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Abstract
Understanding the spatiotemporal distribution pattern of hail disaster risk for cotton is crucial in mitigating hail disaster and promoting the sustainability of cotton farming. Based on such indexes as hail disaster frequency, spatiotemporal exposure, and vulnerability of cotton, we assess hail disaster risk for cotton, and analyze its spatiotemporal pattern and evolution in Mainland China from 1950 to 2009, supported by geographic information system (GIS). The following conclusions are drawn: (1) The proposed risk assessment method reveals the spatiotemporal difference of hail disaster risk for cotton at the county level. (2) Hail disaster risk for cotton is low in China, except for north of the North China Plain and the cotton-planting areas in Xinjiang Uygur Autonomous Region. From 1950 to 2009, hail disaster risk for cotton gradually increased. (3) The descending orders of hail disaster risk levels for cotton are bud stage, seedling stage, sowing and seeding stage, boll stage, and boll opening stage. The growth period with the highest risk varies across the cotton-planting areas. (4) The results of this paper are important for developing hail disaster prevention and reduction measures.
Highlights
Hail is an abrupt weather phenomenon [1]
Our results show that the counties with hail disaster risk above moderate level are mainly distributed in the North China Plain, Central China, Xinjiang Uygur Autonomous Region, Sichuan Basin
Understanding the spatiotemporal distribution pattern of hail disaster risk for cotton is crucial in mitigating hail disasters and promoting the sustainability of cotton farming
Summary
Hail is an abrupt weather phenomenon [1]. the effects of hailfalls usually interest limited areas, the damages can be severe [2], especially to agriculture [3,4,5,6,7,8]. Spatiotemporal analysis of hail disaster risk, including the distribution, intensity, frequency and reference period, will provide important information for decision-makers in developing corresponding mitigation planning and management countermeasures [10,11]. Most previous studies failed to reveal the spatiotemporal characteristics of hail disaster risk because of the conceptual confusion of hail event and hail disaster. Many scholars studied the spatiotemporal pattern of hails employing datasets of hailfall events instead of hail disasters. Previous studies are helpful in recognizing spatial distribution, regional variation, time cycles such as annual, seasonal and monthly of hails, they can neither reflect the space and time patterns of hail disasters, nor, reveal the spatiotemporal characteristics of hail disaster risks
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