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The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.

Relying on the support vector machine (SVM)-based classification model, the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face, and the identification calculation was carried out for the five test tunnels. Then, the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.

The results show that compared with the two classification models based on neural networks, the SVM-based classification model has a higher classification accuracy when the sample size is small, and the average accuracy can reach 87.9%. After the samples are replaced, the SVM-based classification model can still reach the same accuracy, whose generalization ability is stronger.

By applying the identification method described in this paper, the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified, and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting, and can provide a basis for local optimization of support parameters.

This paper aims to document the adaptation strategies developed by local farmers to adjust to climate change and related hazards in Lijiang Prefecture in Southwest China, and quantify the determinants of the adaptation measures.

The study conducted a household survey with 433 respondents in Lijiang to documents adaptation measures. The authors used a multivariate probit model to quantify five categories of adaptation measures against a set of household features, extension and information, resources, social network, financial assets and perception variables.

The most significant determinants consisted of information on early climate warnings and impending hazards, ownership to land and livestock, irrigation membership in community-based organisations, household savings, cash crop farming and perceptions of climate change and its related hazards. Adaptation strategies and policies highlighting these determinants could help to improve climate change adaptation in the region.

This study quantified the determinants of adaptive strategies and mapped important determinants for the region that will provide farmers with the appropriate resources and information to implement the best practices for adapting to climatic changes. The method and findings could be useful and easily replicable for future agriculture policies.