Drought Early Warning of Winter Wheat Based on Soil Water Dynamic Model Coupled with Grid Weather Forecast Data

He, L; Qian, Z; Jin, N; Yu, Q; Hou, Y

Drought Early Warning of Winter Wheat Based on Soil Water Dynamic Model Coupled with Grid Weather Forecast Data

He, L Qian, Z Jin, N Yu, Q

Hou, Y

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Publication Type:: Journal Article
Citation:: Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50, (9), pp. 170-176
Issue Date:: 2019-09-25

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Field	Value	Language
dc.contributor.author	He, L
dc.contributor.author	Qian, Z
dc.contributor.author	Jin, N
dc.contributor.author	Yu, Q https://orcid.org/0000-0001-6950-1821
dc.contributor.author	Hou, Y
dc.date.accessioned	2020-05-18T22:26:41Z
dc.date.available	2020-05-18T22:26:41Z
dc.date.issued	2019-09-25
dc.identifier.citation	Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50, (9), pp. 170-176
dc.identifier.issn	1000-1298
dc.identifier.uri	http://hdl.handle.net/10453/140790
dc.description.abstract	© 2019, Chinese Society of Agricultural Machinery. All right reserved. Drought is one of the most serious natural disasters and a threat of food security. It is extremely important to have accurate and timely early warning of drought for prevention and reduction of agricultural disasters. Current method of drought early warning was characterized by weak mechanism, low spatial resolution and lack of crop growth information. A daily crop growth and soil moisture dynamics simulation system using a soil water dynamic model in northern winter wheat zone was constructed. Based on this soil moisture simulation system, a drought early warning system for winter wheat was constructed. Daily drought early warning products from April to May in 2018 were generated by using this warning system. The results showed that forecast accuracy of soil relative moisture in next 10 days was high since its coefficient of determination was 0.63~0.91 and its root mean squared error was 5.6%~18.2%. The closer soil moisture forecast was in time, the more accurate was. Forecast accuracy of drought grades for severe and extreme drought was higher than those of mild and moderate grade. This drought warning system satisfied the needs of drought early warning in national agro-meteorological service department in China. The research result would provide scientific basis for prevention and reduction of agricultural disasters and national drought early warning services.
dc.language	en
dc.relation.ispartof	Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
dc.relation.isbasedon	10.6041/j.issn.1000-1298.2019.09.019
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject.classification	Mechanical Engineering & Transports
dc.title	Drought Early Warning of Winter Wheat Based on Soil Water Dynamic Model Coupled with Grid Weather Forecast Data
dc.type	Journal Article
utslib.citation.volume	50
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-05-18T22:26:36Z
pubs.issue	9
pubs.publication-status	Published
pubs.volume	50
utslib.start-page	170
utslib.citation.issue	9

Abstract:

© 2019, Chinese Society of Agricultural Machinery. All right reserved. Drought is one of the most serious natural disasters and a threat of food security. It is extremely important to have accurate and timely early warning of drought for prevention and reduction of agricultural disasters. Current method of drought early warning was characterized by weak mechanism, low spatial resolution and lack of crop growth information. A daily crop growth and soil moisture dynamics simulation system using a soil water dynamic model in northern winter wheat zone was constructed. Based on this soil moisture simulation system, a drought early warning system for winter wheat was constructed. Daily drought early warning products from April to May in 2018 were generated by using this warning system. The results showed that forecast accuracy of soil relative moisture in next 10 days was high since its coefficient of determination was 0.63~0.91 and its root mean squared error was 5.6%~18.2%. The closer soil moisture forecast was in time, the more accurate was. Forecast accuracy of drought grades for severe and extreme drought was higher than those of mild and moderate grade. This drought warning system satisfied the needs of drought early warning in national agro-meteorological service department in China. The research result would provide scientific basis for prevention and reduction of agricultural disasters and national drought early warning services.

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http://hdl.handle.net/10453/140790