DOI: 10.5194/hess-22-127-2018
Scopus记录号: 2-s2.0-85040525608
论文题名: Exploratory studies into seasonal flow forecasting potential for large lakes
作者: Sene K ; , Tych W ; , Beven K
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2018
卷: 22, 期: 1 起始页码: 127
结束页码: 141
语种: 英语
Scopus关键词: Digital storage
; Forecasting
; Model structures
; Stochastic models
; Stochastic systems
; Analytical approximation
; Data assimilation
; Data availability
; Exploratory studies
; Flow forecasting
; Hydrological response
; Individual components
; Water balance models
; Lakes
; data assimilation
; exploration
; flow measurement
; forecasting method
; hydrological modeling
; hydrological response
; seasonal variation
; transfer function
; East African Lakes
; Lake Malawi
; Lake Victoria
英文摘要: In seasonal flow forecasting applications, one factor which can help predictability is a significant hydrological response time between rainfall and flows. On account of storage influences, large lakes therefore provide a useful test case although, due to the spatial scales involved, there are a number of modelling challenges related to data availability and understanding the individual components in the water balance. Here some possible model structures are investigated using a range of stochastic regression and transfer function techniques with additional insights gained from simple analytical approximations. The methods were evaluated using records for two of the largest lakes in the world - Lake Malawi and Lake Victoria - with forecast skill demonstrated several months ahead using water balance models formulated in terms of net inflows. In both cases slight improvements were obtained for lead times up to 4-5 months from including climate indices in the data assimilation component. The paper concludes with a discussion of the relevance of the results to operational flow forecasting systems for other large lakes. © Author(s) 2018. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79434
Appears in Collections: 气候变化事实与影响
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作者单位: Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
Recommended Citation:
Sene K,, Tych W,, Beven K. Exploratory studies into seasonal flow forecasting potential for large lakes[J]. Hydrology and Earth System Sciences,2018-01-01,22(1)