Runoff sensitivity to climate changes in the Longitudinal Range-Gorge Region （LRGR）： An example of the Longchuan Basin in the Upper Yangtze

作     者：ZHU Yunmei LU Xixi ZHOU Yue LIONG Shie-Yui 

作者机构：Department of Environmental Science Kunming University of Science & Technology Kunming 650093 China Department of Geography National University of Singapore 119260 Singapore Institute of Tropical Marine Science National University of Singapore 119260 Singapore 

出 版 物：《Chinese Science Bulletin》 (中国科学通报)

年 卷 期：2006年第51卷第B11期

页      面：88-96页

核心收录：

学科分类：08[工学] 081501[工学-水文学及水资源] 0815[工学-水利工程] 

主　　题：径流 气候变化 人工神经网络 中国西南部 水文学 

摘      要：The sensitivity of runoff to the climate change in the Longitudinal Range-Gorge Region (LRGR) in southwest China was investigated with a case study in the Longchuan Basin of the upper Yangtze River, where the climate change is more complex due to the influences from both global warming and local topography. Non-updating artificial neural networks were calibrated and validated at the baseline condition and were used to predict the response of runoff under 25 hypothetical climate scenarios, which were generated by adjusting the baseline temperature by -1, 0, 1, 2 and 3 degrees C and by scaling rainfall by 0%, +/-+/- 10% and +/- 20%. The results indicated that runoff is more sensitive to the increase in rainfall. The annual and seasonal runoff changes were determined by the interaction between temperature and rainfall. At seasonal scale, the direction of change in runoff is more determined by temperature in winter and spring; whereas it is more determined by rainfall in summer and autumn. The LRGR in southwest China may experience a higher frequency of floods in the wet season and more serious droughts in the dry season, if a wetter summer and warmer winter is the trend of future climate change, as predicted by many GCMs.