Projected impacts of climate change on major dams in the Upper Yangtze River Basin

2022 ◽  
Vol 170 (1-2) ◽  
Author(s):  
Pengcheng Qin ◽  
Hongmei Xu ◽  
Min Liu ◽  
Lüliu Liu ◽  
Chan Xiao ◽  
...  
2016 ◽  
Vol 141 (3) ◽  
pp. 533-546 ◽  
Author(s):  
Buda Su ◽  
Jinlong Huang ◽  
Xiaofan Zeng ◽  
Chao Gao ◽  
Tong Jiang

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yuqian Wang ◽  
Xiaoli Yang ◽  
Mengru Zhang ◽  
Linqi Zhang ◽  
Xiaohan Yu ◽  
...  

Climate change directly impacts the hydrological cycle via increasing temperatures and seasonal precipitation shifts, which are variable at local scales. The water resources of the Upper Yangtze River Basin (UYRB) account for almost 40% and 15% of all water resources used in the Yangtze Basin and China, respectively. Future climate change and the possible responses of surface runoff in this region are urgent issues for China’s water security and sustainable socioeconomic development. This study evaluated the potential impacts of future climate change on the hydrological regimes (high flow (Q5), low flow (Q95), and mean annual runoff (MAR)) of the UYRB using global climate models (GCMs) and a variable infiltration capacity (VIC) model. We used the eight bias-corrected GCM outputs from Phase 5 of the Coupled Model Intercomparison Project (CMIP5) to examine the effects of climate change under two future representative concentration pathways (RCP4.5 and RCP8.5). The direct variance method was adopted to analyze the contributions of precipitation and temperature to future Q5, Q95, and MAR. The results showed that the equidistant cumulative distribution function (EDCDF) can considerably reduce biases in the temperature and precipitation fields of CMIP5 models and that the EDCDF captured the extreme values and spatial pattern of the climate fields. Relative to the baseline period (1961–1990), precipitation is projected to slightly increase in the future, while temperature is projected to considerably increase. Furthermore, Q5, Q95, and MAR are projected to decrease. The projected decreases in the median value of Q95 were 21.08% to 24.88% and 16.05% to 26.70% under RCP4.5 and RCP8.5, respectively; these decreases were larger than those of MAR and Q5. Temperature increases accounted for more than 99% of the projected changes, whereas precipitation had limited projected effects on Q95 and MAR. These results indicate the drought risk over the UYRB will increase considerably in the future.


2019 ◽  
Vol 11 (19) ◽  
pp. 5300
Author(s):  
Pei Xu ◽  
Yingman Guo ◽  
Bin Fu

Water retention is an important factor in ecosystem services, owing to its relationships with climate and land-cover change; however, quantifying the independent and combined impacts of these variables remains a challenge. We use scenario analysis and the InVEST model to assess individual or combined impacts of climate and land cover on water retention in the Upper Yangtze River Basin. Water retention decreased from 1986 to 2015 at a rate of 2.97 mm/10a in response to increasing precipitation (3.94 mm/10a) and potential evapotranspiration (16.47 mm/10a). The rate of water retention change showed regional variability (from 68 to −18 mm/a), with some eastern regions experiencing an increase and most other regions experiencing a decrease. Farmland showed the highest decrease (10,772 km2), with land mainly converted into forest (58.17%) and shrub land (21.13%) from 2000 to 2015. The impact of climate change (−12.02 mm) on water retention generally was greater than the impact of land cover change (−4.14 mm), at the basin scale. Among 22 climate zones, 77.27% primarily were impacted by climate change; 22.73% primarily were impacted by land cover change. Our results demonstrate that both individualistic and integrated approaches toward climate and vegetation management is necessary to mitigate the impacts of climate change on water resources.


2013 ◽  
Vol 10 (5) ◽  
pp. 866-872 ◽  
Author(s):  
Xiao-guo Wang ◽  
Bo Zhu ◽  
Ke-ke Hua ◽  
Yong Luo ◽  
Jian Zhang ◽  
...  

2013 ◽  
Vol 43 (2) ◽  
pp. 163-165 ◽  
Author(s):  
Jinming Wu ◽  
Lei Li ◽  
Hao Du ◽  
Hui Zhang ◽  
Chengyou Wang ◽  
...  

2011 ◽  
Vol 27 (1) ◽  
pp. 59-75 ◽  
Author(s):  
Yongfeng He ◽  
Jianwei Wang ◽  
Sovan Lek ◽  
Wenxuan Cao ◽  
Sithan Lek-Ang

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