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Author |
Lorite, I.J.; Gabaldon-Leal, C.; Ruiz-Ramos, M.; Belaj, A.; de la Rosa, R.; Leon, L.; Santos, C. |
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Title |
Evaluation of olive response and adaptation strategies to climate change under semi-arid conditions |
Type |
Journal Article |
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Year |
2018 |
Publication  |
Agricultural Water Management |
Abbreviated Journal |
Agric. Water Manage. |
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Volume |
204 |
Issue |
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Pages |
247-261 |
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Keywords |
Irrigation requirements; Yield; Irrigation water productivity; Olive; Climate change; Olea-Europaea L.; Different Irrigation Regimes; Water Deficits; Iberian; Peninsula; CO2 Concentration; Potential Growth; Atmospheric CO2; Southern Spain; Change Impacts; River-Basin |
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Abstract |
AdaptaOlive is a simplified physically-based model that has been developed to assess the behavior of olive under future climate conditions in Andalusia, southern Spain. The integration of different approaches based on experimental data from previous studies, combined with weather data from 11 climate models, is aimed at overcoming the high degree of uncertainty in the simulation of the response of agricultural systems under predicted climate conditions. The AdaptaOlive model was applied in a representative olive orchard in the Baeza area, one of the main producer zone in Spain, with the cultivar ‘Picual’. Simulations for the end of the 21st century showed olive oil yield increases of 7.1 and 28.9% under rainfed and full irrigated conditions, respectively, while irrigation requirements decreased between 0.5 and 6.2% for full irrigation and regulated deficit irrigation, respectively. These effects were caused by the positive impact of the increase in atmospheric CO2 that counterbalanced the negative impacts of the reduction in rainfall. The high degree of uncertainty associated with climate projections translated into a high range of yield and irrigation requirement projections, confirming the need for an ensemble of climate models in climate change impact assessment. The AdaptaOlive model also was applied for evaluating adaptation strategies related to cultivars, irrigation strategies and locations. The best performance was registered for cultivars with early flowering dates and regulated deficit irrigation. Thus, in the Baeza area full irrigation requirements were reduced by 12% and the yield in rainfed conditions increased by 7% compared with late flowering cultivars. Similarly, regulated deficit irrigation requirements and yield were reduced by 46% and 18%, respectively, compared with full irrigation. The results confirm the promise offered by these strategies as adaptation measures for managing an olive crop under semi-arid conditions in a changing climate. |
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Address |
2018-06-28 |
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English |
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ISSN |
0378-3774 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5204 |
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Author |
Strauss, F.; Moltchanova, E.; Schmid, E. |
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Title |
Spatially explicit modeling of long-term drought impacts on crop production in Austria |
Type |
Journal Article |
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Year |
2013 |
Publication |
American Journal of Climate Change |
Abbreviated Journal |
American Journal of Climate Change |
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Volume |
2 |
Issue |
3 |
Pages |
1-11 |
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Keywords |
Long-Term Drought Modeling; Dry Day Index; Biophysical Impacts; Spatial Variability; EPIC; Austria |
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Abstract |
Droughts have serious and widespread impacts on crop production with substantial economic losses. The frequency and severity of drought events may increase in the future due to climate change. We have developed three meteorological drought scenarios for Austria in the period 2008-2040. The scenarios are defined based on a dry day index which is combined with bootstrapping from an observed daily weather dataset of the period 1975-2007. The severity of long-term drought scenarios is characterized by lower annual and seasonal precipitation amounts as well as more sig- nificant temperature increases compared to the observations. The long-term impacts of the drought scenarios on Aus- trian crop production have been analyzed with the biophysical process model EPIC (Environmental Policy Integrated Climate). Our simulation outputs show that—for areas with historical mean annual precipitation sums below 850 mm— already slight increases in dryness result in significantly lower crop yields i.e. depending on the drought severity, be- tween 0.6% and 0.9% decreases in mean annual dry matter crop yields per 1.0% decrease in mean annual precipitation sums. The EPIC results of more severe droughts show that spring and summer precipitation may become a limiting factor in crop production even in regions with historical abundant precipitation. |
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2167-9495 |
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CropM, ft_macsur |
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MA @ admin @ |
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4507 |
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Author |
Hutchings, N.J.; Özkan Gülzari, Ş.; de Haan, M.; Sandars, D. |
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Title |
How do farm models compare when estimating greenhouse gas emissions from dairy cattle production |
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Journal Article |
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Year |
2018 |
Publication |
Animal |
Abbreviated Journal |
Animal |
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Volume |
12 |
Issue |
10 |
Pages |
2171-2180 |
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Keywords |
dairy cattle; farm-scale; model; greenhouse gas; Future Climate Scenarios; Systems-Analysis; Milk-Production; Crop; Production; Mitigation; Intensity; Impacts |
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Abstract |
