Climate Change Data Portal
| DOI | 10.1016/j.jhydrol.2024.130941 |
| Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting - A case study on the Lancang-Mekong mainstream | |
| 发表日期 | 2024 |
| ISSN | 0022-1694 |
| EISSN | 1879-2707 |
| 起始页码 | 633 |
| 卷号 | 633 |
| 英文摘要 | In the context of climate change and human influence, timely and reliable information about water level variations is crucial for downstream flood control, navigation, and water resource management, particularly for the Lancang-Mekong River, the largest transboundary river in Southeast Asia. However, accurate real-time water level forecasts remain challenging, especially in data -limited regions. This study focused on the Chiang Saen Station, the uppermost Mekong River hydrological station, comparing three methods to predict 48 -hour water levels: the Variable Infiltration Capacity (VIC) and Hydrology -Hydraulic (HH) physics -based models, the Gated Recurrent Unit (GRU) model, and hybrid models (VIC-GRU and HH-GRU). Evaluations were conducted at the 1h, 3-h, 6-h, 12-h, 24-h, and 48-h forecast lead times. Assessments at various lead times showed that hybrid models incorporating physics -based mechanisms significantly enhanced predictions. VIC-GRU demonstrated superior performance, with KGE values surpassing 0.94, NSE values exceeding 0.95, MAE below 0.17 m, and PBIAS within +/- 1 % across all lead times. Compared to GRU, PBIAS decreased by 84 %, while MAE dropped by 76 % to 81 % relative to VIC and HH, respectively. Notably, seasonal variations affected hybrid model performance, especially in the dry season. Optimal parameter selections enhanced model accuracy by 48 % to 49 %. These results underscore the potential of combining physics -based and deep learning models for more accurate, high -temporal -resolution real-time water level forecasts in data -scarce regions. A comprehensive study of streamflow characteristics enhances the advantages of this integration. This research contributes valuable insights to water level prediction in data -scarce regions and informs flood risk reduction and management in the Lancang-Mekong mainstream. |
| 英文关键词 | Lancang-Mekong River; Real-time water level forecasting; Hybrid models; GRU; Hyperparameter optimization |
| 语种 | 英语 |
| WOS研究方向 | Engineering ; Geology ; Water Resources |
| WOS类目 | Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources |
| WOS记录号 | WOS:001202716500001 |
| 来源期刊 | JOURNAL OF HYDROLOGY
 |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/302949 |
| 作者单位 | China Institute of Water Resources & Hydropower Research; China Institute of Water Resources & Hydropower Research; Tsinghua University; Xi'an University of Technology; Chinese Academy of Sciences; Aerospace Information Research Institute, CAS; Yellow River Engineering Consulting Co., Ltd.; Capital Normal University |
| 推荐引用方式 GB/T 7714 | . Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting - A case study on the Lancang-Mekong mainstream[J],2024,633. |
| APA | (2024).Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting - A case study on the Lancang-Mekong mainstream.JOURNAL OF HYDROLOGY,633. |
| MLA | "Superior performance of hybrid model in ungauged basins for real-time hourly water level forecasting - A case study on the Lancang-Mekong mainstream".JOURNAL OF HYDROLOGY 633(2024). |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
