Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin
Accurate runoff simulation plays a very important role in the planning and management of water resources.However,traditional methods have some limitations in the simulation of runoff near peaks and abrupt points.This paper identifies the abrupt change components of rainfall and runoff in the basins...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Pearl River
2021-01-01
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| Series: | Renmin Zhujiang |
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| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2021.06.010 |
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| author | LIU Yiwen LI Jiake DING Qiang HAO Gairui |
| author_facet | LIU Yiwen LI Jiake DING Qiang HAO Gairui |
| author_sort | LIU Yiwen |
| collection | DOAJ |
| description | Accurate runoff simulation plays a very important role in the planning and management of water resources.However,traditional methods have some limitations in the simulation of runoff near peaks and abrupt points.This paper identifies the abrupt change components of rainfall and runoff in the basins above the controlled section of Ankang Hydrological Station in the Hanjiang River Basin through the Mann-Kendall test.analyzes the trend and cycle of the rainfall and runoff by R/S analysis and wavelet analysis,simulates the runoff series with the partial least squares regression (PLSR) and BP neural network-partial least squares regression (BP-PLSR),and analyzes the simulation effect of runoff near peaks and abrupt points.The results show that:The abrupt points of rainfall appear in 1973,1984 and 2002;and those of runoff appear in 1977 and 1985.The Hurst index of rainfall and runoff is close to 0,indicating that there will be an anti-continuous trend in the future.The simulation effect of BP-PLSR on runoff (RMSE=92.863,NSE=0.797) is better than PLSR (RMSE=152.182,NSE=0.456),and preprocessing the original data by BP can better avoid the over-fitting and local optimization near the abrupt points. |
| format | Article |
| id | doaj-art-55e298b5a04f4c6aa7be80dfda417af4 |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2021-01-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-55e298b5a04f4c6aa7be80dfda417af42025-01-15T02:29:43ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352021-01-014247648829Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River BasinLIU YiwenLI JiakeDING QiangHAO GairuiAccurate runoff simulation plays a very important role in the planning and management of water resources.However,traditional methods have some limitations in the simulation of runoff near peaks and abrupt points.This paper identifies the abrupt change components of rainfall and runoff in the basins above the controlled section of Ankang Hydrological Station in the Hanjiang River Basin through the Mann-Kendall test.analyzes the trend and cycle of the rainfall and runoff by R/S analysis and wavelet analysis,simulates the runoff series with the partial least squares regression (PLSR) and BP neural network-partial least squares regression (BP-PLSR),and analyzes the simulation effect of runoff near peaks and abrupt points.The results show that:The abrupt points of rainfall appear in 1973,1984 and 2002;and those of runoff appear in 1977 and 1985.The Hurst index of rainfall and runoff is close to 0,indicating that there will be an anti-continuous trend in the future.The simulation effect of BP-PLSR on runoff (RMSE=92.863,NSE=0.797) is better than PLSR (RMSE=152.182,NSE=0.456),and preprocessing the original data by BP can better avoid the over-fitting and local optimization near the abrupt points.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2021.06.010abrupt recognitiontrend analysispartial least squares regressionBP neural networkHanjiang River Basin |
| spellingShingle | LIU Yiwen LI Jiake DING Qiang HAO Gairui Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin Renmin Zhujiang abrupt recognition trend analysis partial least squares regression BP neural network Hanjiang River Basin |
| title | Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin |
| title_full | Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin |
| title_fullStr | Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin |
| title_full_unstemmed | Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin |
| title_short | Characteristic Analysis and Prediction of Rainfall and Runoff in Ankang Section of Hanjiang River Basin |
| title_sort | characteristic analysis and prediction of rainfall and runoff in ankang section of hanjiang river basin |
| topic | abrupt recognition trend analysis partial least squares regression BP neural network Hanjiang River Basin |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2021.06.010 |
| work_keys_str_mv | AT liuyiwen characteristicanalysisandpredictionofrainfallandrunoffinankangsectionofhanjiangriverbasin AT lijiake characteristicanalysisandpredictionofrainfallandrunoffinankangsectionofhanjiangriverbasin AT dingqiang characteristicanalysisandpredictionofrainfallandrunoffinankangsectionofhanjiangriverbasin AT haogairui characteristicanalysisandpredictionofrainfallandrunoffinankangsectionofhanjiangriverbasin |