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Ventrella, D., Charfeddine, M., Giglio, L., & Castellini, M. (2012). Application of DSSAT models for an agronomic adaptation strategy under climate change in Southern of Italy: optimum sowing and transplanting time for winter durum wheat and tomato. Ital. J. Agron., 7(1), 16.
Abstract: Many climate change studies have been carried out in different parts of the world to assess climate change vulnerability and adaptation capacity of agricultural crops for certain environments characterized from climatic, pedological and agronomical point of view. The objective of this study was to analyse the productive response of winter durum wheat and tomato to climate change and sowing/transplanting time in one of the most productive areas of Italy (i.e. Capitanata, Puglia), using CERES-Wheat and CROPGRO cropping system models. Three climatic datasets were used: i) a single dataset (50 km x 50 km) provided by the JRC European centre for the period 1975- 2005; two datasets from HadCM3 for the IPCC A2 GHG scenario for time slices with +2°C (centred over 2030-2060) and +5°C (centred over 2070-2099), respectively. All three datasets were used to generate synthetic climate series using a weather simulator (model LARS-WG). No negative yield effects of climate change were observed for winter durum wheat with delayed sowing (from 330 to 345 DOY) increasing the average dry matter grain yield under forecasted scenarios. Instead, the warmer temperatures were primarily shown to accelerate the phenology, resulting in decreased yield for tomato under the + 5°C future climate scenario. In general, under global temperature increase by 5°C, early transplanting times could minimize the negative impact of climate change on crop productivity but the intensity of this effect was not sufficient to restore the current production levels of tomato cultivated in southern Italy.
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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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Kollas, C., Kersebaum, K. C., Nendel, C., Manevski, K., Müller, C., Palosuo, T., et al. (2015). Crop rotation modelling—A European model intercomparison. European Journal of Agronomy, 70, 98–111.
Abstract: • First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects.
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Ventrella, D., Giglio, L., Charfeddine, M., & Dalla Marta, A. (2015). Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy. Italian Journal of Agrometeorology, 20(1), 33–44.
Abstract: In this study at the regional scale, the model DSSAT CERES-Wheat was applied in order to simulate the cultivation of winter durum wheat (WW) and to estimate the green water (GW) and the blue water (BW) through a dual-step approach (with and without supplemental irrigation). The model simulation covered a period of 30 years for three scenarios including a reference period and two future scenarios based on forecasted global average temperature increase of 2 and 5 degrees C. The GW and BW contribution for evapo transpiration requirement is presented and analyzed on a distributed scale related to the Puglia region (Southern Italy) characterized by high evaporative demand of the atmosphere. The GW component was dominant compared to BW, covering almost 90% of the ETc of WW Under a Baseline scenario the weight BW was 11%, slightly increased in the future scenarios. GW appeared dependent on the spatial and temporal distribution of rainfall during the crop cycle, and to the hydraulic characteristics of soil for each calculation unit. After considering the effects of climate change on irrigation requirement of WW we carried out an example of analysis in order to verify the economic benefit of supplemental irrigation for WW cultivation. The probability that irrigation generates a negative or zero income ranged between 55 and 60% and 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.
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Sollitto, D., De Benedetto, D., Castrignanò, A., Crescimanno, G., Provenzano, G., & Ventrella, D. (2012). Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy). Ital. J. Agron., 7(1), 4.
Abstract: Salinization is one of the most serious problems confronting sustainable agriculture in semi-arid and arid regions. Accurate mapping of soil salinization and the associated risk represent a fundamental step in planning agricultural and remediation activities. Geostatistical analysis is very useful for soil quality assessment because it makes it possible to determine the spatial relationships between selected variables and to produce synthetic maps of spatial variation. The main objective of this paper was to map the soil salinization risk in the Delia-Nivolelli alluvial basin (south-western Sicily, southern Italy), using multivariate geostatistical techniques and a set of topographical, physical and soil hydraulic properties. Elevation data were collected from existing topographic maps and analysed preliminarily to improve the estimate precision of sparsely sampled primary variables. For interpolation multi-collocated cokriging was applied to the dataset, including textural and hydraulic properties and electrical conductivity measurements carried out on 128 collected soil samples, using elevation data as auxiliary variable. Spatial dependence among elevation and physical soil properties was explored with factorial kriging analysis (FKA) that could isolate and display the sources of variation acting at different spatial scales. FKA isolated significant regionalised factors which give a concise description of the complex soil physical variability at the different selected spatial scales. These factors mapped, allowed the delineation of zones at different salinisation risk to be managed separately to control and prevent salinization risk. The proposed methodology could be a valid support for land use and soil remediation planning at regional scale.
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