Drought risk assessment of spring maize based on APSIM crop model in Liaoning province, China

Wang, Yaxu; Lv, Juan; Wang, Yicheng; Sun, Hongquan; Hannaford, Jamie ORCID: https://orcid.org/0000-0002-5256-3310; Su, Zhicheng; Barker, Lucy J. ORCID: https://orcid.org/0000-0002-2913-0664; Qu, Yanping. 2020 Drought risk assessment of spring maize based on APSIM crop model in Liaoning province, China. International Journal of Disaster Risk Reduction, 45, 101483. 11, pp. https://doi.org/10.1016/j.ijdrr.2020.101483

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Official URL: https://doi.org/10.1016/j.ijdrr.2020.101483

Abstract/Summary

Drought risk assessment is a vital part of drought risk management, which plays an important role in drought mitigation. Due to its complexity, drought risk is difficult to define and challenging to quantitatively assess, as the drought impacts associate with many social sectors. This contribution method the issue by quantitatively evaluating the yield loss due to drought as a function of the drought severity indicator in Liaoning province, China for spring maize using logarithmic regression. As crop water deficit is essence to identify agricultural drought, it developed a drought severity indicator using the crop water stress coefficient and duration. The Agricultural Production Systems sIMulator (APSIM) crop model was employed to simulate the spring maize growth to obtain daily water deficit during the growth period (May to September) and yield. The relationship between drought severity frequency and yield loss rate due to drought was established to assess the drought risk of spring maize when drought severity frequency is equal to 20%, 10%, 5% and 2%. The results show that Chaoyang and Fuxin have the highest drought risk in four levels of drought severity frequency whilst the lowest drought risk was identified in Tieling. The central Liaoning province has a moderate drought risk. For a specific drought severity frequency, drought risk increases from east to west in Liaoning province whilst it varies in each city at different drought severities. This method can predict yield loss due to drought for drought early warning. Drought risk maps presents spatial characteristics that can help to agricultural drought mitigation and the development of drought preparedness plan in Liaoning province.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.ijdrr.2020.101483
UKCEH and CEH Sections/Science Areas:	Water Resources (Science Area 2017-) Unaffiliated
ISSN:	2212-4209
Additional Keywords:	drought risk assessment, APSIM crop model, crop water deficit, yield loss due to drought
NORA Subject Terms:	Agriculture and Soil Science
Date made live:	23 Jan 2020 14:55 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/526558

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.ijdrr.2020.101483

UKCEH and CEH Sections/Science Areas:

Water Resources (Science Area 2017-)
Unaffiliated

ISSN:

2212-4209

Additional Keywords:

drought risk assessment, APSIM crop model, crop water deficit, yield loss due to drought

NORA Subject Terms:

Agriculture and Soil Science