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| Titel |
A proposal to reduce streamflow predictive uncertainty in ungauged basins |
| VerfasserIn |
Luis Samaniego, Rohini Kumar, András Bárdossy |
| Konferenz |
EGU General Assembly 2010
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 12 (2010) |
| Datensatznummer |
250037956
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| Zusammenfassung |
| One of the main goals of the PUB Science Plan is to reduce uncertainty in hydrological
predictions. Prediction in ungauged basins is, however, a complex task mainly because
the hydrologic processes occurring within a basin take place over a wide range of
spatio-temporal scales for which no agreed upon general hydrological theory is
still available. For these reasons, various techniques are required to guaranty the
transferability of information from donor basins to an ungauged locations. These
techniques aim 1) to find an appropriate dissimilarity measure based on discharge
time series. 2) to relate a dissimilarity measure with various basin descriptors. 3)
to develop a multiscale parameter regionalization (MPR) technique that is able
to relate model parameters with basin characteristics through transfers functions
and upscaling operators. And, 4) to develop a multi-structure hydrologic model to
represent various dominant hydrologic process. As shown in Samaniego et al., 2010a,
2010b1
2, the
combination of first three techniques within a Monte Carlo framework have contributed to
reduce the predictive uncertainty in a number of crossvalidation experiments in
Germany. Additionally, the MPR technique ensures the transferability across modelling
scales.
In this study, we propose a method that further reduces the streamflow predictive
uncertainty at ungauged locations by selecting only those transfer function
parameters (from donor basins) which are able to reproduce discharge simulations
in an ungauged location whose seasonal runoff characteristics are closer to
those obtained with regionalized input-output models (Samaniego and Bárdossy,
2005)3.
Runoff characteristics such as total drought duration, magnitude and frequency of high flows,
among others, can be used for this purpose.
To illustrate the application of this technique, 34 southern German basins ranging from 70
to 4200 km2 were selected. For each donor basin a number of catchment descriptors were
quantified for the regionalization of the runoff characteristics, e.g. mean slope, aspect, shape
factor, mean elevation, and several climatic indices such as the antecedent precipitation index
and mean monthly temperature. Daily streamflow time series for the donor basins
correspond to the period from 1961 to 2000. Results showed that this procedure lead to a
reduction up to 20% of the streamflow predictive uncertainty if compared with
unconstrained selection of transfer function parameters from the nearest donor
basins. |
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