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Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China

JIANG Yan LIU Changming ZHENG Hongxing LI Xuyong WU Xianing

JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. 中国地理科学, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
引用本文: JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. 中国地理科学, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. Chinese Geographical Science, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
Citation: JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. Chinese Geographical Science, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7

Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China

doi: 10.1007/s11769-010-0152-7
基金项目: Under the auspices of National Natural Science Foundation of China (No. 50809004)
详细信息
    通讯作者:

    JIANG Yan.E-mail:lirenjy@sohu.com;yanjiang@rcees.ac.cn

Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China

Funds: Under the auspices of National Natural Science Foundation of China (No. 50809004)
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  • 被引次数: 0
出版历程
  • 收稿日期:  2009-03-09
  • 修回日期:  2009-10-09
  • 刊出日期:  2010-01-22

Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China

doi: 10.1007/s11769-010-0152-7
    基金项目:  Under the auspices of National Natural Science Foundation of China (No. 50809004)
    通讯作者: JIANG Yan.E-mail:lirenjy@sohu.com;yanjiang@rcees.ac.cn

摘要: Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956-2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well.

English Abstract

JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. 中国地理科学, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
引用本文: JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. 中国地理科学, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. Chinese Geographical Science, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
Citation: JIANG Yan, LIU Changming, ZHENG Hongxing, LI Xuyong, WU Xianing. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China[J]. Chinese Geographical Science, 2010, 20(2): 152-158. doi: 10.1007/s11769-010-0152-7
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