Climatically driven yield variability of major crops in Khakassia (South Siberia)
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URI (for links/citations):
https://link.springer.com/article/10.1007/s00484-017-1496-9https://elib.sfu-kras.ru/handle/2311/111313
Author:
Elena A. Babushkina
Liliana V. Belokopytova
Dina F. Zhirnova
Santosh K. Shah
Tatiana V. Kostyakova
Corporate Contributor:
Хакасский технический институт — филиал СФУ
Научно-образовательная лаборатория "Дендроэкология и экологический мониторинг"
Кафедра строительства
Date:
2018-06Journal Name:
International Journal of BiometeorologyJournal Quartile in Scopus:
Q1Journal Quartile in Web of Science:
Q2Bibliographic Citation:
Elena A. Babushkina. Climatically driven yield variability of major crops in Khakassia (South Siberia) [Текст] / Elena A. Babushkina, Liliana V. Belokopytova, Dina F. Zhirnova, Santosh K. Shah, Tatiana V. Kostyakova // International Journal of Biometeorology. — 2018. — Т. 62 (№ 6). — С. 939-948Abstract:
We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: 1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; 2) the Central Zone, where crops yield depends mainly on temperatures; and 3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient and presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed
to estimate climate- and autocorrelation-induced variability of the crops yield. These
models allowed prediction of the possibility of yield decreasing by at least 2-11% in the
next decade due to increasing of the regional summer temperatures.