 |
| Titel |
Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area |
| VerfasserIn |
J. Cristóbal, R. Poyatos, M. Ninyerola, P. Llorens, X. Pons |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 15, no. 5 ; Nr. 15, no. 5 (2011-05-25), S.1563-1575 |
| Datensatznummer |
250012789
|
| Publikation (Nr.) |
 copernicus.org/hess-15-1563-2011.pdf |
|
|
|
|
|
| Zusammenfassung |
| Evapotranspiration monitoring allows us to assess the environmental stress
on forest and agricultural ecosystems. Nowadays, Remote Sensing and
Geographical Information Systems (GIS) are the main techniques used for
calculating evapotranspiration at catchment and regional scales. In this
study we present a methodology, based on the energy balance equation
(B-method), that combines remote sensing imagery with GIS-based climate
modelling to estimate daily evapotranspiration (ETd) for several dates
between 2003 and 2005. The three main variables needed to compute ETd
were obtained as follows: (i) Land surface temperature by means of the
Landsat-5 TM and Landsat-7 ETM+ thermal band, (ii) air temperature by means
of multiple regression analysis and spatial interpolation from
meteorological ground stations data at satellite pass, and (iii) net
radiation by means of the radiative balance. We calculated ETd using
remote sensing data at different spatial and temporal scales (Landsat-7
ETM+, Landsat-5 TM and TERRA/AQUA MODIS, with a spatial resolution of 60,
120 and 1000 m, respectively) and combining three different approaches to
calculate the B parameter, which represents an average bulk conductance for
the daily-integrated sensible heat flux. We then compared these estimates
with sap flow measurements from a Scots pine (Pinus sylvestris L.) stand in a Mediterranean
mountain area. This procedure allowed us to better understand the
limitations of ETd modelling and how it needs to be improved,
especially in heterogeneous forest areas. The method using Landsat data
resulted in a good agreement, R2 test of 0.89, with a mean RMSE value
of about 0.6 mm day−1 and an estimation error of ±30 %. The poor
agreement obtained using TERRA/AQUA MODIS, with a mean RMSE value of 1.8 and
2.4 mm day−1 and an estimation error of about ±57 and 50 %,
respectively. This reveals that ETd retrieval from coarse resolution
remote sensing data is troublesome in these heterogeneous areas, and
therefore further research is necessary on this issue. Finally, implementing
regional GIS-based climate models as inputs in ETd retrieval have has
provided good results, making possible to compute ETd at regional
scales. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|