气候变化领域集成服务门户(CCPortal): The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed

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DOI	10.5194/hess-22-5947-2018
	The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed
	Hoang L.; Mukundan R.; Moore K.E.B.; Owens E.M.; Steenhuis T.S.
发表日期	2018
ISSN	1027-5606
起始页码	5947
结束页码	5965
卷号	22 期号:11
英文摘要	Uncertainty in hydrological modeling is of significant concern due to its effects on prediction and subsequent application in watershed management. Similar to other distributed hydrological models, model uncertainty is an issue in applying the Soil and Water Assessment Tool (SWAT). Previous research has shown how SWAT predictions are affected by uncertainty in parameter estimation and input data resolution. Nevertheless, little information is available on how parameter uncertainty and output uncertainty are affected by input data of varying complexity. In this study, SWAT-Hillslope (SWAT-HS), a modified version of SWAT capable of predicting saturation-excess runoff, was applied to assess the effects of input data with varying degrees of complexity on parameter uncertainty and output uncertainty. Four digital elevation model (DEM) resolutions (1, 3, 10 and 30 m) were tested for their ability to predict streamflow and saturated areas. In a second analysis, three soil maps and three land use maps were used to build nine SWAT-HS setups from simple to complex (fewer to more soil types/land use classes), which were then compared to study the effect of input data complexity on model prediction/output uncertainty. The case study was the Town Brook watershed in the upper reaches of the West Branch Delaware River in the Catskill region, New York, USA. Results show that DEM resolution did not impact parameter uncertainty or affect the simulation of streamflow at the watershed outlet but significantly affected the spatial pattern of saturated areas, with 10m being the most appropriate grid size to use for our application. The comparison of nine model setups revealed that input data complexity did not affect parameter uncertainty. Model setups using intermediate soil/land use specifications were slightly better than the ones using simple information, while the most complex setup did not show any improvement from the intermediate ones. We conclude that improving input resolution and complexity may not necessarily improve model performance or reduce parameter and output uncertainty, but using multiple temporal and spatial observations can aid in finding the appropriate parameter sets and in reducing prediction/output uncertainty. © Author(s) 2018.
语种	英语
scopus关键词	Forecasting; Input output programs; Land use; Soil conservation; Soils; Stream flow; Surveying; Water conservation; Water management; Watersheds; Degrees of complexity; Digital elevation model; Distributed hydrological model; Hydrological modeling; Hydrological prediction; Parameter uncertainty; Saturation excess runoffs; Soil and water assessment tool; Uncertainty analysis; complexity; digital elevation model; hydrological modeling; parameter estimation; prediction; resolution; soil and water assessment tool; streamflow; uncertainty analysis; watershed; Appalachians; Catskill Mountains; Delaware River; New York [United States]; Town Brook; United States
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/159849
作者单位	Hoang, L., Hunter College, City University of New York, 695 Park Avenue, New York, NY 10065, United States, New York City Department of Environmental Protection, 71 Smith Avenue, Kingston, NY 12401, United States, National Institute of Water and Atmospheric Research, Hamilton, New Zealand; Mukundan, R., New York City Department of Environmental Protection, 71 Smith Avenue, Kingston, NY 12401, United States; Moore, K.E.B., New York City Department of Environmental Protection, 71 Smith Avenue, Kingston, NY 12401, United States; Owens, E.M., New York City Department of Environmental Protection, 71 Smith Avenue, Kingston, NY 12401, United States; Steenhuis, T.S., Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, United States
推荐引用方式 GB/T 7714	Hoang L.,Mukundan R.,Moore K.E.B.,et al. The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed[J],2018,22(11).
APA	Hoang L.,Mukundan R.,Moore K.E.B.,Owens E.M.,&Steenhuis T.S..(2018).The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed.Hydrology and Earth System Sciences,22(11).
MLA	Hoang L.,et al."The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed".Hydrology and Earth System Sciences 22.11(2018).