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Bojar, W., Sinabell, F., & Verburg, R. (2013). Economic and Trade Models to Analyze Climate Change Risk and Food Security for European Agriculture – A Survey..
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Bojar, W., & Leszek, K., Jacek Zarski, Wojciech Zarski, Cezary Slawinski, Piotr Baranowski. (2013). Integrating TradeM and CropM MACSUR models for regional case studies in Poland..
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Bojar, W., Żarski, J., Knopik, L., Kuśmierek-Tomaszewska, R., Sikora, M., & Dzieża, G. (2015). Markov chain as a model of daily total precipitation and a prediction of future natural events.. Braunschweig (Germany).
Abstract: The size of arable crop yields depends on many weather factors, such as precipitation and air temperature during the vegetation period. When studying the relation between yields and precipitation, not only the total amount of precipitation, but also the occurrence of long periods without precipitation must be taken into account. The paper [Bojar et al., 2014] demonstrated that barley yield significantly statistically depends on the length of the series of days without precipitation. This paper attempts to analyse the statistical data on daily precipitation totals recorded during the January – December periods in the years 1971 – 2013 at the weather station of the University of Science and Technology in Bydgoszcz, Faculty of Agriculture and Biotechnology, in the Research Centre located in an agricultural area in the Mochle township, situated 17 kilometres from Bydgoszcz. The primary statistical operation in the study is an attempt to estimate the Markov chain order. To this end, two criteria of chain order determination are applied: BIC (Bayesian information criterion, Schwarz 1978) and AIC (Akaike information criterion, Akaike 1974). Both are based on the log-likelihood functions for transition probability of the Markov chain constructed on certain data series. Statistical analysis of precipitation totals data leads to the conclusion that both AIC and BIC indicate the 2nd order for the studied Markov chain. The proposed method of estimating the variability of precipitation occurrence in the future will be utilised to improve region-related bio-physical and economical models, and to assess the risk of extreme events in the context of growing climate hazards. It will serve as basis for a search in agriculture for solutions mitigating those hazards.
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Bojar, W., & Zarski, J. (2014). “Methods of management with processes and resources in organizations and the economy”, “Application of water saving irrigation and fertigation systems in plants cultivation”. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: The first research project concerns methods of management with processes and resources in organizations and the economy. In order to address socio-economic problems, methods for evaluating the way in which natural resources are globally utilised in the face of the adverse effects of climate change must be developed. Previous findings of the project MACSUR allow to formulate the hypothesis that the method developed in UTP integrated with models of MACSUR partners is useful to assess the impact of climate change on food security in the context of growing economic risks in agricultural production. Verified hypothesis allows us to expect a common understanding on the assessment of the impact of climate change on food security in the light of the growing threat of food production.The second research project is to assess the feasibility and effectiveness of the system of drip irrigation in the cultivation of selected crops in the area of particularly large water shortages. Field studies are carried out in parallel on two soil types in the Research Centre of the University of Technology and Life Sciences near Bydgoszcz. The results confirm the possibility of a significant increase in productivity of irrigated plants on very light and light soils. The most important result of the synergistic relationship of this project to MACSUR project can be economic evaluation of the cost-effectiveness of surveyed plants under conditions of increasing drought probability. The results will be presented to stakeholders – agricultural producers, which will confront their usefulness in the management of farms.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER
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Bojar, W., Knopik, L., & Żarski, J. (2014). Integrated assessment of business crop productivity and profitability for use in food supply forecasting. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Climate change suggests long periods without rainfall will occur in the future quite often. Previous approach on dependence crop-yields from size of rain confirms the existence of a statistically significant relation. We built a model describing the amount of precipitation and taking into account periods of drought, using a mixture of gamma distribution and one point-distribution. Parameter estimators were constructed from rainfall data using the method of maximum likelihood. Long series of days or decades of drought allow to determine the probabilities of adverse developments in agriculture as the basis for forecasting crop yields in the future (years 2030, 2050). Forecasted yields can be used for assessment of productivity and profitability of some selected crops in Kujavian-Pomeranian region. Assumptions and parameters of large-scale spatial economic models will be applied to build up relevant solutions. Calculated with this approach output could be useful to expect decrease in agricultural output in the region. It will enable to shape effective agricultural policy to know how to balance food supply and demand through appropriate managing with stored food raw material and/or import/export policies. Used precipitation-yields dependencies method let verify earlier used methodology through comparison of obtained solutions concerning forecasted yields and closed to it uncertainty analysis.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER
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