Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China
Study region: The upper reaches of the Hei River Basin, northwest China Study focus: To improve the accuracy and physical consistency of runoff simulations, as well as to compare the applicability of meteorological data obtained from multiple sources, this study integrates physical mechanisms with d...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S221458182400449X |
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| author | Huazhu Xue Yaheng Wang Guotao Dong Chenchen Zhang Yaokang Lian Hui Wu |
| author_facet | Huazhu Xue Yaheng Wang Guotao Dong Chenchen Zhang Yaokang Lian Hui Wu |
| author_sort | Huazhu Xue |
| collection | DOAJ |
| description | Study region: The upper reaches of the Hei River Basin, northwest China Study focus: To improve the accuracy and physical consistency of runoff simulations, as well as to compare the applicability of meteorological data obtained from multiple sources, this study integrates physical mechanisms with deep learning methods to construct a coupled model, HIMS-LSTM. Considering the impact of meteorological data on runoff simulation and prediction, meteorological station observation data, ERA5 data and CFSv2 data were obtained for runoff simulation and prediction. This approach enables the assessment of the applicability of meteorological data obtained from three different sources. New hydrological insights for the region: The HIMS-LSTM model leverages physical mechanisms to compensate for the lack of physical knowledge in data-driven models. Consequently, the accuracy and physical consistency of runoff simulation results are significantly improved compared to the single models HIMS and LSTM. Furthermore, a comparative assessment of simulation results based on multi-source meteorological data demonstrates that daily runoff simulations using meteorological station observation data yield the best results, indicating the highest applicability of this data source. The constructed coupled HIMS-LSTM model provides some insight into the simulation and prediction of daily runoff. Furthermore, this study provides a valuable reference for selecting suitable meteorological data sources for runoff simulation and prediction. |
| format | Article |
| id | doaj-art-12c5a3d32a9d47a69d3883dffc198eaa |
| institution | Kabale University |
| issn | 2214-5818 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Hydrology: Regional Studies |
| spelling | doaj-art-12c5a3d32a9d47a69d3883dffc198eaa2025-01-22T05:42:01ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-02-0157102100Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest ChinaHuazhu Xue0Yaheng Wang1Guotao Dong2Chenchen Zhang3Yaokang Lian4Hui Wu5School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaHeihe Water Resources and Ecological Protection Research Center, Lanzhou 730030, China; Corresponding author.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaHeihe Water Resources and Ecological Protection Research Center, Lanzhou 730030, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaStudy region: The upper reaches of the Hei River Basin, northwest China Study focus: To improve the accuracy and physical consistency of runoff simulations, as well as to compare the applicability of meteorological data obtained from multiple sources, this study integrates physical mechanisms with deep learning methods to construct a coupled model, HIMS-LSTM. Considering the impact of meteorological data on runoff simulation and prediction, meteorological station observation data, ERA5 data and CFSv2 data were obtained for runoff simulation and prediction. This approach enables the assessment of the applicability of meteorological data obtained from three different sources. New hydrological insights for the region: The HIMS-LSTM model leverages physical mechanisms to compensate for the lack of physical knowledge in data-driven models. Consequently, the accuracy and physical consistency of runoff simulation results are significantly improved compared to the single models HIMS and LSTM. Furthermore, a comparative assessment of simulation results based on multi-source meteorological data demonstrates that daily runoff simulations using meteorological station observation data yield the best results, indicating the highest applicability of this data source. The constructed coupled HIMS-LSTM model provides some insight into the simulation and prediction of daily runoff. Furthermore, this study provides a valuable reference for selecting suitable meteorological data sources for runoff simulation and prediction.http://www.sciencedirect.com/science/article/pii/S221458182400449XMulti-source meteorological dataCoupled model HIMS-LSTMDaily runoff simulationApplicability assessment |
| spellingShingle | Huazhu Xue Yaheng Wang Guotao Dong Chenchen Zhang Yaokang Lian Hui Wu Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China Journal of Hydrology: Regional Studies Multi-source meteorological data Coupled model HIMS-LSTM Daily runoff simulation Applicability assessment |
| title | Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China |
| title_full | Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China |
| title_fullStr | Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China |
| title_full_unstemmed | Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China |
| title_short | Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China |
| title_sort | multi source meteorological data assessment on daily runoff simulation in the upper reaches of the hei river northwest china |
| topic | Multi-source meteorological data Coupled model HIMS-LSTM Daily runoff simulation Applicability assessment |
| url | http://www.sciencedirect.com/science/article/pii/S221458182400449X |
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