Abstract

This article presents the structure and results of a simplified model (VISTOCK) for simulating grass growth and water dynamics of grassland systems. The model, based on a process-based approach coupled with proximal (SKR 1800 2-Channel Light Sensor) and remote (Sentinel-2) NDVI-derived data for estimating LAI, simulates aboveground biomass (AGB), net primary production (NPP), evapotranspiration (ET), and the fraction of transpirable water in soil (FTSW). VISTOCK simulated a grassland system with few meteorological data (i.e., minimum and maximum daily temperatures, precipitation, global solar radiation), considering limitations to vegetation growth due to thermal and water stresses. It was calibrated for a natural alpine grassland in Italy (site T) during the most contrasting meteorological seasons of the dataset (2012, 2017, and 2018). It was then evaluated for the remaining years at site T (2013, 2014, 2015, and 2016) and for other two sites in Italy (sites B1, B2 and M) with different soil and climate conditions and diverse management strategies (2020 and 2021). VISTOCK accurately predicted AGB during the growing season (RMSE = 445, 240, 219, 365 kg DM ha-1 for T, M, B1, and B2, respectively) as well as for NPP, ET, and FSTW at site T. Simulation results suggest the ability of the model to simulate grassland in diverse environments with few inputs and parameters to be calibrated. The model’s simplified structure, combined with easy-to obtain input data and easy applicability, encourages its wider use for out- and/or upscaling and decision making.

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