Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2018WR023650 |
A Nonlinear Dynamical System-Based Modelling Approach for Stochastic Simulation of Streamflow and Understanding Predictability | |
Rajagopalan, Balaji1,2; Erkyihun, Solomon Tassew1,3,4; Late, Upmanu5; Zagona, Edith1,3; Nowak, Kenneth6 | |
2019-07-01 | |
发表期刊 | WATER RESOURCES RESEARCH
![]() |
ISSN | 0043-1397 |
EISSN | 1944-7973 |
出版年 | 2019 |
卷号 | 55期号:7页码:6268-6284 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | We propose a time series modeling approach based on nonlinear dynamical systems to recover the underlying dynamics and predictability of streamflow and to produce projections with identifiable skill. First, a wavelet spectral analysis is performed on the time series to identify the dominant quasiperiodic bands. The time series is then reconstructed across these bands and summed to obtain a signal time series. This signal is embedded in a D-dimensional space with an appropriate lag tau to reconstruct the phase space in which the dynamics unfolds. Time-varying predictability is assessed by quantifying the divergence of trajectories in the phase space with time, using Local Lyapunov Exponents. Ensembles of projections from a current time are generated by block resampling trajectories of desired projection length, from the K-nearest neighbors of the current vector in the phase space. This modeling approach was applied to the naturalized historical and paleoreconstructed streamflow at Lees Ferry gauge on the Colorado River, which offered three interesting insights. (i) The flows exhibited significant epochal variations in predictability. (ii) The predictability of the flow quantified by Local Lyapunov Exponent is related to the variance of the flow signal and selected climate indices. (iii) Blind projections of flow during epochs identified as highly predictable showed good skill in capturing the distributional and threshold exceedance statistics and poor performance during low predictability epochs. The ability to assess the potential skill of these long lead projections opens opportunities to perceive hydrologic predictability and consequently water management in a new paradigm. |
领域 | 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000481444700061 |
WOS关键词 | GREAT-SALT-LAKE ; ATLANTIC MULTIDECADAL OSCILLATION ; TIME-SERIES ; SPACE RECONSTRUCTION ; LYAPUNOV EXPONENTS ; CHAOS ; PREDICTION ; VARIABILITY ; IDENTIFICATION ; BOOTSTRAP |
WOS类目 | Environmental Sciences ; Limnology ; Water Resources |
WOS研究方向 | Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/184882 |
专题 | 资源环境科学 |
作者单位 | 1.Univ Colorado Boulder, Civil Environm & Architectural Engn, Boulder, CO 80309 USA; 2.Univ Colorado Boulder, CIRES, Boulder, CO 80309 USA; 3.Univ Colorado Boulder, CADSWES, Boulder, CO USA; 4.Tampa Bay Water, Clearwater, FL USA; 5.Columbia Univ, Earth & Environm Engn, New York, NY USA; 6.Tech Serv Ctr, Bur Reclamat, Denver, CO USA |
推荐引用方式 GB/T 7714 | Rajagopalan, Balaji,Erkyihun, Solomon Tassew,Late, Upmanu,et al. A Nonlinear Dynamical System-Based Modelling Approach for Stochastic Simulation of Streamflow and Understanding Predictability[J]. WATER RESOURCES RESEARCH,2019,55(7):6268-6284. |
APA | Rajagopalan, Balaji,Erkyihun, Solomon Tassew,Late, Upmanu,Zagona, Edith,&Nowak, Kenneth.(2019).A Nonlinear Dynamical System-Based Modelling Approach for Stochastic Simulation of Streamflow and Understanding Predictability.WATER RESOURCES RESEARCH,55(7),6268-6284. |
MLA | Rajagopalan, Balaji,et al."A Nonlinear Dynamical System-Based Modelling Approach for Stochastic Simulation of Streamflow and Understanding Predictability".WATER RESOURCES RESEARCH 55.7(2019):6268-6284. |
条目包含的文件 | 条目无相关文件。 |
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。
修改评论