Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data
3. Method
3.1. Mann–Kendall Test
3.2. IHA Method
3.3. Revised Reservoir Operation Scheme
- (a)
- Limitation of water storage capacity:
- (b)
- Limitation of outflow:
4. Results
4.1. Performance of the Revised Reservoir Operation Scheme in the SWAT Model
4.2. Alteration of Flow Regimes
4.3. Reservoir-Induced Hydrological Alteration
5. Discussion
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | Station Name | Longitude (°) | Latitude (°) | Period | Time Step |
---|---|---|---|---|---|
1 | Yichang | 111.28 | 30.7 | 1960–2017 | Daily |
2 | Zhutuo | 105.85 | 29.02 | 1971–1986, 2007–2017 | Daily |
3 | Cuntan | 106.6 | 29.62 | 1960–1986, 1993–2017 | Daily |
4 | Huadan | 102.88 | 26.92 | 1977–1987, 2007–2014 | Daily |
5 | Pingshan | 104.17 | 28.63 | 1977–1987, 2007–2011 | Daily |
6 | Wudongde | 102.6 | 26.28 | 2012–2017 | Daily |
7 | Xiangjiaba | 104.4 | 28.63 | 2012–2017 | Daily |
8 | Baihetan | 102.88 | 27.27 | 2015–2017 | Daily |
9 | Shigu | 99.93 | 26.9 | 2007–2015 | Daily |
10 | Jinjiangjie | 100.55 | 26.23 | 1987, 2010 | Daily |
11 | Panzhihua | 101.72 | 26.58 | 2006–2015 | Daily |
12 | Ahai | 100.5 | 27.35 | 2012–2015 | Daily |
13 | Jin’anqiao | 100.43 | 26.8 | 2012–2015 | Daily |
14 | Zhongjiang | 100.42 | 26.5 | 2012–2015 | Daily |
15 | Tingzikou | 105.82 | 31.85 | 1969–1983, 2007–2012 | Daily |
16 | Langzhong | 105.97 | 31.57 | 2007–2017 | Daily |
17 | Wusheng | 106.27 | 30.27 | 1965–1983, 2007–2017 | Daily |
18 | Beibei | 106.47 | 29.82 | 1975–1983, 2007–2017 | Daily |
19 | Wudu | 104.92 | 33.38 | 1965–1983, 2007–2017 | Daily |
20 | Bikou | 105.25 | 32.75 | 1965–1983, 2007–2017 | Daily |
21 | Sanleiba | 105.65 | 32.42 | 1975–1983, 2007–2017 | Daily |
22 | Zhenjiangguan | 103.73 | 32.3 | 1960–1983, 2007–2017 | Daily |
23 | Pengshan | 103.88 | 30.2 | 1960–1983, 2007–2017 | Daily |
24 | Gaochang | 104.42 | 28.8 | 1960–1983, 2007–2017 | Daily |
25 | Jiangsheba | 103.58 | 31.48 | 1960–1983, 2012–2017 | Daily |
26 | Zipingpu | 103.57 | 30.98 | 1976–1983 | Daily |
27 | Shimian | 102.37 | 29.25 | 1960–1976, 2008–2017 | Daily |
28 | Shawan | 103.55 | 29.4 | 2010–2017 | Daily |
29 | Huning | 101.87 | 28.45 | 1967–1987, 2007–2017 | Daily |
30 | Tongzilin | 101.85 | 26.68 | 2007–2017 | Daily |
31 | Wali | 101.57 | 28.1 | 1972–1987 | Daily |
32 | Xiaodeshi | 101.83 | 26.75 | 1967–1987 | Daily |
33 | Wujiangdu | 106.78 | 27.3 | 1965–1983, 2006–2017 | Daily |
34 | Goupitan | 107.68 | 27.4 | 2006–2017 | Daily |
35 | Sinan | 108.25 | 27.95 | 1965–1983, 2006–2017 | Daily |
36 | Yanhe | 108.47 | 28.55 | 2006–2017 | Daily |
