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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #326994

Research Project: Quantifying and Monitoring Nutrient Cycling, Carbon Dynamics and Soil Productivity at Field, Watershed and Regional Scales

Location: Hydrology and Remote Sensing Laboratory

Title: Assessment on the effect of climate change on streamflow in the source region of the Yangtze river, China

item BIAN, HUANQING - Hohai University
item LU, HAISHEN - Hohai University
item Sadeghi, Ali
item ZHU, YONGHUA - Hohai University
item YU, ZHONGBO - Hohai University
item OUYANG, FEN - Hohai University
item SU, JIANBIN - Hohai University

Submitted to: Water
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/20/2016
Publication Date: 1/23/2017
Citation: Bian, H., Lu, H., Sadeghi, A.M., Zhu, Y., Yu, Z., Ouyang, F., Su, J. 2017. Impact of climate change on the streamflow hydrology of the Yangtze River in China. Water. 9(1):70.

Interpretive Summary: Impact of climate change on regional water resources is of a great importance. In China, for example, the Tibetan Plateau, also known as the “Water Tower” of Asia, is one of the most sensitive areas vulnerable to the impacts of the climate change, especially being also influenced by the unique Asian climatic conditions. Thus, the projections of the future hydrological changes and water resources availability are quite important for future water resource management planning in this area. In this study, six GCMs (Global Climate Models) and three pathway scenarios were applied to simulate the future impacts of climate change for the 2020s, 2050s, and 2080s periods. A hydrological model was also applied to evaluate the effects of climate change on the future streamflow hydrology. Simulated future projections showed increases in both temperature and precipitation. Annual mean temperature and precipitation changes ranged from 0.66' to 6.68' and 1.18 to 66.14%. Also, the model scenarios indicated that the streamflow in this area will likely increase due to the increase in precipitation and the expected annual mean streamflow changes will range from -0.52 to 22.58%. These findings reveal that the future climate of the Tuotuo River basin will be wetter and warmer and, as the Tibetan Plateau is a special geographical location, we suggest that the future studies should also focus more on the effects of climate change on the snow amounts and glacier melting intensities as well as their contributions to the annual streamflow hydrology.

Technical Abstract: Tuotuo River basin, the source region of the Yangtze River, is the key area, where the impact of climate change has been observed on many of the hydrological processes of this central region of the Tibetan Plateau. In this study, we examined six global climate models (GCMs) under three Respectively Concentration Pathways (RCPs) scenarios, with the Coupled Model Inter-comparison Project Phase 5 (CMIP5). This modeling approach was used to evaluate the climate variability impacts on the hydrology of the stream network within the Tuotuo River basin. First, the already impacted climate change on stream hydrology was analyzed, based on the historical data available and then, the simulation results of the GCMs and RCPs were used for future scenario assessments. Results indicated that the annual mean temperature will likely be increased, ranging from -0.34' to 6.68' during the three future prediction periods (2020s, 2050s, and 2080s), while the change in the expected annual precipitation ranged from 1.18% to 57.78%, compared to the existing level. Then, a well-known distributed hydrological soil vegetation model (DHSVM) was also utilized to investigate the impacts of climate change on the future streamflow dynamics. The DHSVM simulation results showed an accepted performance with a Nash Efficiency Coefficient (NSE) of 0.79 and 0.84 for the calibration and the validation periods, respectively. The annual mean streamflows, predicted by the six GCMs and the three RCPs scenarios, were also shown to likely increased during the May to October months, ranging from -0.52% to 22.58%. Furthermore, the uncertainties of the model used in this study were also examined. The results showed that the main sources of the uncertainties were associated with the different kinds of GCMs used, the three RCPs scenarios investigated, the downscaling method used, and the hydrological model simulations. However, among the factors evaluated, the selection of the GCMs appeared to be the most important contributing source of the uncertainty that most likely impacted the outcome results of this assessment.