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DOI10.5194/hess-23-4011-2019
Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain
A Lane R.; Coxon G.; E Freer J.; Wagener T.; J Johnes P.; P Bloomfield J.; Greene S.; J A Macleod C.; M Reaney S.
发表日期2019
ISSN1027-5606
起始页码4011
结束页码4032
卷号23期号:10
英文摘要Benchmarking model performance across large samples of catchments is useful to guide model selection and future model development. Given uncertainties in the observational data we use to drive and evaluate hydrological models, and uncertainties in the structure and parameterisation of models we use to produce hydrological simulations and predictions, it is essential that model evaluation is undertaken within an uncertainty analysis framework. Here, we benchmark the capability of several lumped hydrological models across Great Britain by focusing on daily flow and peak flow simulation. Four hydrological model structures from the Framework for Understanding Structural Errors (FUSE) were applied to over 1000 catchments in England, Wales and Scotland. Model performance was then evaluated using standard performance metrics for daily flows and novel performance metrics for peak flows considering parameter uncertainty.

Our results show that lumped hydrological models were able to produce adequate simulations across most of Great Britain, with each model producing simulations exceeding a 0.5 Nash-Sutcliffe efficiency for at least 80 % of catchments. All four models showed a similar spatial pattern of performance, producing better simulations in the wetter catchments to the west and poor model performance in central Scotland and south-eastern England. Poor model performance was often linked to the catchment water balance, with models unable to capture the catchment hydrology where the water balance did not close. Overall, performance was similar between model structures, but different models performed better for different catchment characteristics and metrics, as well as for assessing daily or peak flows, leading to the ensemble of model structures outperforming any single structure, thus demonstrating the value of using multi-model structures across a large sample of different catchment behaviours.

This research evaluates what conceptual lumped models can achieve as a performance benchmark and provides interesting insights into where and why these simple models may fail. The large number of river catchments included in this study makes it an appropriate benchmark for any future developments of a national model of Great Britain. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.

语种英语
scopus关键词Catchments; Digital storage; Flood control; Floods; Model structures; Runoff; Uncertainty analysis; Benchmarking models; Catchment characteristics; Catchment water balance; Hydrological modeling; Hydrological simulations; Parameter uncertainty; Predictive capabilities; Standard performance; Benchmarking; catchment; hydrological modeling; hydrology; peak flow; performance assessment; river flow; simulation; uncertainty analysis; water budget; United Kingdom
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/159809
作者单位A Lane, R., School of Geographical Sciences, University of Bristol, Bristol, BS8 2NQ, United Kingdom; Coxon, G., School of Geographical Sciences, University of Bristol, Bristol, BS8 2NQ, United Kingdom; E Freer, J., School of Geographical Sciences, University of Bristol, Bristol, BS8 2NQ, United Kingdom, Cabot Institute, University of Bristol, Bristol, BS8 2NQ, United Kingdom; Wagener, T., Faculty of Engineering, University of Bristol, Bristol, BS82NQ, United Kingdom, Cabot Institute, University of Bristol, Bristol, BS8 2NQ, United Kingdom; J Johnes, P., School of Geographical Sciences, University of Bristol, Bristol, BS8 2NQ, United Kingdom, Cabot Institute, University of Bristol, Bristol, BS8 2NQ, United Kingdom; P Bloomfield, J., British Geological Survey, Maclean Building, Wallingford, OX10 8BB, United Kingdom; Greene, S., Trinity College Dublin, Dublin, Ireland; J A Macleod, C., James Hutton Institute, Craigiebuckler, Aberdeen, AB15 8QH, United Kingdom; M Reaney, S., Department of Geography, Durham U...
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GB/T 7714
A Lane R.,Coxon G.,E Freer J.,et al. Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain[J],2019,23(10).
APA A Lane R..,Coxon G..,E Freer J..,Wagener T..,J Johnes P..,...&M Reaney S..(2019).Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain.Hydrology and Earth System Sciences,23(10).
MLA A Lane R.,et al."Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain".Hydrology and Earth System Sciences 23.10(2019).
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