气候变化领域集成服务门户(CCPortal): On the assimilation of environmental tracer observations for model-based decision support

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DOI	10.5194/hess-24-1677-2020
	On the assimilation of environmental tracer observations for model-based decision support
	Knowling M.J.; White J.T.; Moore C.R.; Rakowski P.; Hayley K.
发表日期	2020
ISSN	1027-5606
起始页码	1677
结束页码	1689
卷号	24 期号:4
英文摘要	It has been advocated that history matching numerical models to a diverse range of observation data types, particularly including environmental tracer concentrations and their interpretations and derivatives (e.g., mean age), constitutes an effective and appropriate means to improve model forecast reliability. This study presents two regional-scale modeling case studies that directly and rigorously assess the value of discrete tritium concentration observations and tritium-derived mean residence time (MRT) estimates in two decision-support contexts; "value" is measured herein as both the improvement (or otherwise) in the reliability of forecasts through uncertainty variance reduction and bias minimization as a result of assimilating tritium or tritium-derived MRT observations. The first case study (Heretaunga Plains, New Zealand) utilizes a suite of steady-state and transient flow models and an advection-only particle-tracking model to evaluate the worth of tritium-derived MRT estimates relative to hydraulic potential, spring discharge and river-aquifer exchange flux observations. The worth of MRT observations is quantified in terms of the change in the uncertainty surrounding ecologically sensitive spring discharge forecasts via first-order second-moment (FOSM) analyses. The second case study (Hauraki Plains, New Zealand) employs paired simple-complex transient flow and transport models to evaluate the potential for assimilation-induced bias in simulated surface-water nitrate discharge to an ecologically sensitive estuary system; formal data assimilation of tritium observations is undertaken using an iterative ensemble smoother. The results of these case studies indicate that, for the decision-relevant forecasts considered, tritium observations are of variable benefit and may induce damaging bias in forecasts; these biases are a result of an imperfect model's inability to properly and directly assimilate the rich information content of the tritium observations. The findings of this study challenge the advocacy of the increasing use of tracers, and of diverse data types more generally, whenever environmental model data assimilation is undertaken with imperfect models. This study also highlights the need for improved imperfect-model data assimilation strategies. While these strategies will likely require increased model complexity (including advanced discretization, processes and parameterization) to allow for appropriate assimilation of rich and diverse data types that operate across a range of spatial and temporal scales commensurate with a forecast of management interest, it is critical that increased model complexity does not preclude the application of formal data assimilation and uncertainty quantification techniques due to model instability and excessive run times. © 2020 Author(s).
语种	英语
scopus关键词	Aquifers; Decision support systems; Forecasting; Iterative methods; Surface waters; Tracers; Transition flow; Tritium; Environmental tracers; Information contents; Iterative ensemble smoothers; Particle tracking models; Spatial and temporal scale; Steady state and transients; Tritium concentration; Uncertainty quantifications; Uncertainty analysis; concentration (composition); data assimilation; decision support system; groundwater-surface water interaction; tracer; transient flow; tritium; Hauraki Plains; Hawkes Bay; Heretaunga Plains; New Zealand; North Island; Waikato
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/159449
作者单位	Knowling, M.J., GNS Science, Lower Hutt, New Zealand; White, J.T., GNS Science, Lower Hutt, New Zealand; Moore, C.R., GNS Science, Lower Hutt, New Zealand; Rakowski, P., Hawke's Bay Regional Council, Napier, New Zealand; Hayley, K., Groundwater Solutions Ltd, Melbourne, VIC, Australia
推荐引用方式 GB/T 7714	Knowling M.J.,White J.T.,Moore C.R.,et al. On the assimilation of environmental tracer observations for model-based decision support[J],2020,24(4).
APA	Knowling M.J.,White J.T.,Moore C.R.,Rakowski P.,&Hayley K..(2020).On the assimilation of environmental tracer observations for model-based decision support.Hydrology and Earth System Sciences,24(4).
MLA	Knowling M.J.,et al."On the assimilation of environmental tracer observations for model-based decision support".Hydrology and Earth System Sciences 24.4(2020).