Frontiers in Environmental Science (Oct 2022)
Weather index insurance for transition to sustainable cotton production under climate change in Xinjiang, China
Abstract
Assessing climate-induced reductions in cotton yields is critical to developing weather insurance for sustainable agricultural development. Climatic factors such as frost, hail, and drought severely constrain the sustainable development of cotton production in Xinjiang. In this study, based on cotton production and meteorological data from 1988 to 2019 in Aksu, Xinjiang, the H-P filtering method, correlation test, and regression analysis were used to develop a weather index model of cotton yield reduction rate and key meteorological factors. The results showed that the trend yield separated by the H-P filtering method was more stable. The correlation analysis between cotton fertility and meteorological factors concluded that there was a strong positive correlation between precipitation and cotton yield, i.e., the more rainfall, the more unfavorable environment for cotton growth and development. The results of the empirical analysis to determine the net premium rate under different disaster registrations based on the logistic probability distribution model showed that the highest probability of meteorological disasters in the Aksu region was 22.36%, the premium rate was 1.79%, and the net premium was 34.01 RMB per mu. It is found that climate change is closely related to the environment, and human production activities are compatible with the carrying capacity of the environment, otherwise, climate change leads to frequent meteorological disasters, which is not conducive to the sustainable development of agricultural production. It is expected that these research results can provide a relevant basis for the implementation of cotton policy weather insurance in Aksu and other regions and promote the sustainable development of cotton production.
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