In this study, a Bayesian network (BN)-based inhibition model is developed for the rainstorm–landslide–debris flow (R-L-D) disaster chain in the mountainous area of the Greater Bay Area (GBA), China, using the historical disaster data. Twelve nodes are selected for the inhibition model, which are classified into four types, including Hazardous Factor, Response Operation, Disaster Evolution, and Disaster Result. By combining the proposed inhibition with the scenario analysis method, the probabilities of the BN nodes under different rainfall scenarios are analyzed, and then the inhibitory effects of the environmental geological conditions and rescue speed on the R-L-D disaster chain under the most unfavorable rainfall scenario are investigated. On this basis, an inhibition framework consisting of the early warning, inhibition, and measures layers is proposed for the R-L-D disaster chain. The results reveal that under the most unfavorable rainfall scenarios, where the rainfall intensity is greater than 100 mm/d and the rainfall duration is greater than 24 h, the probability of landslides and debris flow is 0.930 and 0.665, respectively. Improving the environmental geological conditions such as slope, lithology and geological structure can greatly inhibit the occurrence of the R-L-D disaster chain. Moreover, the improvement of geological structure conditions is the most significant, and reduces the probability of landslides and debris flow by 0.684 and 0.430, respectively, as well as reducing the probability of death and direct economic loss by 0.411 and 0.619, respectively. Similarly, increasing the rescue speed leads to a reduction in the probability of death and direct economic loss by 0.201 and 0.355, respectively. This study can provide theoretical and practical insights into the prevention and inhibition of the R-L-D disaster chain.

The rational utilization of unconventional water sources is of great significance to areas where conventional water resources are scarce, and water resource allocation is an important way to realize the rational distribution of multiple water sources. This paper constructs a water resources allocation system integrating model data parameter database, water resources supply and demand prediction module, groundwater numerical simulation module and water resources allocation module. Taking brackish water as the main research object and final goal of achieving the best comprehensive optimization of social, economic and ecological benefits. The brackish water is incorporated as an independent water source into the water resource allocation model, and the stratum structure model and groundwater numerical model are constructed to simulate the brackish water level in the planning target year. The water resources allocation system is applied to Guantao County, China. The results show that increasing the development and utilization of brackish water under the recommended scheme can significantly reduce the water supply pressure of local fresh water resources in agriculture and industry. Compared with the current year, the overall water shortage in the region will be reduced by 4.493 × 10⁶ m³ in 2030, and meanwhile, the brackish water level will be decreased by 12.69 m in 2035, which plays a positive role in improving soil salinization.

Water pricing is the key to maximizing the economic and social benefits of the water transfer project. In this study, we propose the extended linear expenditure system-water price tolerance index (ELES-WPTI) model that combines the ELES model and the WPTI method for water pricing. Firstly, the ELES model is used to estimate the price elasticity of water demand and the basic demand for farmers of different income levels. Secondly, the WPTI method is used to simulate and analyze the affordability of farmers of different income levels for agricultural water under the dynamic change of water price standards. Finally, the ELES-WPTI model is applied to the Yinda-Jihuang (YJ) Project, China, to determine the appropriate agricultural water price. The results reveal that the farmers in the DH district have slightly higher affordability of water price than that in HL District. As water consumption should account for less than 15% of the total production cost and 10% of the net income, the affordable water price is determined to be 237 $/hm² in the DH district and 205 $/hm² in the HL district, respectively.

The disaster chain caused by strong typhoons has caused huge social economy and ecological environment impact on coastal areas. In this study, a special risk assessment model is proposed for the typhoon-storm tide-flood-embankment disaster chain based on its disaster mechanism and chain disaster law. The proposed model is developed to reflect both the disaster hazard which based on the probability distribution function of Bayesian network, and the carrier vulnerability which based on the evaluation index system. The model has been successfully applied in the coastal cities of Guangdong Province, China, and the disaster chain risk under three typical typhoon scenarios has been simulated. The results reveal that the risk distribution of different disasters caused by typhoons is different due to the different decisive factors. For storm tide disaster, the highest risk is mainly in the coastal city of Zhuhai, and as the influence of sea level increase caused by typhoon gradually weakens from coastal area to inland, the disaster chain risk gradually weakens from coastal to inland. For flood disaster, the highest risk is mainly distributed in the economically developed and densely populated Foshan City due to its low carrier vulnerability. For embankment disaster, the highest risk is mainly distributed in Zhongshan City due to its low design grade of dike, indicating that the condition of water conservancy project is an important factor in determining whether the dike failure or not. The research results are of great significance for coping with typhoon disaster chain in coastal areas, and have certain reference value for identifying the chain risk transmission of typhoon disaster.