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| Author | Challinor, A.J.; Müller, C.; Asseng, S.; Deva, C.; Nicklin, K.J.; Wallach, D.; Vanuytrecht, E.; Whitfield, S.; Ramirez-Villegas, J.; Koehler, A.-K. | ||||
| Title | Improving the use of crop models for risk assessment and climate change adaptation | Type | Journal Article | ||
| Year | 2017 | Publication | Agricultural Systems | Abbreviated Journal | Agric. Syst. |
| Volume | 159 | Issue  |
Pages | 296-306 | |
| Keywords | Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty | ||||
| Abstract | Highlights • 14 criteria for use of crop models in assessments of impacts, adaptation and risk • Working with stakeholders to identify timing of risks is key to risk assessments. • Multiple methods needed to critically assess the use of climate model output • Increasing transparency and inter-comparability needed in risk assessments Abstract Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper. |
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| Publisher | Place of Publication | Editor | |||
| Language | Summary Language | phase 2+ | Original Title | ||
| Series Editor | Series Title | Abbreviated Series Title | |||
| Series Volume | Series Issue | Edition | |||
| ISSN | 0308521x | ISBN | Medium | ||
| Area | CropM | Expedition | Conference | ||
| Notes | CropM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 5175 | ||
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| Author | Sollitto, D.; De Benedetto, D.; Castrignanò, A.; Crescimanno, G.; Provenzano, G.; Ventrella, D. | ||||
| Title | Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy) | Type | Journal Article | ||
| Year | 2012 | Publication | Italian Journal of Agronomy | Abbreviated Journal | Ital. J. Agron. |
| Volume | 7 | Issue |
1 | Pages | 4 |
| Keywords | salinization risk; soil retention curve; geostatistics; factor Kriging; intrinsic random funciton | ||||
| 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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| Language | English | Summary Language | Original Title | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 2039-6805 1125-4718 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, ftnotmacsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4595 | ||
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| Author | Müller, C. | ||||
| Title | African lessons on climate change risks for agriculture | Type | Journal Article | ||
| Year | 2013 | Publication | Annual Review of Nutrition | Abbreviated Journal | Ann. Rev. Nutr. |
| Volume | 33 | Issue |
1 | Pages | 395-411 |
| Keywords | Africa/epidemiology; *Climate Change/economics; Crops, Agricultural/economics/*growth & development; Diet/adverse effects/economics; Forecasting; *Global Health/economics/trends; Humans; Malnutrition/economics/epidemiology/prevention & control; *Models, Theoretical; Risk; Soil/chemistry; Water Resources/economics | ||||
| Abstract | Climate change impact assessments on agriculture are subject to large uncertainties, as demonstrated in the present review of recent studies for Africa. There are multiple reasons for differences in projections, including uncertainties in greenhouse gas emissions and patterns of climate change; assumptions on future management, aggregation, and spatial extent; and methodological differences. Still, all projections agree that climate change poses a significant risk to African agriculture. Most projections also see the possibility of increasing agricultural production under climate change, especially if suitable adaptation measures are assumed. Climate change is not the only projected pressure on African agriculture, which struggles to meet demand today and may need to feed an additional one billion individuals by 2050. Development strategies are urgently needed, but they will need to consider future climate change and its inherent uncertainties. Science needs to show how existing synergies between climate change adaptation and development can be exploited. | ||||
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| Language | English | Summary Language | Original Title | ||
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| ISSN | 0199-9885 1545-4312 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4496 | ||
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| Author | Dono, G.; Raffaele, C.; Luca, G.; Roggero, P.P. | ||||
| Title | Income Impacts of Climate Change: Irrigated Farming in the Mediterranean and Expected Changes in Probability of Favorable and Adverse Weather Conditions | Type | Journal Article | ||
| Year | 2014 | Publication | German Journal of Agricultural Economics | Abbreviated Journal | German Journal of Agricultural Economics |
| Volume | 63 | Issue |
3 | Pages | 177-186 |
| Keywords | discrete stochastic programming; rdp measures to adapt to climate change; economic impact of climate change; irrigated agriculture and climate change; insurance tools for adaptation to climate change; water markets; risk; variability; management; systems | ||||
| Abstract | EU rural development policy (RDP) regulation 1305/2013 aims to protect farmers’ incomes from ongoing change of climate variability (CCV), and the increase in frequency of adverse climatic events. An income stabilization tool (IST) is provided to compensate drastic drops in income, including those caused by climatic events. The present study examines some aspect of its application focussing on Mediterranean irrigation area where frequent water shortages may generate significant income reductions in the current climate conditions, and may be further exacerbated by climate change. This enhanced loss of income in the future would occur due to a change in climate variability. This change would appreciably reduce the probability of weather conditions that are favourable for irrigation, but would not significantly increase either the probability of unfavourable weather conditions or the magnitude of their impact. As the IST and other insurance tools that protect against adversity and catastrophic events are only activated under extreme conditions, farmers may not consider them to be suitable in dealing with the new climate regime. This would leave a portion of the financial resources allocated by the RDP unused, resulting in less support for climate change adaptation. | ||||
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| Language | English | Summary Language | Original Title | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0002-1121 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, TradeM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4669 | ||
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| Author | Refsgaard, J.C.; Arnbjerg-Nielsen, K.; Drews, M.; Halsnaes, K.; Jeppesen, E.; Madsen, H.; Markandya, A.; Olesen, J.E.; Porter, J.R.; Christensen, J.H. | ||||
| Title | The role of uncertainty in climate change adaptation strategies – a Danish water management example | Type | Journal Article | ||
| Year | 2013 | Publication | Mitigation and Adaptation Strategies for Global Change | Abbreviated Journal | Mitig. Adapt. Strateg. Glob. Change |
| Volume | 18 | Issue |
3 | Pages | 337-359 |
| Keywords | Climate change; Adaptation; Uncertainty; Risk; Water sectors; Multi-disciplinary; change impacts; global change; winter-wheat; models; scenarios; ensembles; denmark; vulnerability; community; knowledge | ||||
| Abstract | We propose a generic framework to characterize climate change adaptation uncertainty according to three dimensions: level, source and nature. Our framework is different, and in this respect more comprehensive, than the present UN Intergovernmental Panel on Climate Change (IPCC) approach and could be used to address concerns that the IPCC approach is oversimplified. We have studied the role of uncertainty in climate change adaptation planning using examples from four Danish water related sectors. The dominating sources of uncertainty differ greatly among issues; most uncertainties on impacts are epistemic (reducible) by nature but uncertainties on adaptation measures are complex, with ambiguity often being added to impact uncertainties. Strategies to deal with uncertainty in climate change adaptation should reflect the nature of the uncertainty sources and how they interact with risk level and decision making: (i) epistemic uncertainties can be reduced by gaining more knowledge; (ii) uncertainties related to ambiguity can be reduced by dialogue and knowledge sharing between the different stakeholders; and (iii) aleatory uncertainty is, by its nature, non-reducible. The uncertainty cascade includes many sources and their propagation through technical and socio-economic models may add substantially to prediction uncertainties, but they may also cancel each other. Thus, even large uncertainties may have small consequences for decision making, because multiple sources of information provide sufficient knowledge to justify action in climate change adaptation. | ||||
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| Language | English | Summary Language | Original Title | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 1381-2386 1573-1596 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, ftnotmacsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4613 | ||
| Permanent link to this record | |||||