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| Titel |
Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data |
| VerfasserIn |
F. Silvestro, S. Gabellani, R. Rudari, F. Delogu, P. Laiolo, G. Boni |
| 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 ; 19, no. 4 ; Nr. 19, no. 4 (2015-04-16), S.1727-1751 |
| Datensatznummer |
250120680
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| Publikation (Nr.) |
 copernicus.org/hess-19-1727-2015.pdf |
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| Zusammenfassung |
During the last decade the opportunity and usefulness of using remote-sensing data in hydrology, hydrometeorology and geomorphology has become
even more evident and clear. Satellite-based products often allow for the
advantage of observing hydrologic variables in a distributed way, offering a
different view with respect to traditional observations that can help with
understanding and modeling the hydrological cycle. Moreover, remote-sensing data
are fundamental in scarce data environments. The use of satellite-derived
digital elevation models (DEMs), which are now globally available at 30 m
resolution (e.g., from Shuttle Radar Topographic Mission, SRTM), have become
standard practice in hydrologic model implementation, but other types of
satellite-derived data are still underutilized. As a consequence there is
the need for developing and testing techniques that allow the
opportunities given by remote-sensing data to be exploited, parameterizing hydrological
models and improving their calibration.
In this work, Meteosat Second Generation land-surface temperature (LST)
estimates and surface soil moisture (SSM), available from European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) H-SAF, are
used together with streamflow observations (S. N.) to calibrate the Continuum hydrological model that computes such state variables in a prognostic mode. The first
part of the work aims at proving that satellite observations can be
exploited to reduce uncertainties in parameter calibration by reducing the
parameter equifinality that can become an issue in forecast mode. In the
second part, four parameter estimation strategies are implemented and tested
in a comparative mode: (i) a multi-objective approach that includes both
satellite and ground observations which is an attempt to use different
sources of data to add constraints to the parameters; (ii and iii) two
approaches solely based on remotely sensed data that reproduce the case of
a scarce data environment where streamflow observation are not available;
(iv) a standard calibration based on streamflow observations used as a benchmark
for the others.
Two Italian catchments are used as a test bed to verify the model capability
in reproducing long-term (multi-year) simulations.
The results of the analysis evidence that, as a result of the model
structure and the nature itself of the catchment hydrologic processes, some
model parameters are only weakly dependent on discharge observations, and
prove the usefulness of using data from both ground stations and satellites
to additionally constrain the parameters in the calibration process and
reduce
the number of equifinal solutions. |
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