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Cortignani, R.; Dono, G. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Simulation of the impact of greening measures in an agricultural area of the southern Italy |
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Journal Article |
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Year |
2015 |
Publication |
Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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Volume |
48 |
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Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
525-533 |
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Keywords |
agricultural policy; supply analysis; mathematical programming; maximum-entropy; level; models |
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Abstract |
Together, sustainable management of natural resources and climate action form one of the three objectives of the 2014-2020 Common Agricultural Policy. This objective is being addressed by replacing the existing direct payments under Pillar 1 with a basic payment, combined with an additional payment conditional on farmers undertaking agricultural practices beneficial for the climate and the environment, a policy referred to as greening. In this study, the impact of greening was assessed using a hybrid model calibrated using positive mathematical programming. The model describes the macro-types of farm production in a Mediterranean agricultural area. The results show that greening was not beneficial throughout the study area and only some farm types have been particularly affected. However, greening appears to have a positive impact on curtailing the use of chemicals, particularly nitrogen, and on crop diversity. (C) 2015 Elsevier Ltd. All rights reserved. |
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0264-8377 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4746 |
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Author |
Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment |
Type |
Journal Article |
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Year |
2013 |
Publication |
Water Resource Management |
Abbreviated Journal |
Water Resource Manage. |
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27 |
Issue |
10 |
Pages ![sorted by First Page field, ascending order (up)](img/sort_asc.gif) |
3607-3622 |
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Keywords |
discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis |
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Abstract |
Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy. |
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0920-4741 |
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TradeM |
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MA @ admin @ |
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4487 |
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