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DOI	10.5194/hess-22-871-2018
	State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application
	Gibbs M.S.; McInerney D.; Humphrey G.; Thyer M.A.; Maier H.R.; Dandy G.C.; Kavetski D.
发表日期	2018
ISSN	1027-5606
起始页码	871
结束页码	887
卷号	22 期号:1
英文摘要	Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.
语种	英语
scopus关键词	Calibration; Catchments; Decision making; Environmental management; Information management; Open channel flow; Rain; Runoff; Stream flow; Uncertainty analysis; Water management; Water resources; Environmental decision making; Planning applications; Predictive performance; Rainfall-runoff modeling; Streamflow forecast; Streamflow forecasting; Traditional approaches; Waterresource management; Forecasting; calibration; catchment; decision making; drainage network; forecasting method; rainfall; rainfall-runoff modeling; seasonal variation; streamflow; water management; water planning; water resource; Australia
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160113
作者单位	Gibbs, M.S., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia, Department of Environment, Water and Natural Resources, Government of South Australia, P.O. Box 1047, Adelaide, 5000, Australia; McInerney, D., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia; Humphrey, G., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia; Thyer, M.A., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia; Maier, H.R., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia; Dandy, G.C., School of Civil, Environmental and Mining Engineering, University of Adelaide, North Terrace, Adelaide, SA 5005, Australia; Kavetski, D., School of Civil, Environmental and Mining Engi...
推荐引用方式 GB/T 7714	Gibbs M.S.,McInerney D.,Humphrey G.,et al. State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application[J],2018,22(1).
APA	Gibbs M.S..,McInerney D..,Humphrey G..,Thyer M.A..,Maier H.R..,...&Kavetski D..(2018).State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application.Hydrology and Earth System Sciences,22(1).
MLA	Gibbs M.S.,et al."State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application".Hydrology and Earth System Sciences 22.1(2018).