Multi-year simulation of Mediterranean forest transpiration by the integration of NOAA-AVHRR and ancillary data

The estimation of transpiration fluxes through wide vegetated land surfaces is of great importance for the proper planning and management of environmental resources, particularly in areas where water is a main limiting factor during at least part of the growing cycle. While remotely sensed techniques cannot directly measure these fluxes, they can provide useful information on vegetation variables such as Leaf Area Index (LAI), which are functionally related to the mentioned processes. The aims of the present work were: ( a) to illustrate the use of multi-temporal LAI profiles derived from National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI) data as input for a biogeochemical model (Forest-BGC) which simulates the main processes of forest vegetation ( transpiration and photosynthesis); and (b) to analyse the sensitivity of the calibrated model to its main driving variables ( meteorological data and NDVI-derived LAI profiles) in order to assess their relative importance for operational transpiration monitoring. In particular, the model was applied to two oak stands in the Tuscany Region ( central Italy), which are representative of Mediterranean forests and for which a calibration phase had already been performed. Simulations were carried out for a 15-year period ( 1986 - 2000) using as inputs daily meteorological data and NDVI-derived monthly LAI profiles. The sensitivity of the model to both input types was then assessed through other model runs with fixed values of the two variables. The results of these experiments indicated that the remotely sensed LAI estimates are the main determinant of simulated transpirations, especially during the Mediterranean arid season ( summer) when water resources are the primary limiting factor for vegetation development.