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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. [ABSTRACT FROM AUTHOR]

Climate change in North China would result in significant changes in temperature, precipitation and their spatial/temporal distributions. Consequently, these induced changes will have profound effects on the hydrological cycle and water resources in both agricultural and natural ecosystems. Panjiakou reservoir in the middle Luanhe River basin-a tributary of the Haihe River basin-is one of the important sources of water for industrial and agricultural development in Beijing, Tianjin and Hebei province, China. Any significant change in the magnitude and/or timing of runoff from the reservoir induced by changes in climatic variables would have significant implication for the economic prosperity in North China. This paper investigates the impacts of climate change on hydrological processes in the Luanhe River basin as follows. Firstly, spatial and temporal patterns of precipitation, temperature and runoff at both annual and seasonal scales from 1957 to 2000 in the Luanhe River basin are analyzed using Mann-Kendall trend analysis, linear regression methods and inverse distance weighted interpolation. For the impact study, four Global Climate Models (GCMs) (named CSIRO, HadCM3, CNRM and GFDL) were used to produce precipitation and temperature data under A2 scenario by mean of a widely used quantile-quantile transformation. Projected meteorological variables were used to force a two-parameter hydrologic model to simulate the hydrological response to climate change in the future (2021-2050). Moreover, a sensitivity analysis is conducted to assess how precipitation and temperature affect the runoff. Results suggested that most part of the Luanhe River basin was dominated by significant increasing trends of temperature and no significant trends of precipitation in annual and seasonal scale during the past decades. Annual, spring and autumn runoffs present significant decreasing trends in the Panjiakou reservoir basin. Meanwhile, runoff is more strongly related to precipitation than to temperature. All GCMs projected precipitation and temperature series after bias correction indicated increasing temperature and increasing precipitation trends for the period 2021-2050 except that CNRM showed a slight decreasing trend in precipitation. Great enhancements can be found in projected runoff except CNRM by driving the two-parameter water balance model. The study provides valuable information on the assessment of the impact of the climate change on water resources in the Luanhe River basin as well for allocating and designing water resources projects. [ABSTRACT FROM AUTHOR]

Reliable projections of extremes at finer spatial scales are important in assessing the potential impacts of climate change on societal and natural systems, particularly for elevated and cold regions in the Tibetan Plateau. This paper presents future projections of extremes of daily precipitation and temperature, under different future scenarios in the headwater catchment of Yellow River basin over the 21st century, using the statistical downscaling model (SDSM). The results indicate that: (1) although the mean temperature was simulated perfectly, followed by monthly pan evaporation, the skill scores in simulating extreme indices of precipitation are inadequate; (2) The inter-annual variabilities for most extreme indices were underestimated, although the model could reproduce the extreme temperatures well. In fact, the simulation of extreme indices for precipitation and evaporation were not satisfactory in many cases. (3) In future period from 2011 to 2100, increases in the temperature and evaporation indices are projected under a range of climate scenarios, although decreasing mean and maximum precipitation are found in summer during 2020s. The findings of this work will contribute toward a better understanding of future climate changes for this unique region. [ABSTRACT FROM AUTHOR]