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Keywords:

  • climate change;
  • glacier melting;
  • streamflow change;
  • artificial neural network

Abstract

There is a growing concern over the effects of climate change on glacier melting and hydrology. In this article, we used a natural large-scale basin, the Niyang River Basin in the Southeast Qinghai–Tibet Plateau, China, to show how climate change accelerates glacier melting and consequently leads to hydrological change. First, nonparametric tests were used to analyse the trends of streamflow, precipitation and temperature since 1979. An artificial neural network was then adopted to construct precipitation-streamflow models. Due to lack of data, 30 climate change scenarios were assumed to simulate streamflow sensitivity to climate change. There were significant increasing trends in streamflow over annual and wet season periods (May–October), whereas insignificant trend on annual precipitation was detected. This, along with a significant decreasing trend of water temperature during the wet season, suggests that climate warming has caused acceleration of glacier melting, which resulted in increased streamflow and summer water cooling. The simulation results indicated that streamflow is very sensitive to climate change, particularly with temperature change. Annual streamflow increased by an average of 65 mm per 0·5 °C temperature increment with precipitation unchanged. Streamflow in the wet season is more sensitive to climate change than in the dry season (November–April). Average streamflow increase per 0·5 °C increment in the wet season was projected to be 59·4 mm for the scenarios with precipitation unchanged. Implications of these results for future water and watershed management were discussed in the context of close linkages among climate change, glacier melting and water resources. Copyright © 2011 John Wiley & Sons, Ltd.