Abstract

Ecosystems in the Alps are considered hotspots of climate and land use change. In addition, alpine regions are usually characterized by complex morphologies, which make measurement (especially in the long term) of states and fluxes of water, energy and matter particularly challenging. Therefore, there is a limited availability of information and modelling tools to characterize actual ecosystem conditions, and to simulate future scenarios.Despite the fact that in high altitude areas meteorological forcing is extremely variable in space and time, much of the variability of actual evapotranspiration (AET) in the above-mentioned regions is largely related to land surface properties such as aspect, shadowing and slope. Therefore, a simple, radiation driven, calibration free, bucket hydrological model for predicting AET and estimating the soil–water balance is proposed here (i.e. CLIME-MG). Conventional meteorological data from a network of automatic weather stations together with a 10 m digital terrain model (aggregated at 30 m), and a land cover map are used to inform the model. All the parameters and values required are obtained or calculated from data provided in literature.CLIME-MG has proved to perform well for AET modelling of mountain grassland. The model is validated both temporally and spatially. Temporal validation of AET is performed using eddy-covariance datasets from two different high mountain sites: a sunny and steep abandoned pasture facing S-E at an altitude of 1730 m, and a meadow with a S-SE aspect located at an altitude of 2555 m. Spatial validation is performed by comparing CLIME-MG simulations with the Landsat-based METRIC model evapotranspiration output. Results show good daily temporal performance, especially in wetter periods with recurring rainfall events. Sensitivity of the correlation coefficient between measured and modeled AET values to some key parameters such as effective porosity, and the vegetation and stress coefficients was found to be quite low. Spatial validation of hourly results shows SPAEF values in the range 0.21–0.34 between the outputs of the two models (with a similar spatial structure ruled by the DTM). Boxplots of deviations between CLIME and METRIC with respect to morphological characteristics has highlighted some dependency on elevation and slope (but not on aspect and soil depth); this suggests an opportunity to refine the modelisation of the grassland AET processes. Finally, spatial results demonstrated the non-sensitivity of the proposed model to local elevation and to the distance from the meteorological stations.

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