표제지

목차

Abstract 6

Abbreviations 12

I. 서론 13

1.1. 연구배경 및 필요성 13

1.2. 연구 목적 15

II. 문헌고찰 16

2.1. 기후변화가 수자원에 미치는 영향 16

2.2. 기후변화 전망 과정의 불확실성 18

III. 연구방법 20

3.1. 연구 대상 지역 20

3.2. 모델 구성 절차 22

3.3. 저수지 수리·수질 예측 모델 구축 27

3.3.1. CE-QUAL-W2모델 27

3.3.2. 수치격자 구성 32

3.3.3. 모델 보정 입력자료 구성 34

3.3.4. 기후변화 전망 입력자료 구성 36

3.3.5. 탁수 해석 모델 구축 37

3.4. 저수지 수온성층 특성 평가 38

3.5. 모델의 적합성 평가 39

3.6. 미래 수온 전망 불확실성의 정량화 40

IV. 연구 결과 및 고찰 42

4.1. 저수지 수온 예측모델 보정 결과 42

4.2. 미래 강우량 및 소양호 유입량 45

4.3. 소양호 미래 대기온 변화 전망 47

4.4. 소양호 미래 수온 변화 전망 48

4.5. 소양호 미래 수온의 계절별 전망 53

4.6. 수체의 안정도 변화 56

4.7. 탁수 거동 예측 58

4.8. 불확실성의 정량화 64

V. 결론 67

참고문헌 69

Table 3.1. GCM models used to forecast future water temperature in Soyanggang Reservoir 23

Table 3.2. Key parameters related to water temperature simulations using W2 model 30

Table 3.3. Key parameters related to SS simulations in W2 model 31

Table 3.4. Diameter, sedimentation rate and fraction by suspended solids group 37

Table 3.5. Statistical indices used to evaluate the model accuracy 39

Table 3.6. Scenarios that correspond to the modeling stage 41

Table 4.1. Average water temperature at upper layer for each scenario 50

Table 4.2. Average water temperature at lower layer for each scenario 51

Table 4.3. Annual rising rate of air temperature and upper and lower layer water temperature by scenario and ratio of upper and lower layer water temperature to... 52

Table 4.4. Monthly average water temperature at upper layer for each scenario 54

Table 4.5. Monthly average water temperature at lower layer for each scenario 55

Table 4.6. Monthly average air temperature 55

Table 4.7. Period average number of days of stratification 57

Table 4.8. Uncertainty quantification for each modeling stage 66

Table 4.9. Uncertainty quantification for each scenario 66

Fig. 3.1. Location of the study area and research point 21

Fig. 3.2. Flowchart of modeling processes used in this study 26

Fig. 3.3. Numerical grid structure of Soyanggang Reservoir 32

Fig. 3.4. Comparison of simulated reservoir water level and capacity curve with observed one 33

Fig. 4.1. Comparison of observed and simulated (a) water temperature and (b) water level 43

Fig. 4.2. Comparison of observed and simulated water temperature profiles (2007) 44

Fig. 4.3. Future projected Chuncheon rainfall and Soyanggang Reservoir inflows by RCP scenarios and GCMs 46

Fig. 4.4. Comparison of the annual mean air temperature for the projection period due to future climate change with the annual mean air temperature... 47

Fig. 4.5. Historical (2005 ~ 2015) and projected(2016-2070) yearly water temperature at upper and lower layers in Soyanggang Reservoir 49

Fig. 4.6. Comparison between historical(2005 ~ 2015) and projected(2016 ~ 2070) monthly average air temperature, upper layer water temperature and lower... 54

Fig. 4.7. Annual averaged Schmidt-stability for each scenario of (a) RCP 4.5 and (b) RCP 8.5 56

Fig. 4.8. Number of stratification formation days of (a) RCP 4.5 and (b) RCP 8.5 57

Fig. 4.9. Maximum concentration and duration of turbid water discharge at RCP 4.5, rainfall, and daily inflow for the turbid water inflow (top 5 scenarios) 59

Fig. 4.10. Maximum concentration and duration of turbid water discharge at RCP 8.5, rainfall, and daily inflow for the turbid water inflow (top 5 scenarios) 60

Fig. 4.11. Comparison of the largest turbidity event in the past(2006) and the longest turbidity(2023-2025) among turbidity scenarios 62

Fig. 4.12. RCP 4.5 CCSM4 model extreme turbidity reproduction: maximum concentration 382.90 ㎎/L, duration 356 days (2033-09-17 ~ 2034-09-08) 63

Fig. 4.13. Projected upper water temperatures in Soyanggang Reservoir based on (a) RCP scenarios, (b) wind speed scenarios in W2, and (c) GCM models 65