Climate Change Data Portal
DOI | 10.2166/hydro.2024.229 |
Utilizing waveform synthesis in harmonic oscillator seasonal trend model for short- and long-term streamflow drought modeling and forecasting | |
发表日期 | 2024 |
ISSN | 1464-7141 |
EISSN | 1465-1734 |
起始页码 | 26 |
结束页码 | 4 |
卷号 | 26期号:4 |
英文摘要 | This study introduces an improved version of the harmonic oscillator seasonal trend (HOST) model framework to accurately simulate medium- and long-term changes in extreme events, focusing on streamflow droughts in the Mobile River catchment. Performance of the model relative to the initial framework was enhanced through the inclusion of new mathematical models and waveform synthesis. The updated framework successfully captures long-term and seasonal patterns with a Kling-Gupta efficiency exceeding 0.5 for seasonal fluctuations and over 0.9 for trends. The best-fit model explains around 98% of long-term and approximately 55% of seasonal variance. Test sets show slightly lower accuracies, with about 20% of nodes underperforming due to the absence of drought during the test phase resulting in false-positive model forecasts. The newly developed weighted occurrence classification outperforms the binary classification occurrence model. In addition, application of an automatic period multiplier for decomposition using the seasonal trend decomposition using LOESS method improves test dataset performance and reduces false-positive forecasts. The improved framework provides valuable insights for extreme flow distribution, offering potential for improved water management planning, and the combination of the HOST model with physical models can address short-term drivers of extreme events, enhancing drought occurrence forecasting and water resource management strategies. |
英文关键词 | host model; modeling; seasonality; streamflow drought; trend; wave |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering ; Environmental Sciences & Ecology ; Water Resources |
WOS类目 | Computer Science, Interdisciplinary Applications ; Engineering, Civil ; Environmental Sciences ; Water Resources |
WOS记录号 | WOS:001198311200001 |
来源期刊 | JOURNAL OF HYDROINFORMATICS
![]() |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/297422 |
作者单位 | Mississippi State University; Mississippi State University |
推荐引用方式 GB/T 7714 | . Utilizing waveform synthesis in harmonic oscillator seasonal trend model for short- and long-term streamflow drought modeling and forecasting[J],2024,26(4). |
APA | (2024).Utilizing waveform synthesis in harmonic oscillator seasonal trend model for short- and long-term streamflow drought modeling and forecasting.JOURNAL OF HYDROINFORMATICS,26(4). |
MLA | "Utilizing waveform synthesis in harmonic oscillator seasonal trend model for short- and long-term streamflow drought modeling and forecasting".JOURNAL OF HYDROINFORMATICS 26.4(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。