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Titel |
Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment |
VerfasserIn |
R. Guzinski, H. Nieto, S. Stisen, R. Fensholt |
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 (2015-04-24), S.2017-2036 |
Datensatznummer |
250120696
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Publikation (Nr.) |
copernicus.org/hess-19-2017-2015.pdf |
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Zusammenfassung |
Evapotranspiration (ET) is the main link between the natural water cycle and
the land surface energy budget. Therefore water-balance and energy-balance
approaches are two of the main methodologies for modelling this process. The
water-balance approach is usually implemented as a complex, distributed
hydrological model, while the energy-balance approach is often used with
remotely sensed observations of, for example, the land surface temperature
(LST) and the state of the vegetation. In this study we compare the
catchment-scale output of two remote sensing models based on the two-source
energy-balance (TSEB) scheme, against a hydrological model, MIKE SHE,
calibrated over the Skjern river catchment in western Denmark. The three
models utilize different primary inputs to estimate ET (LST from different
satellites in the case of remote sensing models and modelled soil moisture
and heat flux in the case of the MIKE SHE ET module). However, all three of
them use the same ancillary data (meteorological measurements, land cover
type and leaf area index, etc.) and produce output at similar spatial
resolution (1 km for the TSEB models, 500 m for MIKE SHE).
The comparison is performed on the spatial patterns of the fluxes present
within the catchment area as well as on temporal patterns on the whole
catchment scale in 8-year long time series. The results show that the spatial
patterns of latent heat flux produced by the remote sensing models are more
similar to each other than to the fluxes produced by MIKE SHE. The temporal
patterns produced by the remote sensing and hydrological models are quite
highly correlated (r ≈ 0.8). This indicates potential benefits to the
hydrological modelling community of integrating spatial information derived
through remote sensing methodology (contained in the ET maps derived with the
energy-balance models, satellite based LST or another source) into the
hydrological models. How this could be achieved and how to evaluate the
improvements, or lack of thereof, is still an open research question. |
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