Multi-temporal scale modeling on climatic-hydrological processes in data-scarce mountain basins of Northwest China |
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| Authors: | Jianhua Xu Chong Wang Weihong Li Jingping Zuo |
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| Institution: | 1.Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences,East China Normal University,Shanghai,China;2.Research Center for East-West Cooperation in China,East China Normal University,Shanghai,China;3.School of Social Sciences,Shanghai University of Engineering Science,Shanghai,China;4.State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi,China |
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| Abstract: | Previous studies showed that the climatic processes drive the streamflow of the inland river in Northwest China. However, it is difficult to quantitatively assess the climatic-hydrological processes in the ungauged mountainous basins because of the scarce data. This research developed an integrated approach for multi-temporal scale modeling the climatic-hydrological processes in data-scarce mountain basins of Northwest China by combining downscaling method (DM), backpropagation artificial neural network (BPANN), and wavelet regression (WR). To validate the approach, we also simulated the climatic-hydrological processes at different temporal scales in a typical data-scarce mountain basin, the Kaidu River Basin in Northwest China. The main results are as follows: (i) the streamflow is related with regional climatic change as well as atmosphere-ocean variability, (ii) the BPANN model well simulated the nonlinear relationship between the streamflow and temperature and precipitation at the monthly temporal scale, and (iii) although the annual runoff (AR) appears to have fluctuations, there are significant correlations among AR, annual average temperature (AAT), annual precipitation (AP), and oscillation indices, which can be simulated by equations of WR at different temporal scales of years. |
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