The European Union Effort Sharing Regulation (ESR) will require a 30% reduction in greenhouse gas (GHG) emissions by 2030 compared with 2005 from the sectors not included in the European Emissions Trading Scheme, including agriculture. This will require the estimation of current and future emissions from agriculture, including dairy cattle production systems. Using a farm-scale model as part of a Tier 3 method for farm to national scales provides a more holistic and informative approach than IPCC (2006) Tier 2 but requires independent quality control. Comparing the results of using models to simulate a range of scenarios that explore an appropriate range of biophysical and management situations can support this process by providing a framework for placing model results in context. To assess the variation between models and the process of understanding differences, estimates of GHG emissions from four farm-scale models (DailyWise, FarmAC, HolosNor and SFARMMOD) were calculated for eight dairy farming scenarios within a factorial design consisting of two climates (cool/dry and warm/wet) x two soil types (sandy and clayey) x two feeding systems (grass only and grass/maize). The milk yield per cow, follower cow ratio, manure management system, nitrogen (N) fertilisation and land area were standardised for all scenarios in order to associate the differences in the results with the model structure and function. Potential yield and application of available N in fertiliser and manure were specified separately for grass and maize. Significant differences between models were found in GHG emissions at the farm-scale and for most contributory sources, although there was no difference in the ranking of source magnitudes. The farm-scale GHG emissions, averaged over the four models, was 10.6 t carbon dioxide equivalents (CO(2)e)/ha per year, with a range of 1.9 t CO(2)e/ha per year. Even though key production characteristics were specified in the scenarios, there were still significant differences between models in the annual milk production per ha and the amounts of N fertiliser and concentrate feed imported. This was because the models differed in their description of biophysical responses and feedback mechanisms, and in the extent to which management functions were internalised. We conclude that comparing the results of different farm-scale models when applied to a range of scenarios would build confidence in their use in achieving ESR targets, justifying further investment in the development of a wider range of scenarios and software tools. |
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2019-01-07 |
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ISSN |
1751-7311 |
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Notes |
TradeM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5212 |
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Author |
Pasqui, M.; Di Giuseppe, E. |
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Title |
Climate change, future warming, and adaptation in Europe |
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Journal Article |
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Year |
2019 |
Publication |
Animal Frontiers |
Abbreviated Journal |
Animal Frontiers |
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Volume |
9 |
Issue |
1 |
Pages |
6-11 |
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Keywords |
heat waves; impacts; perception; vulnerability; temperature-humidity index; extremes indexes |
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Abstract |
In recent decades, the increased temperatures reported in Europe and in the Mediterranean basin represent one of the clearest footprints of climate change along with increased frequency of heat waves. These climate modifications put the environment and human activities under strong pressure with a resulting need for designing new adaptation and mitigation strategies. The climate change challenge is unprecedented for humanity and is recognized as a priority topic for future research. Changes in the way we think and behave are critical challenges at the global and regional levels. |
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2020-06-08 |
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LiveM, ft_macsur |
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Call Number |
MA @ admin @ |
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5236 |
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Author |
Park, S.K.; Sungmin, O.; Cassardo, C. |
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Title |
Soil temperature response in Korea to a changing climate using a land surface model |
Type |
Journal Article |
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Year |
2017 |
Publication |
Asia-Pacific Journal of Atmospheric Sciences |
Abbreviated Journal |
Asia-Pacific Journal of Atmospheric Sciences |
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Volume |
53 |
Issue |
4 |
Pages |
457-470 |
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Keywords |
Land surface process; soil temperature; climate change; soil-vegetation-atmosphere transfer (SVAT) scheme; University of TOrino model of land Process Interaction with Atmosphere (UTOPIA); REGIONAL CLIMATE; SNOW COVER; WATER-RESOURCES; SOCIOECONOMIC SCENARIOS; QUANTITATIVE-ANALYSIS; MESOSCALE MODEL; SRES EMISSIONS; FUTURE CLIMATE; CHANGE IMPACTS; SOUTH-AMERICA |
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Abstract |
The land surface processes play an important role in weather and climate systems through its regulation of radiation, heat, water and momentum fluxes. Soil temperature (ST) is one of the most important parameters in the land surface processes; however, there are few extensive measurements of ST with a long time series in the world. According to the CLImatology of Parameters at the Surface (CLIPS) methodology, the output of a trusted Soil-Vegetation- Atmosphere Transfer (SVAT) scheme can be utilized instead of observations to investigate the regional climate of interest. In this study, ST in South Korea is estimated in a view of future climate using the output from a trusted SVAT scheme – the University of TOrino model of land Process Interaction with Atmosphere (UTOPIA), which is driven by a regional climate model. Here characteristic changes in ST are analyzed under the IPCC A2 future climate for 2046-2055 and 2091-2100, and are compared with those under the reference climate for 1996-2005. The UTOPIA results were validated using the observed ST in the reference climate, and the model proved to produce reasonable ST in South Korea. The UTOPIA simulations indicate that ST increases due to environmental change, especially in air temperature (AT), in the future climate. The increment of ST is proportional to that of AT except for winter. In wintertime, the ST variations are different from region to region mainly due to variations in snow cover, which keeps ST from significant changes by the climate change. |
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Address |
2017-12-21 |
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English |
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ISSN |
1976-7633 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5182 |
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