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| Titel |
Series distance – an intuitive metric to quantify hydrograph similarity in terms of occurrence, amplitude and timing of hydrological events |
| VerfasserIn |
U. Ehret, E. Zehe |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 15, no. 3 ; Nr. 15, no. 3 (2011-03-11), S.877-896 |
| Datensatznummer |
250012687
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| Publikation (Nr.) |
 copernicus.org/hess-15-877-2011.pdf |
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| Zusammenfassung |
Applying metrics to quantify the similarity or dissimilarity of hydrographs
is a central task in hydrological modelling, used both in model calibration
and the evaluation of simulations or forecasts. Motivated by the
shortcomings of standard objective metrics such as the Root Mean Square
Error (RMSE) or the Mean Absolute Peak Time Error (MAPTE) and the advantages
of visual inspection as a powerful tool for simultaneous, case-specific and
multi-criteria (yet subjective) evaluation, we propose a new objective
metric termed Series Distance, which is in close accordance with visual
evaluation. The Series Distance quantifies the similarity of two hydrographs
neither in a time-aggregated nor in a point-by-point manner, but on the
scale of hydrological events. It consists of three parts, namely a Threat
Score which evaluates overall agreement of event occurrence, and the overall
distance of matching observed and simulated events with respect to amplitude
and timing. The novelty of the latter two is the way in which matching point
pairs on the observed and simulated hydrographs are identified: not by
equality in time (as is the case with the RMSE), but by the same relative
position in matching segments (rise or recession) of the event, indicating
the same underlying hydrological process. Thus, amplitude and timing errors
are calculated simultaneously but separately, from point pairs that also
match visually, considering complete events rather than only individual
points (as is the case with MAPTE). Relative weights can freely be assigned
to each component of the Series Distance, which allows (subjective)
customization of the metric to various fields of application, but in a
traceable way. Each of the three components of the Series Distance
can be used in an aggregated or non-aggregated way, which makes
the Series Distance a suitable tool for differentiated, process-based model
diagnostics.
After discussing the applicability of established time series metrics for
hydrographs, we present the Series Distance theory, discuss its properties
and compare it to those of standard metrics used in Hydrology, both at the
example of simple, artificial hydrographs and an ensemble of realistic
forecasts. The results suggest that the Series Distance quantifies the
degree of similarity of two hydrographs in a way comparable to visual
inspection, but in an objective, reproducible way. |
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