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Impacts of climate change under CMIP5 RCP scenarios on streamflow in the Huangnizhuang catchment

Author:
Ouyang, Fen, Zhu, Yonghua, Fu, Guobin, Lü, Haishen, Zhang, Aijing, Yu, Zhongbo, Chen, Xi
Source:
Stochastic environmental research and risk assessment 2015 v.29 no.7 pp. 1781-1795
ISSN:
1436-3240
Subject:
Soil and Water Assessment Tool model, air temperature, basins, climate change, climate models, emissions, evapotranspiration, methodology, planning, stream flow, water management, watersheds, China
Abstract:
Six global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 under three Respectively Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) were used to assess the impact of climate change on streamflow for the Huangnizhuang catchment (HNZ) in China. Change factor method was used for bias correction between GCM outputs and observations and the SWAT model was used to simulate the hydrological processes. The results indicated that the SWAT model performed well in the study catchment with a monthly Nash–Sutcliffe efficiency (NS) of 0.93 and 0.91 and daily NS of 0.63 and 0.68 for calibration and validation periods respectively. Their corresponding relative errors were −2.2 and 8.9, and −2.6 and 8.5 % respectively. The ensemble of multi-GCMs projected an increase of precipitation in the middle and end of twenty-first century over the HNZ, ranging from −2.4 to 9 %. However, streamflow is likely to decline in the future, ranging −6.9 to 0.8 %, mainly due to an increase of evapotranspiration in a warming world, as air temperature shows steadily increases for all the GCMs and RCPs. Average monthly streamflow from six GCMs are likely to increase in August and September but decline from October to June. The associated uncertainties of the reported results were also discussed. It includes, but is not limit to, different GCMs, emissions scenarios, downscaling techniques as well as hydrological simulations. The results of this study can inform planning of long-term basin water management strategies taking into account global change scenarios.
Agid:
4389811