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Author |
Dumont, B.; Leemans, V.; Ferrandis, S.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Assessing the potential of an algorithm based on mean climatic data to predict wheat yield |
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Journal Article |
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Year |
2014 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume  |
15 |
Issue |
3 |
Pages |
255-272 |
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Keywords |
stics model; yield prediction; real-time; proxy-sensing; stochastic weather generator; crop yield; mediterranean environment; simulation-model; variability; nitrogen; ensembles; forecasts; demeter; europe |
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Abstract |
The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days. |
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1385-2256 1573-1618 |
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CropM |
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no |
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Call Number |
MA @ admin @ |
Serial |
4621 |
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Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
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Title |
Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions |
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Journal Article |
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Year |
2015 |
Publication |
Precision Agriculture |
Abbreviated Journal |
Precision Agric. |
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Volume |
16 |
Issue |
4 |
Pages |
361-384 |
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Keywords |
nitrogen management; climatic variability; lars-wg weather generator; stics soil-crop model; pearson system; probability risk assessment; crop model stics; fertilizer nitrogen; generic model; wheat yield; maize; simulation; skewness; field; agriculture; scenarios |
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Abstract |
At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution. |
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1385-2256 |
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CropM, ft_macsur |
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MA @ admin @ |
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4519 |
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Holman, I.P.; Brown, C.; Carter, T.R.; Harrison, P.A.; Rounsevell, M. |
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Title |
Improving the representation of adaptation in climate change impact models |
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Journal Article |
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Year |
2019 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
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19 |
Issue |
3 |
Pages |
711-721 |
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Keywords |
Adaptive capacity; Limits; Water; Land; Decision making; Integrated assessment; Land-Cover Change; Global Change; River-Basin; Integrated Assessment; Adaptive Capacity; Vulnerability; Variability; Precautionary; Agriculture; Management |
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Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate. |
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2019-04-27 |
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ISSN |
1436-3798 |
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TradeM, ft_macsur |
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MA @ admin @ |
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5220 |
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Ventrella, D.; Giglio, L.; Charfeddine, M.; Dalla Marta, A. |
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Title |
Consumptive use of green and blue water for winter durum wheat cultivated in Southern Italy |
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Journal Article |
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Year |
2015 |
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Italian Journal of Agrometeorology |
Abbreviated Journal |
Italian Journal of Agrometeorology |
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20 |
Issue |
1 |
Pages |
33-44 |
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Keywords |
irrigation; water productivity; model simulation; climate change; climate-change scenarios; air co2 enrichment; impact; footprint; irrigation; simulation; yield; agriculture; variability; resources |
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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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CropM, ft_macsur |
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MA @ admin @ |
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4653 |
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Below, T.B.; Mutabazi, K.D.; Kirschke, D.; Franke, C.; Sieber, S.; Siebert, R.; Tscherning, K. |
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Title |
Can farmers’ adaptation to climate change be explained by socio-economic household-level variables |
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Journal Article |
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Year |
2012 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
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22 |
Issue |
1 |
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223-235 |
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Keywords |
Sub-Saharan Africa; Tanzania; Adaptive capacity; Index; Vulnerability; Adaptation; adaptive capacity; environmental-change; south-africa; vulnerability; variability; resilience; tanzania; framework; drought; policy |
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A better understanding of processes that shape farmers’ adaptation to climate change is critical to identify vulnerable entities and to develop well-targeted adaptation policies. However, it is currently poorly understood what determines farmers’ adaptation and how to measure it. In this study, we develop an activity-based adaptation index (AAI) and explore the relationship between socioeconomic variables and farmers’ adaptation behavior by means of an explanatory factor analysis and a multiple linear regression model using latent variables. The model was tested in six villages situated in two administrative wards in the Morogoro region of Tanzania. The Mlali ward represents a system of relatively high agricultural potential, whereas the Gairo ward represents a system of low agricultural potential. A household survey, a rapid rural appraisal and, a stakeholder workshop were used for data collection. The data were analyzed using factor analysis, multiple linear regression, descriptive statistical methods and qualitative content analysis. The empirical results are discussed in the context of theoretical concepts of adaptation and the sustainable livelihood approach. We found that public investment in rural infrastructure, in the availability and technically efficient use of inputs, in a good education system that provides equal chances for women, and in the strengthening of social capital, agricultural extension and, microcredit services are the best means of improving the adaptation of the farmers from the six villages in Gairo and Mlali. We conclude that the newly developed AAI is a simple but promising way to capture the complexity of adaptation processes that addresses a number of shortcomings of previous index studies. |
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0959-3780 |
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TradeM |
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MA @ admin @ |
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4467 |
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