气候变化领域集成服务门户(CCPortal): Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions

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DOI	10.5194/hess-23-171-2019
	Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions
	Jing M.; Heße F.; Kumar R.; Kolditz O.; Kalbacher T.; Attinger S.
发表日期	2019
ISSN	1027-5606
起始页码	171
结束页码	190
卷号	23 期号:1
英文摘要	Groundwater travel time distributions (TTDs) provide a robust description of the subsurface mixing behavior and hydrological response of a subsurface system. Lagrangian particle tracking is often used to derive the groundwater TTDs. The reliability of this approach is subjected to the uncertainty of external forcings, internal hydraulic properties, and the interplay between them. Here, we evaluate the uncertainty of catchment groundwater TTDs in an agricultural catchment using a 3-D groundwater model with an overall focus on revealing the relationship between external forcing, internal hydraulic properties, and TTD predictions. Eight recharge realizations are sampled from a high-resolution dataset of land surface fluxes and states. Calibration-constrained hydraulic conductivity fields (K s fields) are stochastically generated using the null-space Monte Carlo (NSMC) method for each recharge realization. The random walk particle tracking (RWPT) method is used to track the pathways of particles and compute travel times. Moreover, an analytical model under the random sampling (RS) assumption is fit against the numerical solutions, serving as a reference for the mixing behavior of the model domain. The StorAge Selection (SAS) function is used to interpret the results in terms of quantifying the systematic preference for discharging young/old water. The simulation results reveal the primary effect of recharge on the predicted mean travel time (MTT). The different realizations of calibration-constrained K s fields moderately magnify or attenuate the predicted MTTs. The analytical model does not properly replicate the numerical solution, and it underestimates the mean travel time. Simulated SAS functions indicate an overall preference for young water for all realizations. The spatial pattern of recharge controls the shape and breadth of simulated TTDs and SAS functions by changing the spatial distribution of particles' pathways. In conclusion, overlooking the spatial nonuniformity and uncertainty of input (forcing) will result in biased travel time predictions. We also highlight the worth of reliable observations in reducing predictive uncertainty and the good interpretability of SAS functions in terms of understanding catchment transport processes. © 2019 Author(s).
语种	英语
scopus关键词	Analytical models; Calibration; Catchments; Forecasting; Groundwater; Mixing; Monte Carlo methods; Numerical models; Runoff; Spatial distribution; Surface measurement; Agricultural catchments; Distribution of particles; Hydrological response; Lagrangian particle tracking; Predictive uncertainty; Random walk particle tracking; Travel time distributions; Travel time prediction; Travel time; agricultural catchment; catchment; groundwater; hydraulic conductivity; hydrological modeling; hydrological response; mixing; prediction; recharge; travel time; uncertainty analysis
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/159794
作者单位	Jing, M., Department of Computational Hydrosystems, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318, Germany, Institute of Geosciences, Friedrich Schiller University Jena, Burgweg 11, Jena, 07749, Germany; Heße, F., Department of Computational Hydrosystems, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318, Germany; Kumar, R., Department of Computational Hydrosystems, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318, Germany; Kolditz, O., Department of Environmental Informatics, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318, Germany, Applied Environmental Systems Analysis, Technische Universität Dresden, Dresden, Germany; Kalbacher, T., Department of Environmental Informatics, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318, Germany; Attinger, S., Department of Computational Hydrosystems, UFZ - Helmholtz Centre for Environmental Resea...
推荐引用方式 GB/T 7714	Jing M.,Heße F.,Kumar R.,et al. Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions[J],2019,23(1).
APA	Jing M.,Heße F.,Kumar R.,Kolditz O.,Kalbacher T.,&Attinger S..(2019).Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions.Hydrology and Earth System Sciences,23(1).
MLA	Jing M.,et al."Influence of input and parameter uncertainty on the prediction of catchment-scale groundwater travel time distributions".Hydrology and Earth System Sciences 23.1(2019).