Title Page
Contents
國文抄錄 14
Abstract 15
1. Introduction 17
1.1. Research Background 17
1.2. Research Objectives 20
2. Theoretical Backgrounds 21
2.1. Watershed Model - Hydrodynamic and Water Quality Models 21
2.2. Overview of ANN (Artificial Neural Network) 23
2.2.1. Introduction of ANN 23
2.2.2. Governing Equations 25
2.3. Overview of SWAT (Soil and Water Assessment Tool) 28
2.3.1. Introduction of SWAT 28
2.3.2. Hydrology 33
2.3.3. Nutrients 36
2.3.4. Erosion 38
2.3.5. Main Channel Processes 39
3. Field Survey 42
3.1. Study Area 42
3.2. Characteristic of Namgang Dam 44
3.3. Status of Flow Rate and Water Quality in Namgang Dam 46
4. Model Setup 55
4.1. Prediction of Climate Scenarios 55
4.2. Geometry Data 58
4.3. Hydrological, Water Quality and Point Source Data 62
5. Results and Discussions 64
5.1. Results of ANN model 64
5.1.1. ANN Learning Process and Verification Process 64
5.1.2. Trend Analysis of Climate Change Scenario 91
5.1.3. Quantile Mapping 94
5.2. Results of SWAT model 98
5.2.1. Calibration Parameters for SWAT 98
5.2.2. Calibration and Validation of SWAT model 102
5.2.3. Results of SWAT Calibration and Validation 105
5.3. Forecast of Climate Change Scenarios 116
6. Conclusions 127
7. References 129
Table 1. Geomorphological and hydrologic characteristics of Namgang Dam 45
Table 2. Observed data in Namgang Dam 1 51
Table 3. Observed data in Namgang Dam 2 51
Table 4. Observed data in Namgang Dam 3 52
Table 5. AWS characteristics of Namgang Dam watershed 57
Table 6. Hydrologic and water quality data 62
Table 7. Status of WWTPs in Namgang Dam watershed 63
Table 8. Climate parameter of CGCM3.1/T63 or RCM climate change scenarios 65
Table 9. Evaluation indices of ANN model 66
Table 10. Trend analysis for monthly average of prediction parameter 91
Table 11. List of adjusted hydrologic parameters of SWAT 100
Table 12. List of adjusted sediment parameters of SWAT 101
Table 13. List of adjusted water quality parameters of SWAT 102
Table 14. Hydrological and water quality evaluation indices 104
Table 15. Hydrologic statistical results in Sancheong gauging station 108
Table 16. Hydrologic statistical results in Namgang Dam station 108
Table 17. Results of water quality statistical 115
Table 18. Monthly change of Dam-inflow for climate change scenario 118
Table 19. Result of flow duration analysis 119
Table 20. Monthly change of sediment for climate change scenario 121
Table 21. Monthly change of T-N for climate change scenario 124
Table 22. Monthly change of T-P for climate change scenario 126
Fig. 1. Climate change impact on water resources 18
Fig. 2. Conceptual diagram of three-layer neural network model 24
Fig. 3. Land phase of the hydrologic cycle 34
Fig. 4. HRU / Subbasin flow chart 35
Fig. 5. Partitioning of nitrogen in SWAT 37
Fig. 6. Partitioning of phosphorous in SWAT 37
Fig. 7. Study area of Namgang Dam watershed 44
Fig. 8. Correlation of rainfall (2010) 46
Fig. 9. Observed data of water flowrate (2010) 47
Fig. 10. Monitoring point of Namgang Dam (2010) 48
Fig. 11. Observed data of water quality (BOD, SS : 2000~2010) 49
Fig. 12. Observed data of water quality (T-N, T-P : 2000~2010) 50
Fig. 13. Observed data of water quality (BOD, SS : annual average) 53
Fig. 14. Observed data of water quality (T-N, T-P : annual average) 54
Fig. 15. Climate observation stations of study area 57
Fig. 16. Landuse of Namgang Dam watershed 59
Fig. 17. Soil of Namgang Dam watershed 59
Fig. 18. DEM of Namgang Dam watershed 60
