|
|
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.
|
|
|
|
Brüser, K. (2015). Crop production..
|
|
|
|
Boote, K. J., Porter, C., Jones, J. W., Thorburn, P. J., Kersebaum, K. C., Hoogenboom, G., et al. (2015). Sentinel site data for crop model improvement – definition and characterization. In J. L. Hatfield, & D. Fleisher (Eds.), (Vol. Advances in Agricultural Systems Modeling (7)). Madison, WI: ASA, CSSA, and SSSA.
|
|
|
|
Siczek, A., Horn, R., Lipiec, J., Usowicz, B., & Łukowski, M. (2015). Effects of soil deformation and surface mulching on soil physical properties and soybean response related to weather conditions. Soil and Tillage Research, 153, 175–184.
Abstract: A field experiment was conducted on Haplic Luvisol developed from loess to assess the effects of soil deformation and straw mulch on soil water status (matric potential), temperature, penetration resistance, soybean growth, seed yield and yield components including straw, protein and oil in 2006-2008. Water use efficiencies related to the amount of rainfall during the growing seasons were calculated for seeds and total above ground biomass. The soil deformation levels (main plots) comprised the following trials: non-compacted (NC, 0 tractor pass), moderately compacted (MC, 3 passes), and strongly compacted (SC, 5 passes). A uniform seedbed in all plots was prepared by harrowing before planting. The main plots included sub-plots without and with surface wheat straw mulch (0.5 kg m(-2)) and the corresponding trials were NC + M, MC + M, SC + M. The amount and distribution of rainfall during the growing season differed among the experimental years with extended drought at bloom-full seed (R2-R6) stages in 2006, good water supply in 2007, and alternative periods with relatively high and low rainfalls in 2008. The effect of soil deformation on matric potential was influenced by weather conditions, soybean growth phase, mulching and depth. The differences were greatest in 2007 and 2008 at R7-R8 growth stages. With increasing deformation level from NC to SC matric potential for 0-15 cm depth during these stages significantly decreased from -401 to -1184 kPa in 2007 and from -1154 to -1432 kPa in 2008. On mulched soil, the corresponding ranges were from -541 to -841 klpa and from -748 to -1386 kPa, respectively. In the dry summer 2006, the differences were smaller and less consistent. Irrespective of soil deformation level, mulching reduced soil temperature in most growth phases but most pronounced initially. Most yield components increased from NC to MC during the experiments which could be attributed to enhanced root water and nutrient uptake rates and decreased from MC to SC due to high soil strength that restrained root growth down to deeper depth. The yields of seeds, straw, protein and oil as well as water productivity of soybean seed and biomass were improved by mulching in 2007-2008. This improvement was more pronounced in 2007 when the mean yield of seeds, protein and oil were significantly greater by 16, 29 and 11%, respectively and was attributed to positive alterations in soil water retention. These results indicate the possibilities of improvement in soybean performance by identifying allowable amount of traffic and mulching practices at planting depending on weather fluctuations during the growing season. Since rainfall and air temperature distribution in 2007 are close to those averaged over a long period of time, the use of straw mulch may positively affect soybean performance and yields excluding anomalously dry years. The positive effect of straw mulch can be enhanced by moderate soil deformation combined with seedbed loosening before planting to avoid constraining effect of soil structure on crop establishment. (C) 2015 Elsevier B.V. All rights reserved.
|
|
|
|
van Bussel, L. G. J., Stehfest, E., Siebert, S., Müller, C., & Ewert, F. (2015). Simulation of the phenological development of wheat and maize at the global scale. Glob. Ecol. Biogeogr., 24(9), 1018–1029.
Abstract: AimTo derive location-specific parameters that reflect the geographic differences among cultivars in vernalization requirements, sensitivity to day length (photoperiod) and temperature, which can be used to simulate the phenological development of wheat and maize at the global scale. LocationGlobal. Methods Based on crop calendar observations and literature describing the large-scale patterns of phenological characteristics of cultivars, we developed algorithms to compute location-specific parameters to represent this large-scale pattern. Vernalization requirements were related to the duration and coldness of winter, sensitivity to day length was assumed to be represented by the minimum and maximum day lengths occurring at a location, and sensitivity to temperature was related to temperature conditions during the vegetative development phase of the crop. Results Application of the derived location-specific parameters resulted in high agreement between simulated and observed lengths of the cropping period. Agreement was especially high for wheat, with mean absolute errors of less than 3 weeks. In the main maize cropping regions, cropping periods were over- and underestimated by 0.5-1.5 months. We also found that interannual variability in simulated wheat harvest dates was more realistic when accounting for photoperiod effects. Main conclusions The methodology presented here provides a good basis for modelling the phenological characteristics of cultivars at the global scale. We show that current global patterns of growing season length as described in cropping calendars can be largely reproduced by phenology models if location-specific parameters are derived from temperature and day length indicators. Growing seasons can be modelled more accurately for wheat than for maize, especially in warm regions. Our method for computing parameters for phenology models from temperature and day length offers opportunities to improve the simulation of crop productivity by crop simulation models developed for large spatial areas and for long-term climate impact projections that account for adaptation in the selection of varieties
|
|
