The SWAMP project published a paper in the 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor 2020) reporting an experience aimed at evaluating the Sensitivity of the agro-hydrological model CRITERIA-1D to the Leaf Area Index parameter for precision irrigation management. The CRITERIA-1D model is currently running into the SWAMP platform for estimating crop water requirements in the Italian pilot. The leaf area index is an input data of the model and is used to characterize the plant status and to represent its developing stages. To assess the importance of the LAI parameter on the estimation of the plant water needs, the model was set-up to mimic the agro-environmental conditions of the selected pear orchard. Two scenarios were defined: in the first reference scenario literature LAI values were used (Sref); in the second scenario measured LAI values (SLAI), collected with the AccuPAR LP80 ceptometer, were replaced to reproduce the real filed conditions. During the summer 2019, four sampling campaigns were conducted in the pear orchard and LAI measurements were collected in 16 points in a regular grid; for every point six measurements were taken around the plant.
Results of the simulations with the model are presented in the two figures below. As it is shown, for the modified scenario (SLAI) LAI values were lower than those of the reference scenario (Sref). This is accompanied by a decrease of the plant’s potential transpiration (left graph) resulting in less water demand for the modified scenario (SLAI).
Looking at the irrigation water requirements, a lower number of irrigation events compared to the reference scenario have been quantified. Consequently, a lower total irrigation water need is also estimated, as it is possible to see in the right figure.
As general conclusion, the results confirmed the sensitivity of water need estimation CRITERIA-1D model output to the LAI values. Following this analysis, the model into the SWAMP platform has been updated using LAI ground-based measurements, to better represent the actual field condition as this parameter affects the management of irrigation water and its consequent saving.