Fig. 19. Sub-basin boundary of Namgang Dam watershed 61
Fig. 20. Hydrological and water quality gauging station 63
Fig. 21. Result of ANN learning process(precipitation) 67
Fig. 22. Result of ANN learning process(precipitation) 68
Fig. 23. Result of ANN learning process(precipitation) 69
Fig. 24. Result of ANN learning process(humidity) 70
Fig. 25. Result of ANN learning process(humidity) 71
Fig. 26. Result of ANN learning process(humidity) 72
Fig. 27. Result of ANN learning process(maximum temperature) 73
Fig. 28. Result of ANN learning process(maximum temperature) 74
Fig. 29. Result of ANN learning process(maximum temperature) 75
Fig. 30. Result of ANN learning process(minimum temperature) 76
Fig. 31. Result of ANN learning process(minimum temperature) 77
Fig. 32. Result of ANN learning process(minimum temperature) 78
Fig. 33. Result of ANN verification process(precipitation) 79
Fig. 34. Result of ANN verification process(precipitation) 80
Fig. 35. Result of ANN verification process(precipitation) 81
Fig. 36. Result of ANN verification process(humidity) 82
Fig. 37. Result of ANN verification process(humidity) 83
Fig. 38. Result of ANN verification process(humidity) 84
Fig. 39. Result of ANN verification process(maximum temperature) 85
Fig. 40. Result of ANN verification process(maximum temperature) 86
Fig. 41. Result of ANN verification process(maximum temperature) 87
Fig. 42. Result of ANN verification process(minimum temperature) 88
Fig. 43. Result of ANN verification process(minimum temperature) 89
Fig. 44. Result of ANN verification process(minimum temperature) 90
Fig. 45. Trend analysis for monthly average of prediction parameter 92
Fig. 46. Monthly trend analysis of prediction parameter 93
Fig. 47. Seasonal trend analysis of prediction parameter 94
Fig. 48. Example of quantile mapping method 95
Fig. 49. Comparison of RCM, ANN and ANN+QM precipitation 96
Fig. 50. Result of RCM precipitation 96
Fig. 51. Result of ANN precipitation 97
Fig. 52. Result of ANN+QM precipitation 97
Fig. 53. Simulation section of hydrologic 106
Fig. 54. Runoff in Sancheong gauging station: (a) Calibration, (b) Validation 107
Fig. 55. Runoff in Namgang Dam station: (a) Calibration, (b) Validation 107
Fig. 56. A scatter plot between observed and simulated daily runoff flow at... 109
Fig. 57. A scatter plot between observed and simulated daily runoff flow at... 109
Fig. 58. Simulation section of water quality 111
Fig. 59. Water quality(Sediment) in Gyeongho river2 gauging station:... 112
Fig. 60. Water quality(T-N) in Gyeongho river2 gauging station:... 112
Fig. 61. Water quality(T-P) in Gyeongho river2 gauging station:... 113
Fig. 62. Water quality(Sediment) in Deokcheon river2 gauging station:... 114
Fig. 63. Water quality(T-N) in Deokcheon river2 gauging station:... 114
Fig. 64. Water quality(T-P) in Deokcheon river2 gauging station:... 115
Fig. 65. Monthly change of Dam-inflow for climate change scenario 117
Fig. 66. Monthly change of Dam-inflow 117
Fig. 67. Flow duration analysis for climate change scenario 119
Fig. 68. Monthly change of sediment for climate change scenario 120
Fig. 69. Monthly change of sediment 121
Fig. 70. Change of sediment 122
Fig. 71. Monthly change of T-N for climate change scenario 123
Fig. 72. Monthly change of T-N 123
Fig. 73. Change of T-N 124
Fig. 74. Monthly change of T-P for climate change scenario 125
Fig. 75. Monthly change of T-P 125
Fig. 76. Change of T-P 126