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Giglio, L., & Ventrella, D. (2012). Vulnerabilità di frumento duro e pomodoro ed analisi di adattamento agronomico ai cambiamenti climatici nel territorio agricolo Pugliese. In: De Mastro G.; Ventrella D.; Verdini L. (Eds). 2012 Atti dell 480-482..
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Ventrella, D. (2015). Climate change impact on green and blue water consumptive use for winter durum wheat and tomato cultivated in Southern Italy (Vol. 5).
Abstract: In this study at regional scale, the model DSSAT was applied in order to simulate the cultivation of winter durum wheat and tomato to estimate the green water and the blue water through a dual-step approach (with and without supplemental irrigation). The model simulation covered a period of 30 years in three scenario including a reference period and two future scenarios based on forecasted global average temperature increase of 2 and 5°C. In this paper GW e BW contribution for evapotranspiration requirement is presented and analyzed on a distributed scale related to Puglia region (Southern Italy) characterized by high evaporative demand of the atmosphere. For winter durum wheat the GW component was predominant compared to BW, covering almost 90% of the ETc of WW. Under Baseline scenario the weight of BW was of 11%, slightly increasing in the future scenarios. After considering the probability the climate change determine an increase of irrigation practice for WW from climatic point of view we carried out an example of analysis in order to verify the economical convenience of supplemental irrigation for WW cultivation. The probability that irrigation has a negative or zero income ranged between 55 and 60% and the climate change did not impact the profitability of irrigation for WW as simulated for the economic and agro-pedoclimatic conditions of Puglia region considered in this study.For tomato, in the baseline and future scenarios affected by global warming, the analysis of ET components showed with strong evidence the importance of irrigation that is confirmed as irreplaceable practice for obtaining sustainable yield from productive and economical point of view.GW and BW, both in the case of wheat and tomato, appeared dependent on the spatial and temporal distribution of rainfall during the crop cycle, but also on the hydraulic characteristics of soils corresponding to each calculation unit. No Label
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Ventrella, D. (2016). Durum wheat yield and protein stability depending on residue management in a long term experiment in Southern Italy Edinburgh. Proceeding of ESA 14 – Growing landscapes – Cultivating innovative agricultural systems. Edinburgh (UK).
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Roggero, P. P., Pulina, A., Baldoni, G., Basso, B., Berti, A., Orlandini, S., et al. (2014). IC-FAR: Linking Long Term Observatories with Crop Systems Modeling For a better understanding of Climate Change Impact, and Adaptation Strategies for Italian Cropping Systems. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The IC-FAR project (2013-2016), funded by the Italian ministry of University, Research and Education, aims to use datasets from 16 Italian long term agronomic experiments (LTEs) to assess the reliability of different cropping system models over a range of Mediterranean environments and cropping systems. The selected models will be used for scenario and uncertainty analyses vs near-future climate change. The LTEs are located in seven sites: Turin, Padua, Bologna, Ancona, Pisa, Perugia, Foggia. The project’s is linked to international projects such as MACSUR, AgMIP, ANAEE, ESFRI and GRA, and has model developer teams as associate partners. IC-FAR is structured in five WPs. WP1 is focused on building a common dataset and sampling protocols. The field data will be implemented in the WP2 to calibrate, validate and assess the performances of different models across Italian environments. An uncertainty analysis will be performed in relation to the model types, cropping system typologies and climate scenarios (WP3). WP4 and WP5 are focused on capacity building on modeling and on dissemination, including networking with other European LTE platforms (WP4), and to the project coordination (WP5). The next step of IC-FAR will be the design and realization of a special issue summarizing a selection of the most important results from the LTEs, that will be the starting point towards the full implementation of the data sharing policy of this project.
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Kersebaum, K. C., Kollas, C., Bindi, M., Palosuo, T., Wu, L., Sharif, B., et al. (2014). Model inter-comparison on crop rotation effects – an intermediate report. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed.
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