|CASTELLI, M. - Free University Of Bozen-Bolzano|
|WOHLFART, G. - University Of Innsbruck|
|BERTOLDI, G. - Collaborator|
|HAMMERLE, A. - University Of Innsbruck|
|ZHAO, P. - University Of Innsbruck|
|NIEDRIST, G. - Free University Of Bozen-Bolzano|
|ZEBISCH, M. - Free University Of Bozen-Bolzano|
|NOTARNICOLA, C. - Free University Of Bozen-Bolzano|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/22/2018
Publication Date: 3/19/2018
Citation: Castelli, M., Anderson, M.C., Yang, Y., Wohlfart, G., Bertoldi, G., Hammerle, A., Zhao, P., Niedrist, G., Zebisch, M., Notarnicola, C. 2018. Two source energy balance modeling of evapotranspiration in Alpine grasslands. Remote Sensing of Environment. 209:327-342. https://doi.org/10.1016/j.rse.2018.02.062.
Interpretive Summary: Climate shifts are altering drought cycles and water balance in the European Alps. Droughts in the inner-alpine dry valleys are becoming more frequent, and snowpack contributions to the regional water balance are changing as average temperatures increase. To better assess the large-scale impacts of changing climate on water resources and ecosystem health, robust satellite-based remote sensing methods are desired for wide area coverage. This paper evaluates the performance of a satellite-based method for mapping evapotranspiration (ET) at high spatial and temporal resolution, fusing multi-sensor estimates acquired at varying spatial and temporal resolutions. ET image timeseries at 30m to 1km spatial resolution and daily timesteps were generated over a grassland ecosystem in South Tyrol (Italy) for the period 2012-2015. Model estimates were compared with observations collected at two different measurement tower sites within the modeling region. The results show that the 1km estimates agreed reasonably with the tower data, but small-scale hetereogeneity within the landscape limited our ability to perform an robust accuracy assessment at that scale. When the ET models were run at finescale, using inputs collected at the towers themselves, the model-measurement agreement improved, demonstrating the utility of the modeling system itself. The study also demonstrated that routine monitoring via satellite in this region will be limited by persistent cloud-cover, impacting the frequency of clear-sky image acquistion potential particularly at the finer spatial resolutions where landsurface heterogeneity is reasonably resolved.
Technical Abstract: This work aims to assess a diagnostic approach which links evapotranspiration (ET) to land surface temperature (LST) measured by thermal remote sensing in the Alps. We estimated gridded ET, from field (30 m) to regional (1 km) scales, and we performed a specific study on grassland ecosystems in the Alps in South Tyrol (Italy), to evaluate the model sensitivity to different land managements. The energy balance model TSEB ALEXI (Two Source Energy Balance Atmosphere Land EXchange Inverse) was first applied to Meteosat satellite data. Then ET was estimated by the flux disaggregation procedure DisALEXI, driven by MODIS and Landsat LST retrievals, which has never been applied before in a mountain region. We validated the model against eddy-covariance (EC) measurements from established stations in the Alps, and analyzed the main limitations which affect the model performances in mountainous regions in order to suggest some adaptations for improving ET retrieval in complex terrain. The error in the retrieval of latent heat flux at the satellite overpass time was between 100 and 180 Wm-2 (30-50% of the mean value) for MODIS-based latent heat, while it was not possible to evaluate Landsat based fluxes because of the lack of cloud free pixels at the measurement stations. In contrast, when we applied the TSEB model at the plot scale, with local meteorological and LST data, the error in the retrieval of daytime latent heat was between 28 and 104 Wm-2, with lower errors when the measured fluxes were corrected for the lack of closure in the energy balance. From MODIS ET, we calculated a thermal water stress index, the ratio between actual and potential ET, fPET, and investigated whether it captured differences between managed and unmanaged grasslands. Results show that in the Alps i) moderate resolution thermal data can be used to monitor evaporative stress at the regional scale; ii) the spatial-temporal evolution of ET can be characterized from MODIS and Landsat thermal data with limitations which are due to the low availability of clear-sky scenes and to the small-scale (~10 m) changes in soil moisture, topography and canopy density, which control ET patterns in mountainous regions; iii) solar radiation and leaf area index are critical variables which strongly affect the accuracy of the modeled energy fluxes.