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Author (up) Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R.
Title Integrated assessment of crop productivity based on the food supply forecasting Type Journal Article
Year 2016 Publication Agricultural Economics – Czech Abbreviated Journal Agricultural Economics – Czech
Volume 61 Issue 11 Pages 502-510
Keywords climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water
Abstract Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0139-570x ISBN Medium Article
Area Expedition Conference
Notes CropM, TradeM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4644
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Author (up) Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G.
Title Markov Chain as a Model of Daily Total Precipitation and a Prediction of Future Natural Events Type Conference Article
Year 2016 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Berlin (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference International Crop Modelling Symposium iCROPM 2016, 2016-05-15 to 2016-05-17, Berlin, Germany
Notes Approved no
Call Number MA @ admin @ Serial 4911
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Author (up) Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G.
Title Markov chain as a model of daily total precipitation and a prediction of future natural events Type Conference Article
Year 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords ft_macsur; MACSUR or FACCE acknowledged.
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.
Address
Corporate Author Thesis
Publisher Place of Publication Braunschweig (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig
Notes Approved no
Call Number MA @ admin @ Serial 4236
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Author (up) Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G.
Title Markov chain as a model of daily total precipitation and a prediction of future natural events Type Conference Article
Year 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords ft_macsur; MACSUR or FACCE acknowledged.
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.
Address
Corporate Author Thesis
Publisher Place of Publication Braunschweig (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig
Notes Approved no
Call Number MA @ admin @ Serial 4395
Permanent link to this record
 

 
Author (up) Żarski, J.; Dudek, S.; Kuśmierek-Tomaszewska, R.; Bojar, W.; Knopik, L.; Żarski, W.
Title Agroklimatologiczna ocena opadów atmosferycznych okresu wegetacyjnego w rejonie Bydgoszczy (Agro-climatological assessment of the growing season rainfall in the Bydgoszcz region) Type Journal Article
Year 2014 Publication Infrastruktura i Ekologia Terenów Wiejskich (Infrastructure and Ecology of Rural Areas) Abbreviated Journal Infrastruktura i Ekologia Terenów Wiejskich (Infrastructure and Ecology of Rural Areas)
Volume Ii Issue 3 Pages 643-656
Keywords rainfall; growing season; Bydgoszcz region; weather-yield model
Abstract The aim of the research was an agro-climatologic assessment of the amount of rainfall on a local scale, mainly aimed to identify trends in their changes and a possible rise in their variability over time. In the studies also we wanted to demonstrate the impact of the amount of rainfall in the region of Bydgoszcz on the yield of some crops. Material for the study consists of rainfall measurements, carried out in a stand- ard way in the years 1981-2010 at the Research Station of the University of Technology and Life Sciences in Bydgoszcz. Station is located in the village of Mochle, located approximately 20 km from the city centre (φ=53013’ N, λ=17051’E, h=98.5 m above sea level) in sparsely urbanized and industrialized area. We also used data of the yield of selected crops (potato, barley, corn for grain, legumes), from the production in the region of Kujawy and Pomorze as well as from our own experimental field. It has been shown that the average long-term rainfall during the growing season allows for classifying Bydgoszcz region as the area with the lowest rainfall in Poland. Analyzed rainfalls were characterized by a very high variability in time, resulting in climatic risk of plant growing. The largest temporal variability related to August. However, there was no extension of the time variability of rainfall totals in the period 1996-2010, as compared to the period 1981-1995. The sole significant growth trend during the period 1981-2010 was found in May. It appeared a tendency to a decline in summer rainfall totals (VI-VIII) in the annual rainfall total, which is consistent with the IPCC projections. Rainfall totals had highly signi cant impact on yields of selected crops. The highest correlation coefficients were found in relations crop-rainfall in the months of increased water needs of plants. Better correlations rainfall-crop were found using data from the production scale as compared with the scale of experimental field.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Polish Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4643
Permanent link to this record