The rapid development of catastrophe bonds provides a new idea for catastrophe risk dispersion, since its traditional means fail to afford the economic losses caused by the global drought catastrophe. With the deepening of the concept of the community with a shared future for mankind, there is an opportunity to issue global drought catastrophe bonds through international cooperation. Based on the data of global drought catastrophe losses from 1900 to 2018, this paper selects 21 countries as the primary participants of international cooperation and studies the pricing of drought catastrophe bonds by the POT model and high quantile estimation. The results show that the first-class bond has a 10% occurrence probability with the trigger point of $252.54 million, and the second-class one has a 35% occurrence probability with the trigger point being $117.13 million. In line with high quartile estimates, the one-year principal-protected catastrophe bonds with a face value of $1,000 are valued at $957.14 and $939.29, respectively. Besides, the principal portion of the lost bonds is $912.50 and $783.04, while the total of it is $867.86 and $626.79, respectively.

To reasonably evaluate and predict the loss of rainstorm and flood disaster, this study is based on the rainfall data and rainstorm and flood disaster data of 18 cities in Henan Province from 2010 to 2020, using GIS technology and weighted comprehensive evaluation method to analyze the risk of rainstorm and flood disaster factors in various regions. The four risk factors of hazard risk, hazard-pregnant environment sensitivity, hazard-bearing body vulnerability, and disaster resilience were analyzed in compartment analysis. At the same time, a new rainstorm and flood disaster prediction model was constructed in combination with the hybrid PSO-SVR algorithm. The research results show that there are many rivers in Henan Province, the terrain tends to be higher in the west and lower in the east, and most areas are low plains, making most cities in Henan Province at a moderate risk level. For the more developed cities such as Zhengzhou, Luoyang, and Nanyang, the hazard risk, sensitivity, vulnerability, and disaster resistance are high, and they are prone to heavy rains and floods. For the economically underdeveloped, the terrain is high or hills, such as Sanmenxia City; Xinyang City and other places have low hazard risk and are not prone to rainstorms and floods. By constructing a hybrid PSO-SVR model, selecting two representative cities of Zhengzhou and Luoyang, and predicting the daily rainfall, the number of disasters, and the direct economic loss, the calculated RMSE and MAPE values are both less than GA-SVR, the traditional SVR, and BPNN models, which have verified the superiority of the model proposed in this study and the practical value it brings. To further verify the prediction accuracy of the hybrid model, the average value of RMSE and MAPE of other 16 cities are calculated, and the result is still smaller than other three models, and the study can provide some decision-making references for the urban rainstorm and flood management.

This paper incorporates exogenous production shocks into short-run policy making process, and altruism is introduced into government utility functions under cooperative policy making scenario. The results reveal that the noisy signal from production shocks and governments self-interested behaviors consist of the main barriers to make cooperative trade negotiations between agricultural importers and exporters. Finally, the project puts forward that domestic public storage policy is a feasible way for storable agricultural products to buffer production shocks and to stabilize domestic price in the context of agricultural price fluctuations with high frequency, and limited function of the WTO with respect to restricting governments trade policies.

With the rapid development of industrialization and urbanization, atmospheric pollution research is vital for regional sustainable development and related policies formulated by the government. Previous studies have mainly studied a single evaluation method to analyze the air quality index (AQI) or single air pollutant. This research integrated the Spearman coefficient (SC) correlation analysis, a random search (RS) algorithm and an excellent extreme gradient boosting (XGBoost) algorithm to evaluate the air pollution influence of industrialization and urbanization (APIIU). Industrialization, urbanization and meteorological indicators were used to measure the influence degree of APIIU on AQI and particulate matter 2.5 (PM2.5), respectively. The main findings were: (1) the APIIU-AQI and APIIU-PM2.5 of Henan Province, Hubei Province and Hunan Province had significant changes from 2017 to 2019; (2) the value of square of determination coefficient of real value (R2), the root mean square error (RMSE) and the mean absolute percentage error (MAPE) of APIIU-AQI and APIIU-PM2.5 in three provinces predicted by the SC-RS-XGBoost were 0.945, 0.103, 4.25% and 0.897, 0.205, 4.84%, respectively; (3) the predicted results were more accurate than using a SC-XGBoost, RS-XGBoost, traditional XGBoost, support vector regression (SVR) and extreme learning machine (ELM).