Publication Date:
2019
Description:
Abstract
In semi‐distributed hydrological modeling, sequential calibration usually refers to the calibration of a model by considering not only the flows observed at the outlet of a catchment, but also the different gauging points inside the catchment from upstream to downstream. While sequential calibration aims to optimize the performance at these interior gauged points, we show that it generally fails to improve performance at ungauged points. In this paper, we propose a regularization approach for the sequential calibration of semi‐distributed hydrological models. It consists in adding a priori information on optimal parameter sets for each modeling unit of the semi‐distributed model. Calibration iterations are then performed by jointly maximizing simulation performance and minimizing drifts from the a priori parameter sets. The combination of these two sources of information is handled by a parameter k to which the method is quite sensitive. The method is applied to 1305 catchments in France over 30 years of observed records. The leave‐one‐out validation shows that, at locations considered as ungauged, model simulations are significantly improved (over all the catchments, the median KGE criterion is increased from 0.75 to 0.83 and the first quartile from 0.35 to 0.66), while model performance at gauged points is not significantly impacted by the use of the regularization approach. Small catchments benefit most from this calibration strategy. These performances are however very similar with the performances obtained with a lumped model based on similar conceptualization.
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
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