Study on fine early warning of maize high wind lodging disaster risk in Jilin Province, China

Abstract

Climate change has significantly disrupted human production and livelihoods. Frequent high wind-lodging disasters during the later stages of maize growth have reduced yields, threatening food security, agricultural systems, and sustainable development goals. This study introduces an innovative early risk warning system to guide agricultural resource allocation. It develops an early warning model for high wind-lodging disasters in maize that including natural, endogenous, and exogenous indicators. The model determines warning conditions, identifies early warning sources, analyzes warning signs, and predicts risk levels to support decision-making.

A comprehensive early warning model for maize high-wind-lodging disaster risk by integrating geographic, economic, and social indicators based on meteorological factors. The risk of maize lodging in Jilin Province from 1982 to 2021 was assessed. Spatial distribution analysis revealed an increasing regional risk warning level from maize joining to maturity, and the expansion of the area above the moderate warning level. The study showed that the early warning index was higher in the western region, with severe and extreme warning risks concentrated in Songyuan, Changchun, and Siping. The coupling coordination degree analysis of the early warning subsystems indicated high coordination in geoeconomic subsystems, with Changchun showing the potential for early coordinated subsystem development. We also revealed Changes in risk levels across different fertility stages in high-risk stages were also identified, offering direction for adjustment. This study provides valuable insights and data support for daily pre-disaster risk management, and demonstrates the model's adaptability to other maize-growing regions after adjusting indicators and parameters.