KnE Life Sciences

ISSN: 2413-0877

The latest conference proceedings on life sciences, medicine and pharmacology.

Modeling Risk Reduction in Agriculture Associated with Dangerous Agrometeorological Phenomena

Published date: Nov 25 2019

Journal Title: KnE Life Sciences

Issue title: International Scientific and Practical Conference “AgroSMART – Smart Solutions for Agriculture”

Pages: 223--231

DOI: 10.18502/kls.v4i14.5608

Authors:

B A Ashabokovashabokov.boris@mail.ruDepartment of Cloud Physics, Federal State Budgetary Institution, High-Mountain Geophysical Institute, Nalchik, Russia; Institute of Informatics and Problems of Regional Management, KBSC of RAS, Nalchik, Russia

L M FedchenkoChief researcher, Federal State Budgetary Institution, High-Mountain Geophysical Institute, Nalchik, Russia

A A TashilovaDepartment of Cloud Physics, Federal State Budgetary Institution, High-Mountain Geophysical Institute, Nalchik, Russia

A V ShapovalovDepartment of Cloud Physics, Federal State Budgetary Institution, High-Mountain Geophysical Institute, Nalchik, Russia

A Kh KhavtsukovDepartment of Cloud Physics, Federal State Budgetary Institution, High-Mountain Geophysical Institute, Nalchik, Russia

S B BalkarovaInstitute of International Relations, Kabardino-Balkarian State University, Nalchik, Russia

Abstract:

The paper discusses possible approaches to reduce the risks associated with dangerous weather conditions. More specifically, the article considers the problem of reducing agricultural losses from such dangerous agrometeorological phenomena as hailstorm and drought. Within the framework of the decision-making theory, the formulation of the problem of reducing the losses of a considering industry from these phenomena is proposed – the objective is making decisions under risk. The features of the information support of this problem and the main tasks arising in the way of its practical use are discussed. The results of calculations that are carried out to analyze the effectiveness of the proposed method are given. The results of the calculations showed that the method is quite effective and can be used to reduce agricultural losses from hail.

References:

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