Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China
文献类型：SCI/SSCI论文
| 作者 | Jiang Y. ; Liu C. M. ; Zheng H. X. ; Li X. Y. ; Wu X. N. |
| 发表日期 | 2010 |
| 关键词 | river runoff runoff forecast nonlinear mixed regression model linear multi-regression model linear mixed regression model BP neural network bone |
| 英文摘要 | 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. |
| 出处 | Chinese Geographical Science |
| 卷 | 20 |
| 期 | 2 |
| 页 | 152-158 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1002-0063 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/23745]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Jiang Y.,Liu C. M.,Zheng H. X.,et al. Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China. 2010. |
入库方式： OAI收割
来源：地理科学与资源研究所
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