Infopaket

Modelling in Agrometeorology

ОК 11.

Обов’язкова дисципліна для ОП

Second

2021/2022

2 Semester

6

Analyze the patterns of occurrence and development of processes and phenomena in the atmosphere in their interaction with other geospheres (PLO-1) Apply their knowledge to identify and solve problematic issues and make informed decisions in meteorology (PLO-2) Model atmospheric processes and phenomena using cartographic and mathematical methods and geographic information technologies (PLO-12)

Full-time form

Successful mastering of the courses "Meteorology", "Methods of agrometeorological and agroclimatic research", "Atmospheric physics", "Ecological climatology". Knowledge of the basic laws of the influence of weather and climate on agrophytocenoses. Ability to evaluate and analyze the features and consequences of the impact of weather conditions on agricultural production facilities. Possession of skills in processing agrometeorological and agroclimatic information, methods of agrometeorological forecasting, methods of synthesis and analysis of information.

the discipline is devoted to the study of theoretical foundations and methods of mathematical modeling of radiation, thermal and water regimes in agrophytocenoses, as well as their influence on the processes of growth, development and formation of crop yields. The course consists of two content modules. The first content module is devoted to the theory of modeling (basic principles of mathematical modeling in agrometeorology, properties of modeling objects and approaches to modeling energy and mass transfer in soil-plant cover). The second content module is devoted to the modeling of plant growth and development processes and crop yield formation, namely the study of the content, structure and features of the application of physico-statistical models and dynamic simulation models of the plant production process, as well as a review of modern approaches and prospects for modeling development. Installation and use of the R programming language.

1.Польовий А. М. Моделювання гідрометеорологічного режиму та продуктивності агроекосистем : [підручник] – Одеса: Екологія, 2013. – 432 с. 2. Genovese, G.P. (2001). Introduction to the MARS Crop Yield Forecasting System (MCYFS). Meeting on 4 and 5 October 2001, Luxembourg. Space Applications Institute, Joint Research Centre of the European Commission, Ispra, Italy, pp. 15. 3. Diepen, C.A. van. (1998). Application of simple interpolation methods in agrometeorology. In: B. Gozzini, M. Hims (Eds). Proceedings of workshop on dealing on spatialisation, 24-25 September, 1996, Toulouse. EUR 18473 EN, Office for Official Publications of the EU 4. Keulen, H. van, Diepen, C.A. van. (1990). Crop growth models and agro-ecological characterization. In: A. Scaife (Ed.). Proceedings of the first congress of the European Society of Agronomy, 5-7 December, Paris, CEC, ESA, INRA, pp. 1-16.

Lectures, practical, independent work

Knowledge control is carried out by a module-rating system, which provides a two-level assessment of the material learned. The maximum score is 100 points, 60 of which the student can gain during the semester control and 40 points - at the exam. The content module 1 (CM1) includes topics 1-5, the content module 2 (CM2) - topics 6-12.

Ukrainian