全球智库信息集成服务系统(G2TT): Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting.

G2TT

来源类型	Article
规范类型	其他
DOI	10.1177/0309133312444943
	Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting.
	Abrahart RJ; Anctil F; Coulibaly P; Dawson CW; Mount NJ; See L; Shamseldin AY; Solomatine DP
发表日期	2012
出处	Progress in Physical Geography 36 (4): 480-513
出版年	2012
语种	英语
摘要	This paper traces two decades of neural network rainfall-runoff and streamflow modelling, collectively termed "river forecasting." The field is now firmly established and the research community involved has much to offer hydrological science. First, however, it will be necessary to converge on more objective and consistent protocols for: selecting and treating inputs prior to model development; extracting physically meaningful insights from each proposed solution; and improving transparency in the benchmarking and reporting of experimental case studies. It is also clear that neural network river forecasting solutions will have limited appeal for operational purposes until confidence intervals can be attached to forecasts. Modular design, ensemble experiments, and hybridization with conventional hydrological models are yielding new tools for decision-making. The full potential for modelling complex hydrological systems, and for characterizing uncertainty, has yet to be realized. Further gains could also emerge from the provision of an agreed set of benchmark data sets and associated development of superior diagnostics for more rigorous intermodel evaluation. To achieve these goals will require a paradigm shift, such that the mass of individual isolated activities, focused on incremental technical refinement, is replaced by a more coordinated, problem-solving international research body.
主题	Ecosystems Services and Management (ESM)
关键词	Forecasting Modelling Network Neural River
URL	http://pure.iiasa.ac.at/id/eprint/9920/
来源智库	International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/129519
推荐引用方式 GB/T 7714	Abrahart RJ,Anctil F,Coulibaly P,et al. Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting.. 2012.