37 | Longtan | 108.35 | 28.92 | 1965–1983, 2006–2007 | Daily |
38 | Pengshui | 108.17 | 29.28 | 2006–2017 | Daily |
39 | Wulong | 107.75 | 29.32 | 1965–1983, 2006–2017 | Daily |
No. | Groups | Hydrological Signatures | Abbreviation | Unit |
---|---|---|---|---|
1 | Group1: Magnitude | Mean daily streamflow | MDF | m3s−1 |
2 | Mean daily streamflow in the flood season (April–September) | NDFF | m3s−1 | |
3 | Mean daily streamflow in the pre-nonflood season (January–March) | MDFN1 | m3s−1 | |
4 | Mean daily streamflow in the post-nonflood season (October–December) | MDFN2 | m3s−1 | |
5 | Group2: Variability and Frequency | Coefficient of variation (CV) of the mean daily streamflow | CVDF | – |
6 | CV of mean daily streamflow in the flood season | CVDFF | – | |
7 | CV of mean daily streamflow in the pre-nonflood season | CVDFN1 | – | |
8 | CV of mean daily streamflow in the post-nonflood season | CVDFN2 | – | |
9 | Low flow spell count (75th percentile of MDF) | FDF75 | – | |
10 | Extremely low flow spell count (90th percentile of MDF) | FDF90 | – | |
11 | High flow spell count (25th percentile of MDF) | FDF25 | – | |
12 | Extremely high flow spell count (10th percentile of MDF) | FDF10 | – | |
13 | Group3: Duration | Low flow spell duration | DDF75 | days |
14 | Extremely low flow spell duration | DDF90 | days | |
15 | High flow spell duration | DDF25 | days | |
16 | Extremely high flow spell duration | DDF10 | days | |
17 | Group4: Timing | Colwell’s constancy of the mean daily streamflow | TDFC | – |
18 | Julian date of the annual minimum daily streamflow | TMnDF | – | |
19 | Julian date of the annual maximum daily streamflow | TMxDF | – | |
20 | Group5: Rates of Change | Mean rate of positive changes in flow from one day to the next | RR | – |
21 | Mean rate of negative changes in flow from one day to the next | RF | – |
No. | Name | Flood Season | Flood Prevention Storage (108 m3) | α | β | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
e | f | g | h | e | f | g | h | ||||
1 | Liyuan | 7.1–7.31 | 1.73 | −1.74 | 5.67 | −6.30 | 3.36 | −0.45 | 1.18 | −1.05 | 1.33 |
2 | Ahai | 7.1–7.31 | 2.15 | −0.40 | 1.02 | −0.92 | 1.30 | −0.52 | 1.44 | −1.46 | 1.54 |
3 | Jinanqiao | 7.1–7.31 | 1.58 | −1.43 | 4.77 | −5.42 | 3.07 | −0.49 | 1.29 | −1.19 | 1.39 |
4 | Longkaikou | 7.1–7.31 | 1.26 | −1.49 | 4.73 | −5.19 | 2.91 | −0.44 | 1.08 | −0.94 | 1.30 |
5 | Ludila | 7.1–7.31 | 5.64 | −1.49 | 5.15 | −5.99 | 3.32 | −0.17 | 0.55 | −0.70 | 1.31 |
6 | Guanyinyan | 7.1–7.31 | 5.42 | −2.06 | 6.80 | −7.59 | 3.85 | −0.03 | −0.15 | 0.08 | 1.09 |
