![Hier klicken, um den Treffer aus der Auswahl zu entfernen](images/unchecked.gif) |
Titel |
Alternative methods to predict actual evapotranspiration illustrate the importance of accounting for phenology – Part 2: The event driven phenology model |
VerfasserIn |
V. Kovalskyy, G. M. Henebry |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1726-4170
|
Digitales Dokument |
URL |
Erschienen |
In: Biogeosciences ; 9, no. 1 ; Nr. 9, no. 1 (2012-01-09), S.161-177 |
Datensatznummer |
250006657
|
Publikation (Nr.) |
copernicus.org/bg-9-161-2012.pdf |
|
|
|
Zusammenfassung |
Evapotranspiration (ET) flux constitutes a major component of both the water
and energy balances at the land surface. Among the many factors that control
evapotranspiration, phenology poses a major source of uncertainty in
attempts to predict ET. Contemporary approaches to ET modeling and monitoring
frequently summarize the complexity of the seasonal development of
vegetation cover into static phenological trajectories (or climatologies)
that lack sensitivity to changing environmental conditions. The Event Driven
Phenology Model (EDPM) offers an alternative, interactive approach to
representing phenology. This study presents the results of an experiment
designed to illustrate the differences in ET arising from various techniques
used to mimic phenology in models of land surface processes. The experiment
compares and contrasts two realizations of static phenologies derived from
long-term satellite observations of the Normalized Difference Vegetation
Index (NDVI) against canopy trajectories produced by the interactive EDPM
trained on flux tower observations. The assessment was carried out through
validation of predicted ET against records collected by flux tower
instruments. The VegET model (Senay, 2008) was used as a framework to
estimate daily actual evapotranspiration and supplied with seasonal canopy
trajectories produced by the EDPM and traditional techniques. The
interactive approach presented the following advantages over phenology
modeled with static climatologies: (a) lower prediction bias in crops; (b) smaller root mean square error in daily ET – 0.5 mm per day on average;
(c) stable level of errors throughout the season similar among different land
cover types and locations; and (d) better estimation of season duration and
total seasonal ET. |
|
|
Teil von |
|
|
|
|
|