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Titel |
How to predict hydrological effects of local land use change: how the vegetation parameterisation for short rotation coppices influences model results |
VerfasserIn |
F. Richter, C. Döring, M. Jansen, O. Panferov, U. Spank, C. Bernhofer |
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. 8 ; Nr. 19, no. 8 (2015-08-07), S.3457-3474 |
Datensatznummer |
250120783
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Publikation (Nr.) |
copernicus.org/hess-19-3457-2015.pdf |
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Zusammenfassung |
Among the different bioenergy sources, short rotation coppices (SRC) with
poplar and willow trees are one of the promising options in Europe. SRC provide not only woody biomass but also additional ecosystem services.
However, a known shortcoming is the potentially lower groundwater recharge
caused by the potentially higher evapotranspiration demand compared to
annual crops. The complex feedbacks between vegetation cover and water cycle
can be only correctly assessed by application of well-parameterised and
calibrated numerical models. In the present study, the hydrological model system WaSim (Wasserhaushalts-Simulations-Model) is implemented for assessment of the water balance. The focus
is the analysis of simulation uncertainties caused by the use of guidelines
or transferred parameter sets from scientific literature compared to
"actual" parameterisations derived from local measurements of leaf area index (LAI), stomatal resistance (Rsc) and date of leaf unfolding (LU). The
analysis showed that uncertainties in parameterisation of vegetation lead to
implausible model results. LAI, Rsc and LU are the most sensitive plant
physiological parameters concerning the effects of enhanced SRC cultivation
on water budget or groundwater recharge. Particularly sensitive is the
beginning of the growing season, i.e. LU. When this estimation is wrong, the
accuracy of LAI and Rsc description plays a minor role. Our analyses
illustrate that the use of locally measured vegetation parameters, like
maximal LAI, and meteorological variables, like air temperature, to estimate
LU give better results than literature data or data from remote network
stations. However, the direct implementation of locally measured data is not
always advisable or possible. Regarding Rsc, the adjustment of local
measurements gives the best model evaluation. For local and accurate
studies, measurements of model sensitive parameters like LAI, Rsc and LU are
valuable information. The derivation of these model parameters based on
local measurements shows the best model fit. Additionally, the adjusted
seasonal course of LAI and Rsc is less sensitive to different estimates for
LU. Different parameterisations, as they are all eligible either from local
measurements or scientific literature, can result in modelled ground water
recharge to be present or completely absent in certain years under poplar
SRC. |
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