Development of a SRC simulation model and calibration for poplar (Populus spp.)

Development of a SRC simulation model and calibration for poplar (Populus spp.) Facciotto1 Gianni, Rocca2 Alvaro, Bergante1 Sara, Giovanardi2 Romano, Baldini2 Mario, Danuso2 Francesco 1 Consiglio per la Ricerca e Sperimentazion in Agricoltura – Unità di Ricerca per le produzioni legnose fuori foresta. Strada Frassineto Po, 35, 15033 Casale Monferrato (AL) (Italy). Email: gianni.facciotto@entecra.it. Tel. +39 0142 330900. Fax +39 0142 55580 2 Dipartimento di Scienze Agrarie e Ambientali, Università di Udine, Via delle Scienze 208, 33100 Udine (Italy). Email: francesco.danuso@uniud.it. Tel. +39 0432 558614. Fax +39 0432 558603 Introduction In the last years, starting from 2002, short rotation coppice (SRC) crops in Italy showed a rapid increase up to about 7000 ha, 90% of which formed by poplar. In Italy, SRC poplar is the 10% as compared with the traditional poplar stand and its production is mainly used in energy plants for heat and power cogeneration. Many experiments have been already carried out and the obtained data showed continuous yield increasing, due to genetic and cultural practices. On the other hand, the commercial stands showed a strong yield variability, to be related to the environmental interaction between soil and climate. As a consequence, the understanding of these interactions and the possibility to forecast yield or to optimize the combination a genotype x environment is important and could be made by simulation models. Many simulation models for annual crops have been already developed (CropSyst, Epic, Stics, CSS, etc.) but less common are models for perennial crops; moreover, the few model available for SRC are generally with an annual step, not able to represent the system with a sufficient detail. In these work a new SRC simulation model is presented and calibrated with data coming from a multiannual experiments performed in North Italy. Methods and materials Different poplar clones have been cultivated in two North-Italy locations (Casale Monferrato, AL; Osoppo, UD) from 2002 to 2011, with biennial and 5-year harvesting cycle with 4 replications. Measurements performed on each plot have been planting time, sprouting dates, leaf dropping time, above ground biomass for stems+branches and leaves. At each harvest, biomass yield (t/ha), moisture content and high calorific value have been also detected. Non-destructive growth analysis has been also performed on some plots of two-years and five-years harvesting cycle, estimating the above ground biomass every 15 days during the growing season. In order to calibrate the model, soil parameters (texture, hydrological parameters, soil organic matter (carbon and nitrogen), soil depth) and daily meteorological variables (maximum and minimum temperatures, rainfall, global radiation and reference evapotranspiration) have also obtained. A model for SRC crop has been developed (SRCsim) with the aim to represent multiannual woody crops under different management systems and environmental conditions, with a daily time step. SRCsim requires daily meteorological data (as above indicated), soil parameters and time and intensity agricultural practices. Management techniques currently considered are planting, irrigation, nitrogen fertilization and harvest. The simulation results generated by the model are the above-ground (leaf and stems+branches) and root biomass (coarse and fine), soil water and nitrogen dynamics, carbon and energy balance. The model has been developed using the SEMoLa simulation language and is based on the previous developed crop model MiniCSS. The model is sensitive to water and temperature stresses and also to the soil nitrogen availability. Results Model SRCsim has been improved and calibrated using the crop data from the experiments performed in Casale Monferrato. The model resulted to be flexible and suitable to well represent the experimental biomass growth data (figure 1) wen calibrated. The most sensitive parameters, used to improve the model performance, have been phonological parameters, radiation use efficiency and crop coefficients for water consumption. After calibration, a validation with independent data from the other location (Osoppo ) and other trials from Casale Monferrato has been performed. Also in this case the models proved to be able to predict biomass yield of poplar SRC, when parametrised for the specific environment. Conclusions The model SRCsim can be used for management and planning purposes, e.g., to preliminarily estimating the biomass production of the territory and its variability. In fact, the model can be used to perform Monte Carlo simulation to evaluate the statistical properties of the yields. Other planning tasks can be the optimal location of the processing plants or the identification of the collecting district and the optimization of the crop management techniques. The model is freely available from the authors. SRCsim will be included in a multilingual software application