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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Van Oijen, M. (2015). Methods for risk analysis and spatial upscaling of process-based models: Experiences from projects Carbo-Extreme and GREENHOUSE (Vol. 5).
Abstract: In the recently finished EU-funded project Carbo-Extreme, we developed a simple probabilistic method for quantifying vulnerabilities and risks to ecosystems (http://iopscience.iop.org/1748-9326/8/1/015032). The method defines risk as expected loss due to environmental hazards, and shows how such risk can be calculated as the product of ecosystem vulnerability and hazard probability. The method was used with six different vegetation models to estimate current and future drought risks for crops, grasslands and forests across Europe (http://www.biogeosciences.net/11/6357/2014/bg-11-6357-2014.html).In the still ongoing UK-funded project GREENHOUSE, the focus is on spatial upscaling of local measurements and model predictions of greenhouse gas emissions to wider regions. As part of this work, we are comparing different model upscaling methods – ranging from naive input aggregation to geostatistics – and quantify the uncertainties associated with the upscaling. This work builds on an earlier inventory of model upscaling methods that was produced in a collaboration of CEH-Edinburgh and the University of Bonn (https://www.stat.aau.at/Tagungen/statgis/2009/StatGIS2009Van%20Oijen1.pdf). Here we show a comparison of the methods using model predictions for the border region of England and Scotland. No Label
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van Middelkoop, J. C., & Kipling, R. P. (2017). Modelling the impact of climate change on livestock productivity at the farm-scale: An inventory of LiveM outcomes (Vol. 10).
Abstract: The report presented here provides an inventory of reports and conference papers produced by the partners of the livestock and grassland modelling theme (LiveM) of the Modelling European Agriculture with Climate Change for Food Security (MACSUR) knowledge hub. The findings presented illustrate the diverse nature of the multidisciplinary LiveM research community, and provide a reference source for those seeking to identify and pull out farm-level modelling outputs from the work of MACSUR and its partners. The survey of farm-scale outputs from LiveM revealed the interdependent, dual role of a knowledge hub: to increase the capacity of modelling to meet stakeholder and societal needs under climate change, and to apply that increased capacity to provide new understanding and solutions at the policy and (the focus here) farm scale. While capacity building work across disciplines is time-consuming, difficult, and to a large extent invisible to stakeholders, such work is vital to ensuring that subsequent scientific outcomes reflect best practice, and integrated expertise. Long term, sustained funding of network-based capacity building activities is highlighted as essential to ensuring that the farm-scale modelling work highlighted here can continue to build on ongoing improvements in model quality, flexibility and stakeholder relevance.
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Van der Linden, A. (2016). Exploring grass-based beef production under climate change by integration of grass and cattle growth models (Vol. 8 C6 -).
Abstract: Conference presentation PDF
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Trnka, M., Kersebaum, K., Christian,, & Olesen, J. E. (2015). Description of the compiled experimental data available in the MACSUR CropM database (Vol. 6).
Abstract: The input data necessary for crop model simulations and data for their calibration/validation (and thus requirements for observations and measurements in suitable experiments) have been collected through out the project together with data for additional analysis of abiotic factors influencing yields. A list of possible dataset was collated in the first year of project however very few of the existing datasets were found usable for the crop model simulation as they fell short of the requirements defined in the part 2.3. However database has been populated as planned with the results of the ongoing MACSUR studies and will serve in the same way for the MACSUR 2 duration. No Label
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