7 | Ertan | 7.1–8.31 | 9 | −12.77 | 39.85 | −41.75 | 15.67 | −0.05 | 0.23 | −0.36 | 1.18 |
8 | Jinpingyiji | 7.1–8.31 | 16 | −2.59 | 7.23 | −6.83 | 3.21 | −0.10 | 0.36 | −0.47 | 1.21 |
9 | Pubugou | 7.1–9.30 | 11/7.27 | −0.37 | 1.29 | −1.57 | 1.65 | −0.51 | 1.53 | −1.65 | 1.63 |
10 | Zipingpu | 6.1–9.30 | 1.67 | −0.31 | 0.99 | −1.12 | 1.44 | −0.06 | 0.25 | −0.37 | 1.17 |
11 | Bikou | 5.1–9.30 | 0.5/0.7 | −0.02 | 0.11 | −0.20 | 1.11 | −0.01 | 0.05 | −0.16 | 1.12 |
12 | Baozhusi | 7.1–9.30 | 2.8 | −0.03 | 0.17 | −0.32 | 1.18 | −0.02 | 0.11 | −0.20 | 1.12 |
13 | Tingzikou | 6.21–8.31 | 14.4 | −0.39 | 1.46 | −1.89 | 1.82 | −0.30 | 0.76 | −0.66 | 1.19 |
14 | Caojie | 6.1–8.31 | 1.99 | −1.44 | 4.20 | −4.16 | 2.40 | −0.03 | 0.20 | −0.53 | 1.38 |
15 | Goupitan | 6.1–8.31 | 4/2 | −0.04 | 0.23 | −0.42 | 1.22 | −0.09 | 0.30 | −0.35 | 1.14 |
16 | Silin | 6.1–8.31 | 1.84 | −1.47 | 4.73 | −5.19 | 2.93 | 0.02 | −0.03 | −0.22 | 1.24 |
17 | Shatuo | 6.1–8.31 | 2.09 | −1.27 | 4.02 | −4.27 | 2.51 | −0.08 | 0.12 | −0.20 | 1.14 |
18 | Pengshui | 5.21–8.31 | 2.32 | −0.70 | 2.24 | −2.47 | 1.93 | 0.07 | −0.25 | −0.04 | 1.23 |
19 | Xiluodu | 7.1–9.10 | 46.5 | −35.90 | 110.49 | −113.69 | 40.11 | 0.07 | −0.28 | −0.11 | 1.20 |
20 | Xiangjiaba | 7.1–9.10 | 9.03 | −3.69 | 12.56 | −14.38 | 6.51 | −0.47 | 0.98 | −0.98 | 1.44 |
21 | Sanxia (TGR) | 6.10–8.24 | 221.5 | −3.21 | 9.60 | −9.74 | 4.35 | −1.12 | 3.65 | −4.04 | 2.52 |
Station | Calibration | Validation (Original) | Validation (Revised) | |||
---|---|---|---|---|---|---|
NSE | KGE | NSE | KGE | NSE | KGE | |
Cuntan | 0.95 | 0.95 | 0.92 | 0.96 | 0.92 | 0.95 |
Yichang | 0.96 | 0.97 | 0.81 | 0.90 | 0.85 | 0.92 |
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Liu, H.; Wang, T.; Feng, Y.; Liu, F.; Wang, N.; Wang, H.; Liu, W.; Sun, F. Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches. Water 2023, 15, 2914. https://doi.org/10.3390/w15162914
Liu H, Wang T, Feng Y, Liu F, Wang N, Wang H, Liu W, Sun F. Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches. Water. 2023; 15(16):2914. https://doi.org/10.3390/w15162914
Chicago/Turabian StyleLiu, Hanqi, Tingting Wang, Yao Feng, Fa Liu, Ning Wang, Hong Wang, Wenbin Liu, and Fubao Sun. 2023. "Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches" Water 15, no. 16: 2914. https://doi.org/10.3390/w15162914
APA StyleLiu, H., Wang, T., Feng, Y., Liu, F., Wang, N., Wang, H., Liu, W., & Sun, F. (2023). Identifying Reservoir-Induced Hydrological Alterations in the Upper Yangtze River Basin through Statistical and Modeling Approaches. Water, 15(16), 2914. https://doi.org/10.3390/w15162914