To tame a land: Limiting factors in model performance for the multi-objective calibration of a pan-European, semi-distributed hydrological model for discharge and sediments

被引:3
作者
Brendel, Conrad [1 ]
Capell, Rene [1 ]
Bartosova, Alena [1 ]
机构
[1] Swedish Meteorol & Hydrol Inst, Norrkoping, Sweden
关键词
Calibration; Large; -Scale; HYPE; Hydrological Model; Europe; Sediment; TRACING SUSPENDED SEDIMENT; ENVIRONMENTAL-CHANGE; UNGAUGED BASINS; GULLY EROSION; UNCERTAINTY; PREDICTIONS; IMPACTS; WATER;
D O I
10.1016/j.ejrh.2023.101544
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Study Region: EuropeStudy Focus: The semi-distributed Hydrological Predictions for the Environment (HYPE) model for the European domain, E-HYPE4, was calibrated for discharge and sediments within a framework allowing for evaluation of the factors limiting model performance. Calibration was conducted using a multi-phase approach during which an initial multi-objective discharge/sediment calibration was followed by an exhaustive sediment calibration in which combinations of sediment routines were assessed. During each calibration phase, ensembles of parameter sets and model routines were simultaneously evaluated against discharge, evapotranspiration, and sediment observations. In total, 20,000 parameter sets were evaluated during the discharge calibration, and a further 20,000 model setups were assessed during the sediment calibration. New Hydrological Insights for the Region: Model performance was best with a highly regionalized model, and the largest drop in achievable performance occurred when transitioning from an ensemble of candidates to a single model setup. Much of the performance gains from a highly regionalized model could, however, be achieved with a much less regionalized model. Inclusion of sediments as a calibration objective provided more value than that of evapotranspiration in regards to reducing equifinality in the calibration for discharge. Evaluation of the erosion routines indicated that an index-based routine performed equally well as a more complex, process-based routine. Finally, analysis of model performance by subbasin attributes revealed the dominant factors - such as landuse, glaciers, abstractions/regulations, groundwater, and lakes/wetlands - affecting model biases for various regions.
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页数:31
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