09/06~09/10 in... 69

Figure 27. Comparison of SSC between observation (blue line) and model (red line) at M5 mooring station: (a) spring tide during in 05/26~05/29 in... 70

Figure 28. Daily variation of SSC from GOCI data at (a) 09:30, (b) 10:30, (c) 11:30, (d) 12:30, (e) 13:30, (f) 14:30 (g) 16:30 (f) 17:30 and... 73

Figure 29. Spatial variation of SSC from GOCI data when ebb tide at (a) 09:30, (b) 10:30, (c) 11:30, (d) 12:30 74

Figure 30. Spatial variation of SSC from model data when ebb tide at (a) 09:30, (b) 10:30, (c) 11:30, (d) 12:30 74

Figure 31. Scheme of define bed thickness. each time step d_net is eroded or deposited from bed layer. lthck is the last thickness of bed layer (a)... 75

Figure 32. Difference between 2019 KHOA bathymatry and 2021 water depth survey. 76

Figure 33. Differences in sedimentation rates calculated from numerical models. Accumulation 2020 summer and winter sediment rate and... 76

Figure 34. Residual current distribution by water layer for the sp1, sp2, sp3, and sp4 cross sections during summer. 80

Figure 35. Net sediment transport at cross section in IFP (a) during winter in 2020 (b) during summer in 2020. The red arrow size indicates the net sediment transport.... 81

Figure 36. Net sediment transport at cross section in IFP during summer in 2020 when reservoir discharge input. The red arrow size indicates the net sediment transport. When... 83

Figure 37. Residual current and SSC distribution cross SP1 cross section during summer in 2020 and summer when reservoir discharge input. When freshwater is discharged... 84

Figure 38. Residual current during winter in 2020. The red arrow represents the residual circulation streamline in IFT. During the winter... 87

Figure 39. Residual current during summer in 2020. The red arrow represents the residual circulation streamline in IFT. During summer season,... 88

Figure 40. A schematic diagram of the five sections of SP1-SP5 at IFP 89

Figure 41. Residual current distribution by water layer for the SP1, SP2, SP3, and SP4 cross sections during winter. 90

Figure 42. Residual current distribution by water layer for the sp1, sp2, sp3, and sp4 cross sections during summer. 92

Figure 43. The distribution of the flow velocity by the intertidal slope in the SP5 during flood tide. (a) Low tide, (b) After 2 hours from low tide. 94

Figure 44. The distribution of the flow velocity by the intertidal slope in the SP5 during ebb tide. (a) High tide, (b) After 2 hours from high tide. 95

초록보기

 반 폐쇄적인 항만 내 퇴적 현상 원인을 분석하기 위하여, 3차원 퇴적물 수송 모델을 신국제 여객터미널 해역에 적용하였다. 수치 모델 모의 기간은 관측 자료 수집 기간인 동계(2020년 1월 20일~3월 20일), 춘계(5월 25일~6월 20일), 하계(8월 25일~9월 25일)이다. 수치 모델 결과의 유속 및 염분은 영종대교, 인천 북항, 남항 총 3개의 정점에서 관측된 표층, 저층의 유속 및 염분 시계열 자료와 비교 검증되었다. 수치 모델 결과의 부유사 농도 시계열에 대한 모델 결과는 5개 정점(영종대교, 인천 북항, 남항 조간대 입구, 북단, 남단)에서 관측된 탁도와 채수된 부유사 농도 사이의 1:1 선형 회귀 식을 사용하여 환산된 부유사 농도와 검증되었으며, 수치모델 결과의 표층 공간 부유사 농도 분포는 천리안해양관측위성의 5번 영역(660 nm)으로 산출된 부유사 농도의 공간 분포와 검증되었다. 퇴적물 모델 파라미터는 Gust Erosion Microcosm System(GEMS) 실험을 통해 산출된 침식률과 침식한계전단응력을 기반으로 민감도 테스트를 수행하여 적합한 수치를 적용하였다. 단면 부유사 수지를 계산하여 신국제 여객터미널 해역에서의 퇴적 현상 원인을 퇴적물 수지에 영향을 미치는 외부적 요인의 2가지(제1항로 유입, 갯골 유입)와 퇴적물 집적에 영향을 미치는 내부적 요인 2가지(조간대 사면 유실, 해수 흐름 정체)로 분석하였다. 신국제 여객터미널로 유입되는 부유사는 주로 서쪽의 제1항로로부터 공급된다. 갯골로부터 유입되는 부유사는 약 1%~10%차지한다. 항 입구에 회전성 흐름의 형태로 나타나는 잔차 흐름은, 흐름 중심부에서 유속 감쇠 현상으로 퇴적물 부유를 제한하고, 퇴적물 침강이 발생하기 유리한 환경을 형성한다. 조간대에서의 사면 유실은 사면에서의 급격한 수심 차이로부터 발생한 강한 유속에 의해 퇴적물이 부유 되고, 고조 이후 낙조류의 흐름에 따라 고농도의 부유사가 항내로 유입되는 프로세스로 나타나며, 신국제 여객터미널 입구부에 퇴적이 되는 주요한 원인 중 하나이다. 따라서, 신국제 여객터미널에서의 퇴적 현상은 제 1항로에서의 유입된 퇴적물이 잔차 흐름에 의해 퇴적되는 현상과 더불어, 조간대의 사면 유실에 의한 영향 또한 퇴적 현상에 지배적인 영향을 미치는 것으로 분석되었다. 인천 항만에서 퇴적 원인을 퇴적물 수송 모델로 분석한 연구가 거의 없는 점을 감안하면, 본 연구에서 제안한 퇴적물 수송 프로세스는 향후 항만 개발의 지리적인 위치 설정과 준설계획을 수립하는 데 도움이 될 것으로 기대된다.